personalized medicine

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pages: 433 words: 106,048

The End of Illness by David B. Agus

Danny Hillis, discovery of penicillin, double helix, epigenetics, germ theory of disease, Google Earth, impulse control, information retrieval, longitudinal study, meta analysis, meta-analysis, microbiome, Murray Gell-Mann, pattern recognition, Pepto Bismol, personalized medicine, randomized controlled trial, risk tolerance, Steve Jobs, the scientific method

Think about what it would be like, for instance, to know precisely how to tweak your diet to effortlessly lose twenty pounds for good, or to have a detailed list of things to avoid and things to embrace that make you feel fantastic and be in tip-top shape, or to know what the perfect amount of medicine X is for you to combat affliction Y successfully with no side effects. That’s the promise that personalized medicine has to offer. But, once again, you won’t be able to enjoy the benefits of personalized medicine until you get up close and personal with yourself. Nothing about health is one-size-fits-all, so until you know how to perform your own “fitting,” you won’t be able to live the long and happy life that’s awaiting you. The checklist below used to be buried deep in the book somewhere—long after I’d done a lot of explaining and storytelling—but I’ve since plucked it out and placed it here.

The End of Illness is a bold call for all of us to become our own personal health advocates, and a dramatic departure from orthodox thinking. This is a seminal work that promises to revolutionize how we live. DAVID B. AGUS, MD, is a professor of medicine and engineering at the University of Southern California Keck School of Medicine and Viterbi School of Engineering and heads USC’s Westside Cancer Center and the Center for Applied Molecular Medicine. He is the cofounder of two pioneering personalized medicine companies, Navigenics and Applied Proteomics. Dr. Agus is an international leader in cancer care and new technologies and approaches for personalized health care and chairs the Global Agenda Council on Genetics for the World Economic Forum. He has received numerous awards, including the 2009 GQ Magazine Rock Star of Science Award. On the cover: An image showing the beautiful richness and complexity of protein-based information derived from a drop of human blood.

I also hope that your future will be determined by the power of choice, and, when necessary, that it will guide you down pathways of healing. Only you can end illness. PART I The Science and Art of Defining Your Health If I had to sum up this entire book in a single phrase, it would be this: get to know yourself. I don’t mean that in a cosmic or purely psychological way. I’m a big believer in what’s called personalized medicine, which refers to customizing your health care to your specific needs based on your physiology, genetics, value system, and unique conditions. We are finally entering an exciting time in medicine where we have the technology to custom-tailor treatment and preventive protocols just as we’d custom-tailor a suit or designer gown to one’s individual body. But it all begins with you. You have to know yourself in a manner that you’ve probably never done before.

pages: 272 words: 64,626

Eat People: And Other Unapologetic Rules for Game-Changing Entrepreneurs by Andy Kessler

23andMe, Andy Kessler, bank run, barriers to entry, Berlin Wall, Bob Noyce, British Empire, business cycle, business process, California gold rush, carbon footprint, Cass Sunstein, cloud computing, collateralized debt obligation, collective bargaining, commoditize, computer age, creative destruction, disintermediation, Douglas Engelbart, Eugene Fama: efficient market hypothesis, fiat currency, Firefox, Fractional reserve banking, George Gilder, Gordon Gekko, greed is good, income inequality, invisible hand, James Watt: steam engine, Jeff Bezos, job automation, Joseph Schumpeter, Kickstarter, knowledge economy, knowledge worker, libertarian paternalism, low skilled workers, Mark Zuckerberg, McMansion, Netflix Prize, packet switching, personalized medicine,, prediction markets, pre–internet, profit motive, race to the bottom, Richard Thaler, risk tolerance, risk-adjusted returns, Silicon Valley, six sigma, Skype, social graph, Steve Jobs, The Wealth of Nations by Adam Smith, transcontinental railway, transfer pricing, wealth creators, Yogi Berra

See Market entrepreneurs; Political entrepreneurs EPI-LIT (entertainment and perishable information) Equality, myth of Equal opportunity Establishment, Alinsky on Exceptionalism and employee testing bans finding in colleges and intelligence and productivity of Vital Few FAB (Feature, Application, Business) Facebook Faggin, Federico Fama, Eugene Fannie Mae/Freddie Mac FarmVille Features, versus applications, businesses Federal Deposit Insurance Corporation (FDIC) Federal Reserve and interest rates and money supply roles of Ferguson, Andrew Ferriss, Tim Financial sector as Slimers as Sponges Firefox Flickr Ford, Henry Fox Broadcasting Fractional reserve banking Freedom Free Radicals accomplishments of defined historical examples of See also Rules for Free Radicals French Revolution Frick, Henry Clay Frick Museum Friedman, Tom Fulton, Robert Garrett, Jesse James Gates, Bill Generation X Generation Y Genes, personalized medicine Gesture recognition Gibbons v. Ogden Gilder, George Gladwell, Malcolm Global economy as economic alliance and horizontal integration Gold standard Google advertising book digitization cloud computing job application test as “link server,” Maps, and Ajax and Mozilla and scale Voice YouTube purchase by Gordon, John Steele Gore, Al Government employees, as Sloppers Greed, and profits Griggs v. Duke Power Grove, Andy Guns, Germs, and Steel (Diamond) Halstead, Maurice Halstead length Haves and Have-nots Health care the edge in personalized medicine Hedge funds, abundance, finding for Helú, Carlos Slim Henne, Albert Hersov, Rob Hewlett-Packard Hierarchy of needs Hoff, Ted Horizontal integration benefits of computers and voice communication and global economy and innovation and intellectual property ownership meaning of and price United States example How Capitalism Saved America (DiLorenzo) How We Got Here (Kessler) Hulu Humans, adapting technology to Hybrid autos IBM, vertical integration ICQ instant messaging Imperialism Income, generational differences Industrialization, and specialization Innovation, and horizontal integration Instant messaging, virtual pipe of Insurance companies, as Thieves Integration, horizontal Intel Intellectual property and horizontal integration and price cuts Intelligence (IQ), parameters of Intelligence at the edge cloud computing in health care social networking Interest rates, and Fed Internet digitized products, lack of protection of evolution of horizontal layers peer to peer (P2P) virtual pipes See also Networks; specific companies Internet stocks Investment capital, money/highest returns connection iPad iPhone iPod iTunes Jenkins, Holman Jobs Creators eliminating with technology licensed occupations replacing with technology Servers Slackers Slimers Sloppers Sponges Super Sloppers Thieves Jobs, Steve Junk bonds Kamangar, Salar Katzenberg, Jeffrey Keynes, John Maynard Kindle Kittler, Fred Kluge, John Lawyers, as Sponges Lehman Brothers bankruptcy Licenses, employment-related LinkedIn Livingston, Robert Longshoremen, as Sloppers McCaw, Craig McKnight, Dr.

Put two microphones instead of one in PCs and cell phones, like the iPhone, and you can get rid of background noise and virtually point the microphones at a speaker to figure out exactly what is being said in the middle of a hurricane. Today’s voice recognition is mostly awful, but that can be solved with not only faster and more powerful devices at the edge of the network but with algorithms and look-up tables to figure out spoken words and context, which will reside in the cloud. The same is going to happen with biotech and personalized medicine. The biotech industry got big creating new drugs that address smaller and smaller markets, but more effectively. But now what? Already there is a proliferation of protein tests and genomic tests that can start to figure out what unique disease and unique type of cancer you might have. The possibility of creating custom drugs is on the horizon, though held in check by Food and Drug Administration rules oriented around treating everyone with the same disease with the same drugs, rather than personalized one-off drugs.

Tools to sequence genes can be harnessed to identify and locate disease, as well as customize treatment. Lying down in giant imagers in specialized hospital rooms will give way to using handheld imagers. Beyond entertainment, this is what anyone with wealth beyond food and shelter spends their dough on. And gladly, if it keeps them ticking. OKAY, AS MUCH as I’m intrigued by personalized technology and personalized medicine, that’s not what I’m really talking about. Those things are in the physical realm. All great stuff, all with enormous productivity possibilities and huge upsides and big pots of wealth in their future. But true adaptive technologies are things that adapt to how you think. This is the big change over the next two decades. This is what a Free Radical will want to harness. Figure out what people want.

pages: 290 words: 82,871

The Hidden Half: How the World Conceals Its Secrets by Michael Blastland

air freight, Alfred Russel Wallace, banking crisis, Bayesian statistics, Berlin Wall, central bank independence, cognitive bias, complexity theory, Deng Xiaoping, Diane Coyle, Donald Trump, epigenetics, experimental subject, full employment, George Santayana, hindsight bias, income inequality, manufacturing employment, mass incarceration, meta analysis, meta-analysis, minimum wage unemployment, nudge unit, oil shock, p-value, personalized medicine, phenotype, Ralph Waldo Emerson, random walk, randomized controlled trial, replication crisis, Richard Thaler, selection bias, the map is not the territory, the scientific method, The Wisdom of Crowds, twin studies

Even if we knew everyone’s exact genotype, we have to remember the marmorkrebs’ astonishing variation – from identical genotypes to radically different phenotypes – and rightly wonder how far knowing everyone’s personal genotype can take us in the prediction of what will happen to each person or how they will respond to treatment. My instincts – you can tell – are with the sceptics, and after waving a finger in the air of the argument I’d say that precision or personalized medicine is about one part promise to an equal part hype. If we could settle for talking more modestly of ‘more precise’ medicine, rather than ‘precision’ or ‘personalized’ medicine, I’d feel more comfortable. This limitation is frustrating, as it suggests that to some extent we must live with probabilities which, for all their weaknesses, are often the best we can do. All the more reason, then, to use them properly. Thinking of these different scales – group and individual – as two different but compatible worlds can boggle the mind.

But unless we put it properly into proportion, recognizing its limitations, this knowledge is bluster, capable at the extreme of causing harm. However, if we do distinguish properly between weak and powerful probabilities, there is a genuine prize. This is more clarity about where governments and others can make a real difference. Probabilities can begin to do their job – at the big scale where they mostly belong – and help us to spot the more insistent patterns that we might most want to change. The age of personalized medicine? The problem of group knowledge turning to ignorance when we switch to an individual scale raises a natural question about where we should focus our efforts at tackling disease and other problems. Should we aim big – at the society or group level – or small, at the individual? How far is it even possible to aim small, given that so much of what we know is probabilistic, and probabilities are big-scale knowledge that can be poorly predictive for the individual?

This is the idea which at its most ambitious suggests we will soon be able to tailor treatment to the precise personal characteristics of each patient – so that drugs always work optimally – and even perhaps know from their genome which illnesses patients will have and how best to treat them. I fear that this talk feeds unrealistic expectations. There have been without question some startling advances in our ability to discover the basis of people’s illnesses, especially in genetics. But personalized medicine has several critics who wonder how far it’s feasible to know enough about individuals to treat them precisely or personally.22 Knowledge in medicine relies heavily – in research and in practice – on averages and probabilities: big-scale knowledge. It is very far from personalized, for good reason. A more ‘stratified’ medicine, more sensitive to different broad types of patient, I can see, so that drugs are targeted at the elderly, or the young, for example.

pages: 346 words: 92,984

The Lucky Years: How to Thrive in the Brave New World of Health by David B. Agus

active transport: walking or cycling, Affordable Care Act / Obamacare, Albert Einstein, butterfly effect, clean water, cognitive dissonance, crowdsourcing, Danny Hillis, Drosophila, Edward Lorenz: Chaos theory,, epigenetics, Kickstarter, longitudinal study, medical residency, meta analysis, meta-analysis, microbiome, microcredit, mouse model, Murray Gell-Mann, New Journalism, pattern recognition, personalized medicine, phenotype, placebo effect, publish or perish, randomized controlled trial, risk tolerance, statistical model, stem cell, Steve Jobs, Thomas Malthus, wikimedia commons

But I’m also worried that many people won’t benefit from this medical revolution unless they have a certain knowledge base and the tools to take action. At the same time, we also need society to continually and speedily build the framework and allocate resources to enable further changes to occur. I hope this book will help us all do just that. New technologies and constantly emerging data have produced the age of precision medicine, sometimes called personalized medicine. But precision medicine is still stuck in treatment mode—it’s being used primarily to learn how to treat your condition precisely once you have it. It hasn’t moved into the realm of prevention. However, it will, and it will shed the imperfections that distort the field today. For example, a major 2015 report published in the New England Journal of Medicine, one of the best, most respected medical journals in the world, warns that DNA testing results can be dramatically flawed.14 These genetic analyses that profile your DNA are supposed to assess risk for numerous ailments including cancer, heart conditions, and Alzheimer’s disease.

My clinic, for example, and eleven others across the country have teamed up with the IBM supercomputer known as Watson, which is being trained to analyze the genetic data from a patient’s cancer and search the scientific literature to help guide treatments for this patient. As the artificial-intelligence, “cognitive” computer gets more information and learns about matching patients to treatments, Watson helps us realize the goal of truly personalized medicine. The Washington Post summarized the hope perfectly: “And best of all, Watson will continue to learn on the job as it hunts for appropriate oncology treatments. That means that Watson will gain in value and knowledge over time, based on previous interactions with medical practitioners. The more that participating institutions use Watson to assist clinicians in identifying cancer-causing mutations, the more that Watson’s rationale and insights will improve.”5 At one time, we were afraid to have our financial info online or use a computer to transfer money and store our financial data.

Some would say that story exemplifies personalized or precision medicine—the medicine of the future, in which we will tailor treatments to a person’s unique physiology and health condition. But this approach is far from new. From Charaka, the father of ancient Indian practices (Ayurveda) to Hippocrates, the first father of modern medicine, many doctors throughout history have practiced the personalized approach to some degree using available technology for treating a disease. Today, however, personalized medicine is much more precise from a molecular standpoint. It focuses chiefly on DNA and how single-nucleotide polymorphisms (SNPs) and environmental factors influence an individual’s biology and risk for disease. SNPs are variations in DNA sequences that are thought to provide the genetic markers for our response to disease and drugs. For example, a variation on a particular gene may indicate a predisposition for high cholesterol.

pages: 100 words: 28,911

A Short Guide to a Long Life by David B. Agus

Danny Hillis, Ignaz Semmelweis: hand washing, lifelogging, meta analysis, meta-analysis, Murray Gell-Mann, personalized medicine, placebo effect, risk tolerance, the scientific method

You can buy or access equipment to take your blood pressure at most pharmacies, and some tools can even be downloaded as an application for your smart phone (see Rule 2). I’m a big believer in what’s called personalized medicine, which means customizing your health care to your specific needs based on your physiology, genetics, value system, and individual circumstances. Medicine is finally at a place where we have the technology to tailor treatment and preventive protocols to an individual, just like a seamstress can tailor a garment to a person’s body. But it all begins with you. You won’t be able to enjoy the benefits of personalized medicine until you take a close look at your unique body. Below is a list of general questions to ask yourself during your personal checkup every couple of months after you’ve completed the intense three-month initiation diary:1 • How would you rank your overall energy levels?

Thank you all for your support, and for spreading my mission to better medicine and our health far and wide. About the Author © PHIL CHANNING Dr. David B. Agus is a professor of medicine and engineering at the University of Southern California Keck School of Medicine and Viterbi School of Engineering and heads USC’s Westside Cancer Center and the Center for Applied Molecular Medicine. He is one of the world’s leading cancer doctors, and the cofounder of two pioneering personalized medicine companies, Navigenics and Applied Proteomics. Dr. Agus is an international leader in new technologies and approaches for personalized health care and a contributor to CBS News. His first book, The End of Illness, became a New York Times #1 bestseller and was also the subject of a PBS special. WWW.DAVIDAGUS.COM @DAVIDAGUS MEET THE AUTHORS, WATCH VIDEOS AND MORE AT DISCOVER MORE GREAT BOOKS AT We hope you enjoyed reading this Simon & Schuster eBook

pages: 181 words: 52,147

The Driver in the Driverless Car: How Our Technology Choices Will Create the Future by Vivek Wadhwa, Alex Salkever

23andMe, 3D printing, Airbnb, artificial general intelligence, augmented reality, autonomous vehicles, barriers to entry, Bernie Sanders, bitcoin, blockchain, clean water, correlation does not imply causation, distributed ledger, Donald Trump, double helix, Elon Musk,, epigenetics, Erik Brynjolfsson, Google bus, Hyperloop, income inequality, Internet of things, job automation, Kevin Kelly, Khan Academy, Kickstarter, Law of Accelerating Returns, license plate recognition, life extension, longitudinal study, Lyft, M-Pesa, Menlo Park, microbiome, mobile money, new economy, personalized medicine, phenotype, precision agriculture, RAND corporation, Ray Kurzweil, recommendation engine, Ronald Reagan, Second Machine Age, self-driving car, Silicon Valley, Skype, smart grid, stem cell, Stephen Hawking, Steve Wozniak, Stuxnet, supercomputer in your pocket, Tesla Model S, The Future of Employment, Thomas Davenport, Travis Kalanick, Turing test, Uber and Lyft, Uber for X, uber lyft, uranium enrichment, Watson beat the top human players on Jeopardy!, zero day

But now we can personalize analysis and treatments as never before. We will as consumers have unprecedented insights into and power to control our own health care. And augmenting our bodies and our minds will be possible by a plethora of biological and mechanical means unimaginable just a decade ago—if we choose to make such augmentations available. The Waistline and the New Paradigm for Personalized Medicine A good way to begin this chapter and our quick tour of the new frontiers in medicine is with something familiar, in particular, our waistlines. I love to eat. After my heart attack, though, I started watching my diet very closely. And I learned that perhaps the gravest health problem facing the global population is this disease of abundance called obesity. According to the U.S. Centers for Disease Control and Prevention, 36.5 percent of adult Americans are obese.

In reality, the wide disparity in our response to these stimuli most likely rests upon many biological factors we are only now starting to understand. These include not just our diets and our genes but also how our metabolisms fluctuate, the diversity of the bacteria living in our guts, and our environments—most evidently, what chemicals are in the air we breathe, the water we drink, and the food we consume. With this preliminary knowledge, we are starting to put in place a true system for personalized medicine. The cost of sequencing a human genome is now around $1,000 and should be below $100 within five years. Within a decade, it will cost less than getting a latte at Starbucks, less than reading the Sunday New York Times. But, to view it through this section’s filter, will these breakthroughs equally benefit all, or will they merely buttress existing disparities in health and wellness between rich and poor?

And the same rigorous data-based analysis could be applied not only to ways to make us healthier but also to problems in the medical system that result in needless pain, suffering, and deaths. From these insights will come ways to make even the most intimate medical procedures more highly automated and safe. Does the Technology Foster Autonomy Rather Than Dependence? I have given you a grand tour of the future of health care and personalized medicine and shown you the depth and breadth of its advances. The fact is that medicine is becoming an information technology and advancing at an exponential rate. We have become data, and our doctors are becoming software. And entrepreneurs all over the world are leading the charge. The key question now is whether this future will benefit all equally. In this case, I believe, the answer is a definite yes.

pages: 381 words: 78,467

100 Plus: How the Coming Age of Longevity Will Change Everything, From Careers and Relationships to Family And by Sonia Arrison

23andMe, 8-hour work day, Albert Einstein, Anne Wojcicki, artificial general intelligence, attribution theory, Bill Joy: nanobots, bioinformatics, Clayton Christensen, dark matter, disruptive innovation, East Village,, epigenetics, Frank Gehry, Googley, income per capita, indoor plumbing, Jeff Bezos, Johann Wolfgang von Goethe, Kickstarter, Law of Accelerating Returns, life extension, personalized medicine, Peter Thiel, placebo effect, post scarcity, Ray Kurzweil, rolodex, Silicon Valley, Simon Kuznets, Singularitarianism, smart grid, speech recognition, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Levy, Thomas Malthus, upwardly mobile, World Values Survey, X Prize

It took only sixteen years, however, for one-quarter of American households to get a personal computer, thirteen years for a cell phone, and seven years for Internet access, a promising trend for those who wish to see the widespread use of longevity technologies because health technologies are fast becoming information technologies.44 As we learned in Chapter 2, genomics, which will help usher in personalized medicine, already shows positive signs because costs are dropping at lightning speeds. “Biotech has gone exponential, like Moore’s law,” notes Andrew Hessel, a well-known synthetic biologist and cofounder of the Pink Army Cooperative, the world’s first cooperative biotechnology company. 45 At the time of the writing of this book, advances in biotech were moving faster than Moore’s law, according to which the number of transistors on an integrated circuit doubles approximately every two years.

Connected to the cause by Diamandis, both Hawking and King act as salespeople for the cause.28 For instance, Hawking says, “You may know that I am suffering from what is known as Amyotrophic Lateral Sclerosis (ALS), or Lou Gehrig’s Disease, which is thought to have a genetic component to its origin. It is for this reason that I am a supporter of the $10M Archon Genomics X PRIZE to drive rapid human genome sequencing. This prize and the resulting technology can help bring about an era of personalized medicine.”29 Larry King goes straight to the point when he asks, “What if we could learn how to stop heart disease from happening? What if we were able to reduce a person’s likelihood of cardiovascular disease based on his or her genetic profile, as well as on the individual’s age, gender, and lifestyle?”30 King continues, “It is my hope that by supporting the Archon Genomics X PRIZE to drive rapid human genome sequencing that we can get answers to these questions and help our Foundation save more lives in the years to come.”31 The message is that healthy life extension is possible, and the Genomics X PRIZE is contributing to achieving that goal.

Through Google, Larry Page has given over $250,000 to Singularity University and has said that if he were a student, SU is where he’d want to be.67 Interestingly, his wife, Lucy Southworth, is a biologist who has written papers on aging issues, including one titled “Effects of Aging on Mouse Transcriptional Networks,” coauthored with Stanford’s Dr. Stuart K. Kim, who is a well-known aging expert and one of Larry Ellison’s award recipients.68 Sergey Brin is spreading the meme in a more personal way. 23andMe is a genomics company that was cofounded by Brin’s biologist wife, Anne Wojcicki, and has gone a long way toward popularizing the idea of personalized medicine. “Spit parties” are one of the cute marketing techniques the company uses to get the public interested in thinking about their DNA and how it might be fixed to cure disease. One high-profile party took place during New York City’s Fashion Week. Company staffers recounted the event on their blog, saying, “23andMe managed to lure a few hundred people away from the catwalks Tuesday night to consider the beauty that lies within—DNA.

pages: 502 words: 107,657

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel

Albert Einstein, algorithmic trading, Amazon Mechanical Turk, Apple's 1984 Super Bowl advert, backtesting, Black Swan, book scanning, bounce rate, business intelligence, business process, butter production in bangladesh, call centre, Charles Lindbergh, commoditize, computer age, conceptual framework, correlation does not imply causation, crowdsourcing, dark matter, data is the new oil,, Erik Brynjolfsson, Everything should be made as simple as possible, experimental subject, Google Glasses, happiness index / gross national happiness, job satisfaction, Johann Wolfgang von Goethe, lifelogging, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, mass immigration, Moneyball by Michael Lewis explains big data, Nate Silver, natural language processing, Netflix Prize, Network effects, Norbert Wiener, personalized medicine, placebo effect, prediction markets, Ray Kurzweil, recommendation engine, risk-adjusted returns, Ronald Coase, Search for Extraterrestrial Intelligence, self-driving car, sentiment analysis, Shai Danziger, software as a service, speech recognition, statistical model, Steven Levy, text mining, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Thomas Davenport, Turing test, Watson beat the top human players on Jeopardy!, X Prize, Yogi Berra, zero-sum game

In so doing, might such scientifically based, individualized economic policies help resolve the crippling government deadlock that results from the opposing fiscal ideologies currently held by conservative and liberal policymakers? Personalized medicine. While one medical treatment may deliver better results on average than another, this one-size-fits-all approach commonly implemented by clinical studies means treatment decisions that help many may in fact hurt some. In this way, healthcare decisions backfire on occasion, exerting influence opposite to that intended: they hurt or kill—although they kill fewer than following no clinical studies at all. Personalized medicine aims to predict which treatment is best suited for each patient, employing analytical methods to predict treatment impact (i.e., medical influence) similar to the uplift modeling techniques used for marketing treatment decisions.

Revenue from interest payments and savings from fewer defaults Electoral politics Should we market to the constituent/in the state (swing voter/swing state)? Positive votes resulting from political election campaigns (see this chapter’s sidebar for how Obama’s 2012 campaign employed uplift modeling) Sociology Should we provide benefits to this individual? Improved social program outcome: long-term self-sufficiency Personalized medicine Which medical treatment should the patient receive? Favorable patient outcome in clinical healthcare This chapter covers in detail the first two areas in the table above. Here’s a bit more about the rest of them (note that for some of these application areas, no public case studies or proofs of concept yet exist—uplift modeling is an emerging technology). Content and channel selection.

Kim Larsen, “Net Lift Models: Optimizing the Impact of Your Marketing,” Workshop at Predictive Analytics World San Francisco Conference, San Francisco, CA, March 9, 2012. Measuring impact in sociology: James J. Heckman and Richard Robb Jr., “Alternative Methods for Evaluating the Impact of Interventions: An Overview,” Journal of Econometrics 30, issues 1–2 (October–November 1985): 239–267. Personalized medicine: Brian Claggett, Lihui Zhao, Lu Tian, Davide Castagno, and L. J. Wei, “Estimating Subject-Specific Treatment Differences for Risk-Benefit Assessment with Competing Risk Event-Time Data,” Harvard University Biostatistics Working Paper Series, Working Paper 125, March 2011. Ross E. McKinney Jr., MD, George M. Johnson, MD, Kenneth Stanley, MD, Florence H.

The Ethical Algorithm: The Science of Socially Aware Algorithm Design by Michael Kearns, Aaron Roth

23andMe, affirmative action, algorithmic trading, Alvin Roth, Bayesian statistics, bitcoin, cloud computing, computer vision, crowdsourcing, Edward Snowden, Elon Musk, Filter Bubble, general-purpose programming language, Google Chrome, ImageNet competition, Lyft, medical residency, Nash equilibrium, Netflix Prize, p-value, Pareto efficiency, performance metric, personalized medicine, pre–internet, profit motive, quantitative trading / quantitative finance, RAND corporation, recommendation engine, replication crisis, ride hailing / ride sharing, Robert Bork, Ronald Coase, self-driving car, short selling, sorting algorithm, speech recognition, statistical model, Stephen Hawking, superintelligent machines, telemarketer, Turing machine, two-sided market, Vilfredo Pareto

Of course, other neurons in the same network may have no clear function we can identify (just as in biological brains), so such techniques are rather hit-or-miss, and thus don’t seem to be a promising general methodology for interpretability. Self-Driving Morality As important as fairness, privacy, and interpretability are, we usually do not consider violations of them to be an immediate threat to our health and physical safety (although they can be in areas like criminal justice). But as algorithms come to play central roles in areas such as self-driving cars, personalized medicine, and automated warfare and weaponry, we are inevitably confronted with issues of algorithmic safety, morality, and accountability. While these are topics are being actively discussed in both scientific circles and the mainstream media, there is even less technical progress on them than there is on transparency. And perhaps this is as it should be—while the scientific agenda of this book has been the precise specification of social values and their subsequent algorithmic internalization, maybe there are some norms that we can’t or don’t want to formalize and don’t want algorithms to encode or enforce.

Second, machine learning is a powerful tool that has many extant and potential benefits. Technology companies such as Google and Facebook of course rely on products powered by machine learning for much of their revenue—but as these techniques grow in applicability, their scope and societal benefits grow as well. Rather than simply improving the click-through rate of targeted advertising, if learning procedures can improve the accuracy and efficacy of personalized medicine, they can potentially save lives. If they can predict creditworthiness from a broader set of indicators than just traditional measures such as income, savings, and credit card history, they can expand access to credit to a broader population. Realistic examples of this potential are endless. Although the risks of algorithmic decision-making are all too real, as we have shown throughout this book, avoiding those risks does not require giving up entirely on the benefits.

See also societal norms and values nuclear weapons, 180–81 online shopping algorithms, 116–21, 123–24 Open Science Foundation, 161 optimization and algorithmic violations of fairness and privacy, 96 and data collection bias, 90 and definitions of fairness, 70–72 and differential privacy, 44–45 and echo chamber equilibrium, 125 and equilibrium in game theory, 98–99 and “fairness gerrymandering,” 87 and fairness vs. accuracy, 75–83 and interpretability of model outputs, 174–75 “Maxwell solution,” 105–11 and navigation problems, 102–4, 112 and online shopping algorithms, 116, 122 Pareto optimal solutions, 128, 193 and product recommendation algorithms, 123–24 statistical parity vs. optimal decision-making, 72 threat of optimization gone awry, 179–88 and unintended results, 189–90 and unique challenges of algorithms, 10 outcome trees, 140 outliers, 122 overfitting data, 31, 136, 159, 167 pairwise correlations, 57–58 parable on machine learning pitfalls, 182–83 Pareto, Vilfredo, 81 Pareto frontier (Pareto curves), 63, 81–86, 89, 128, 193 parity, statistical, 84 Partnership on AI to Benefit People and Society, 15 patient records. See medical records and data Pentland, Sandy, 145–46 performance reporting, 140–41 personal data, 171 personalized medicine, 191–92 p-hacking, 144–46, 153–59, 161, 169–70. See also adaptive data analysis phone apps, 2 physiology research, 141–43 plausible deniability, 41 policy, 82–84 political affiliation data, 25–26, 51–52 political bias, 14–15 portfolio management, 81 post hoc rationalization, 191. See also adaptive data analysis “power pose” research, 141–42, 157–58 precise specification goal and adaptive data analysis, 160, 164 and algorithmic morality, 175–76 and design of ethical algorithms, 4, 190–94 and differential privacy, 36–37 and theoretical computer science field, 12 and threat of optimization gone awry, 181–82 prediction and dangers of adaptive data analysis, 152, 155 design of ethical algorithms, 193 and differing notions of fairness, 85 and fairness vs. accuracy of models, 77 and “merit” in algorithmic fairness, 74 “predictive policing,” 92–93 and scope of topics covered, 18–19 and statistical parity, 71 preferences, 116, 136 preregistration of scientific studies, 160–62 The Preregistration Revolution (Nosek), 160 priming studies, 142–43, 158 principled algorithms, 174 Prisoner’s Dilemma, 99–100 privacy and algorithmic morality, 175–77 and algorithms as regulatory measure, 16–18 and concerns about algorithm use, 3 and correlation equilibrium, 114–15 and current state of ethics research, 169–70 and dating apps, 96 and design of algorithms, 5 and design of ethical algorithms, 192–95 and differential privacy, 40, 42–45 and goals of ethics research, 171 and medical research, 34–36 and movie recommendation algorithms, 36–37 parameters, 37–38 and recent efforts to address machine learning issues, 14–15 and scope of topics covered, 18–21 and shortcomings of anonymization methods, 24 and theoretical computer science field, 12–14 and threat of optimization gone awry, 184–85 and unique challenges of algorithms, 7, 10 and weaknesses of aggregate data, 30 and weaknesses of encryption, 33–34 product ratings, 118–23 programming languages, 6 proliferation of algorithms, 3 proxy data, 67 pseudocode, 9–10 publication incentives, 136 publicly available data, 51 public transportation, 112 publishing pressures, 144–45 p-values, 138–39, 141 Pynchon, Thomas, 117–18 quadratic time algorithms, 4–5 quantitative properties of algorithms, 194.

pages: 398 words: 105,032

Soonish: Ten Emerging Technologies That'll Improve And/or Ruin Everything by Kelly Weinersmith, Zach Weinersmith

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 23andMe, 3D printing, Airbnb, Alvin Roth, augmented reality, autonomous vehicles, connected car, double helix, Elon Musk,, Google Glasses, hydraulic fracturing, industrial robot, information asymmetry, Kickstarter, low earth orbit, market design, megastructure, microbiome, moral hazard, multiplanetary species, orbital mechanics / astrodynamics, personalized medicine, placebo effect, Project Plowshare, QR code, Schrödinger's Cat, self-driving car, Skype, stem cell, Tunguska event

“UK Scientists Gain Licence to Edit Genes in Human Embryos.” Nature 530, no. 7588 (2016):18. Campbell, T. A., Tibbits, S., and Garrett, B. “The Next Wave: 4D Printing—Programming the Material World.” Atlantic Council. May 2014. Carini, C., Menon S. M., and Chang, M. Clinical and Statistical Considerations in Personalized Medicine. London: Chapman and Hall/CRC, 2014. Carney, Scott. The Red Market: On the Trail of the World’s Organ Brokers, Bone Thieves, Blood Farmers, and Child Traffickers. New York: William Morrow, 2011. Centers for Disease Control and Prevention. “CDC Media Statement on Newly Discovered Smallpox Specimens.” CDC News Releases. July 8, 2014. Chandler, Michele.

Proceedings of Baylor University Medical Center 25, no. 1 (2012): 49–57. Craig, Alan B. Understanding Augmented Reality: Concepts and Applications. Amsterdam: Morgan Kaufmann, 2013. Craven, B. A., Paterson, E. G., and Settles, G. S. “The Fluid Dynamics of Canine Olfaction: Unique Nasal Airflow Patterns As an Explanation of Macrosmia.” Journal of the Royal Society Interface 7, no. 47 (2010):933–43. Cullis, Pieter. The Personalized Medicine Revolution: How Diagnosing and Treating Disease Are About to Change Forever. Vancouver: Greystone Books, 2015. Daniels, K.E. “Rubble-Pile Near Earth Objects: Insights from Granular Physics.” In Asteroids, edited by V. Badescu, 271–86. Berlin and Heidelberg: Springer, 2013. DAQRI. “Smart Helmet.” 2016. Delaney, K., and Massey, T.

Scientific American, April 1, 2016. International Space Elevator Consortium. “Space Elevator Home.” 2016. ITER. “The Way to New Energy.” 2016. Jafarpour, F., Biancalani, T., and Goldenfeld, N. “Noise-Induced Mechanism for Biological Homochirality of Early Life Self-Replicators.” Physical Review Letters 115, no. 15 (2015):158101. Jain, Kewal K. Textbook of Personalized Medicine. New York: Humana Press, 2015. JAXA. “3-2-2-1 Settlement of Claim between Canada and the Union of Soviet Socialist Republics for Damage Caused by Cosmos 954.’” Japan Aerospace Exploration Agency. Released on April 2, 1981. Jella, S. A., and Shannahoff-Khalsa, D. S. “The Effects of Unilateral Forced Nostril Breathing on Cognitive Performance.”

pages: 239 words: 45,926

As the Future Catches You: How Genomics & Other Forces Are Changing Your Work, Health & Wealth by Juan Enriquez

Albert Einstein, Berlin Wall, bioinformatics, borderless world, British Empire, Buckminster Fuller, business cycle, creative destruction, double helix, global village, half of the world's population has never made a phone call, Howard Rheingold, Jeff Bezos, Joseph Schumpeter, Kevin Kelly, knowledge economy, more computing power than Apollo, new economy, personalized medicine, purchasing power parity, Ray Kurzweil, Richard Feynman, Robert Metcalfe, Search for Extraterrestrial Intelligence, SETI@home, Silicon Valley, spice trade, stem cell, the new new thing

Then Milton Wright went home to care for his two children … Wilbur and Orville … Bicycle mechanics … Who used “Pride of the West” ladies’ underwear cloth … To cover the wings … Of the world’s first airplane.11 Gene chips will lead to personalized medicine … You will be able to test whether one medicine or another works better for you … Before you take it. You cannot do that today … Which is why when you buy a drug … And open the box … The first thing you get … Is a long list of the ways in which … The prescription you paid for … May hurt you.12 (I.e., this medicine may cause bleeding, cramps, dry mouth, impotence, insomnia, irritability, nausea, and other fun stuff.) Thalidomide is one example of highly personalized medicine … Few images are as devastating as the pictures of deformed children published in Life … Caused by prescribing a “safe sedative” to pregnant women.

pages: 294 words: 80,084

Tomorrowland: Our Journey From Science Fiction to Science Fact by Steven Kotler

Albert Einstein, Alexander Shulgin, autonomous vehicles, barriers to entry, Burning Man, carbon footprint, Colonization of Mars, crowdsourcing, Dean Kamen, epigenetics, gravity well, haute couture, interchangeable parts, Kevin Kelly, life extension, Louis Pasteur, low earth orbit, North Sea oil, Oculus Rift, oil shale / tar sands, peak oil, personalized medicine, Peter H. Diamandis: Planetary Resources, private space industry, RAND corporation, Ray Kurzweil, Richard Feynman, Ronald Reagan, self-driving car, stem cell, Stephen Hawking, Stewart Brand, theory of mind, Watson beat the top human players on Jeopardy!, Whole Earth Catalog, WikiLeaks

Today’s chemotherapies are offshoots of chemical warfare agents; we’ve turned weapons into cancer medicines, albeit crude ones. As with carpet bombing, collateral damage is a given. Now, because of advances in genetics, we know that each cancer is unique, and research is shifting to the development of personalized medicines — designer therapies that can exterminate specific cancerous cells in a specific way, in a specific person. Forget collateral damage, these therapies are focused like lasers. The Finnish pharmaceutical Oncos Therapuetics has treated over two hundred patients using just such methods. But it wouldn’t take much at all to subvert them, turning personalized medicines into personalized weapons. In the coming years, criminals will doubtless dedicate significant resources to exploiting these biological advances, just as they’ve exploited a panoply of earlier technologies. Today biocrime is in its infancy.

Thus fields with a huge potential to drive techno-physio evolution — artificial intelligence, nanotechnology, biology, robotics, networks, sensors, etc. — are now advancing along exponential growth curves. Consider genomic sequencing, long touted as the “essential tool” needed to move medicine from standardized and reactive to personalized and preventative. In 1990, when the Human Genome Project was first announced, the cost of this tool was budgeted at $3 billion — about as far from personalized medicine as one can get. But by 2001, costs were down to $300 million. By 2010, they were below $5,000. In 2012, the $1,000 barrier had fallen. Within ten years, at the current rate of decline, a fully sequenced human genome will price out at less than $10. If standardized and reactive medicine managed to double human life span in a century, just imagine how far personalized and preventative medicine might extend that total.

pages: 271 words: 52,814

Blockchain: Blueprint for a New Economy by Melanie Swan

23andMe, Airbnb, altcoin, Amazon Web Services, asset allocation, banking crisis, basic income, bioinformatics, bitcoin, blockchain, capital controls, cellular automata, central bank independence, clean water, cloud computing, collaborative editing, Conway's Game of Life, crowdsourcing, cryptocurrency, disintermediation, Edward Snowden,, Ethereum, ethereum blockchain, fault tolerance, fiat currency, financial innovation, Firefox, friendly AI, Hernando de Soto, intangible asset, Internet Archive, Internet of things, Khan Academy, Kickstarter, lifelogging, litecoin, Lyft, M-Pesa, microbiome, Network effects, new economy, peer-to-peer, peer-to-peer lending, peer-to-peer model, personalized medicine, post scarcity, prediction markets, QR code, ride hailing / ride sharing, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, SETI@home, sharing economy, Skype, smart cities, smart contracts, smart grid, software as a service, technological singularity, Turing complete, uber lyft, unbanked and underbanked, underbanked, web application, WikiLeaks

Operating in collaboration with university collaborators (Baylor College of Medicine’s Human Genome Sequencing Center) and Amazon Web Services, the DNAnexus solution is perhaps the largest current data store of genomes, having 3,751 whole human genomes and 10,771 exomes (440 terabytes) as of 2013.147 The progress to date is producing a repository of 4,000 human genomes, out of the possible field of 7 billion humans, which highlights the need for large-scale models in these kinds of big data projects (human whole-genome sequencing). The DNAnexus database is not a public good with open access; only 300 worldwide preapproved genomic researchers have permission to use it. The Genomic Data Commons148 is a US-government-funded large-scale data warehouse and computational computing project being assembled to focus on genomic research and personalized medicine. In this case, the resource is said to be available to any US-based researcher. This is a good step forward in organizing data into standard unified repositories and allowing access to a certain population. A further step could be using an appcoin like Genomecoin to expand access on a grander scale as a public good fully accessible by any individual worldwide. Further, the appcoin could be the tracking, coordination, crediting, and renumerative mechanism sponsoring collaboration in the Genome Data Commons community.

“Sales of Genetic Scans Direct to Consumer Through deCODEme Have Been Discontinued! Existing Customers Can Access Their Results Here Until January 1st 2015.” 143 Castillo, M. “23andMe to Only Provide Ancestry, Raw Genetics Data During FDA Review.” CBS News, December 6, 2013. 144 Swan, M. “Health 2050: The Realization of Personalized Medicine Through Crowdsourcing, the Quantified Self, and the Participatory Biocitizen.” J Pers Med 2, no. 3 (2012): 93–118. 145 ———. “Multigenic Condition Risk Assessment in Direct-to-Consumer Genomic Services. Genet Med 12, no. 5 (2010): 279–88; Kido, T. et al. “Systematic Evaluation of Personal Genome Services for Japanese Individuals.” Nature: Journal of Human Genetics 58 (2013):734–41. 146 Tamblyn, T.

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50 Future Ideas You Really Need to Know by Richard Watson

23andMe, 3D printing, access to a mobile phone, Albert Einstein, artificial general intelligence, augmented reality, autonomous vehicles, BRICs, Buckminster Fuller, call centre, clean water, cloud computing, collaborative consumption, computer age, computer vision, crowdsourcing, dark matter, dematerialisation, digital Maoism, digital map, Elon Musk, energy security, failed state, future of work, Geoffrey West, Santa Fe Institute, germ theory of disease, global pandemic, happiness index / gross national happiness, hive mind, hydrogen economy, Internet of things, Jaron Lanier, life extension, Mark Shuttleworth, Marshall McLuhan, megacity, natural language processing, Network effects, new economy, oil shale / tar sands, pattern recognition, peak oil, personalized medicine, phenotype, precision agriculture, profit maximization, RAND corporation, Ray Kurzweil, RFID, Richard Florida, Search for Extraterrestrial Intelligence, self-driving car, semantic web, Skype, smart cities, smart meter, smart transportation, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, strong AI, Stuxnet, supervolcano, telepresence, The Wisdom of Crowds, Thomas Malthus, Turing test, urban decay, Vernor Vinge, Watson beat the top human players on Jeopardy!, web application, women in the workforce, working-age population, young professional

First, many drugs are starting to fall out of patent restrictions, and generic drug makers (particularly in Asia) are becoming more aggressive about attacking patents so that generic “lookalike” drugs are getting to be cheaper and more commonplace. The second reason for the trend is technology. Developments in areas such as genomics and personal phenotyping mean that personalized medicine is becoming a reality, and pharmaceutical companies are shifting research and development expenditure toward specialty products and therapies that target niche medical conditions and subpopulations. A 9 million euro, EU-funded project, Food4Me, is being launched to look at all aspects of personalized nutrition—namely how food intake could be tailored to suit each individual’s physical and genetic makeup. Perhaps rather than call it personalized medicine, we should call it personalized health. There’s even a European study on delivering personalized nutrition according to phenotype. In the end, it really is up to you to look after yourself by whatever method you choose from the hundreds of possibilities available so that you don’t need medicine.

pages: 424 words: 114,905

Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again by Eric Topol

23andMe, Affordable Care Act / Obamacare, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, artificial general intelligence, augmented reality, autonomous vehicles, bioinformatics, blockchain, cloud computing, cognitive bias, Colonization of Mars, computer age, computer vision, conceptual framework, creative destruction, crowdsourcing, Daniel Kahneman / Amos Tversky, dark matter, David Brooks, digital twin, Elon Musk,, epigenetics, Erik Brynjolfsson, fault tolerance, George Santayana, Google Glasses, ImageNet competition, Jeff Bezos, job automation, job satisfaction, Joi Ito, Mark Zuckerberg, medical residency, meta analysis, meta-analysis, microbiome, natural language processing, new economy, Nicholas Carr, nudge unit, pattern recognition, performance metric, personalized medicine, phenotype, placebo effect, randomized controlled trial, recommendation engine, Rubik’s Cube, Sam Altman, self-driving car, Silicon Valley, speech recognition, Stephen Hawking, text mining, the scientific method, Tim Cook: Apple, War on Poverty, Watson beat the top human players on Jeopardy!, working-age population

With several of these drugs with sales of more than $10 billion per year (such as Humira, Enbrel, Remicade), you can quickly get a sense of the magnitude of waste incurred. FIGURE 2.3: Schematic showing the number of people with clinical responsiveness to top ten drugs by gross sales in 2014. The gray schematic people represent clinical responders, the black nonresponders. Source: Adapted from N. Schork, “Personalized Medicine: Time for One-Person Trials,” Nature (2015): 520(7549), 609–611. These data do not simply illustrate that medicines don’t work or are some kind of profiteering racket. Rather, in most cases these drugs don’t work because physicians have not honed an ability to predict what sort of person will respond to a treatment or acquired adequate knowledge about an individual to know whether the patient is among those people who will respond positively to a treatment.

Health systems now have remarkable investment assets, like Kaiser Health with over $40 billion, Ascension Health with more than $17 billion, and Cleveland Clinic with over $9 billion.2 Along with the explosive economic growth of healthcare, the practice of medicine has been progressively dehumanized. Amazingly, ninety years ago, Francis Peabody predicted this would happen: “Hospitals… are apt to deteriorate into dehumanized machines.”3 (Parenthetically, if you read one paper cited in this chapter, this would be the one.) Rather than all the talk of “personalized” medicine, business interests have overtaken medical care. Clinicians are squeezed for maximal productivity and profits. We spend less and less time with patients, and that time is compromised without human-to-human bonding. The medical profession has long been mired in inefficiency, errors, waste, and suboptimal outcomes. In recent decades, it has lost its way from taking true care of patients. A new patient appointment averages twelve minutes, a return visit seven.

Welch, “Cancer Screening, Overdiagnosis, and Regulatory Capture.” 24. Centers for Medicare and Medicaid Services. August 8, 2018. 25. Silverman, E., “Why Did Prescription Drug Spending Hit $374B in the US Last Year? Read This,” Wall Street Journal. 2015; Berkrot, B., “U.S. Prescription Drug Spending as High as $610 Billion by 2021: Report,” Reuters. 2017. 26. Schork, N. J., “Personalized Medicine: Time for One-Person Trials.” Nature, 2015. 520(7549): pp. 609–611. 27. Villarosa, L., “Why America’s Black Mothers and Babies Are in a Life-or-Death Crisis,” New York Times. 2018. CHAPTER 3: MEDICAL DIAGNOSIS 1. Tversky, A., and D. Kahneman, “Judgment Under Uncertainty: Heuristics and Biases.” Science, 1974. 185(4157): pp. 1124–1131. 2. Lewis, M., The Undoing Project: A Friendship That Changed Our Minds. 2016.

The Book of Why: The New Science of Cause and Effect by Judea Pearl, Dana Mackenzie

affirmative action, Albert Einstein, Asilomar, Bayesian statistics, computer age, computer vision, correlation coefficient, correlation does not imply causation, Daniel Kahneman / Amos Tversky, Edmond Halley, Elon Musk,, experimental subject, Isaac Newton, iterative process, John Snow's cholera map, Loebner Prize, loose coupling, Louis Pasteur, Menlo Park, pattern recognition, Paul Erdős, personalized medicine, Pierre-Simon Laplace, placebo effect, prisoner's dilemma, probability theory / Blaise Pascal / Pierre de Fermat, randomized controlled trial, selection bias, self-driving car, Silicon Valley, speech recognition, statistical model, Stephen Hawking, Steve Jobs, strong AI, The Design of Experiments, the scientific method, Thomas Bayes, Turing test

Bierut points out one problem with VanderWeele and Christiani’s analysis: they had only one measure of smoking behavior—the number of cigarettes per day. The gene could possibly cause people to inhale more deeply to get a larger dose of nicotine per puff. The Harvard study simply didn’t have data to test this theory. Even if some uncertainty remains, the research on the smoking gene provides a glimpse into the future of personalized medicine. It seems quite clear that in this case the important thing is how the gene and behavior interact. We still don’t know for sure whether the gene changes behavior (as Bierut suggests) or merely interacts with behavior that would have happened anyway (as VanderWeele’s analysis suggests). Nevertheless, we may be able to use genetic status to give people better information about the risks they face.

Another role of Big Data in causal inference problems lies in the last stage of the inference engine described in the Introduction (step 8), which takes us from the estimand to the estimate. This step of statistical estimation is not trivial when the number of variables is large, and only big-data and modern machine-learning techniques can help us to overcome the curse of dimensionality. Likewise, Big Data and causal inference together play a crucial role in the emerging area of personalized medicine. Here, we seek to make inferences from the past behavior of a set of individuals who are similar in as many characteristics as possible to the individual in question. Causal inference permits us to screen off the irrelevant characteristics and to recruit these individuals from diverse studies, while Big Data allows us to gather enough information about them. It’s easy to understand why some people would see data mining as the finish rather than the first step.

NOTES TO CHAPTER ONE then the opposite is true: In other words, when evaluating an intervention in a causal model, we make the minimum changes possible to enforce its immediate effect. So we “break” the model where it comes to A but not B. We should thank the language: I should also mention here that counterfactuals allow us to talk about causality in individual cases: What would have happened to Mr. Smith, who was not vaccinated and died of smallpox, if he had been vaccinated? Such questions, the backbone of personalized medicine, cannot be answered from rung-two information. Yet we can answer: To be more precise, in geometry, undefined terms like “point” and “line” are primitives. The primitive in causal inference is the relation of “listening to,” indicated by an arrow. NOTES TO CHAPTER TWO And now the algebraic magic: For anyone who takes the trouble to read Wright’s paper, let me warn you that he does not compute his path coefficients in grams per day.

Suggestible You: The Curious Science of Your Brain's Ability to Deceive, Transform, and Heal by Erik Vance

fixed income, hive mind, impulse control, Isaac Newton, meta analysis, meta-analysis, personalized medicine, placebo effect, randomized controlled trial, Ronald Reagan, side project, stem cell, Steve Jobs, Yogi Berra

This is who we are. After 2,000 years as an eccentric medical mystery, placebo effects are starting to take shape out of the fog. But although these tricks work on everyone, they do not work the same for everyone. Some people look at Rosario and see a caring and capable community healer, while others see a scam artist with a handful of basil. Some see homeopathy as a tested and proven form of personalized medicine. Others see water in a fancy vial. Everyone’s door to expectation has a different key, and everyone is suggestible in a slightly different way. But once that door is unlocked, we have access to an amazing power to heal ourselves. For all human history, this bizarre thing—that Hippocrates warned us about, that Avicenna tried to screen out, that Mesmer capitalized on, that Jellinek dismissed, and that obliterated 1,000 modern medicines—was the brain’s own method of self-medication.

Certainly placebos enhance the effect of a drug, but do they also interact with a drug—just as one would expect when you mix two chemicals inside the human body? Most important, if there was ever truly a way to separate placebo responders from the rest of society—either by personality or brain scans or genetics—what would we do with that information? Bar them from all drug trials? If we did that, wouldn’t we have to bar them from taking the drugs that came out of such trials? Placebo research promises to open a path to some of the first truly personalized medicine on Earth. But will that medicine prove an inspiring beacon of inclusion or will it be just another way to classify and exclude people? The placebo effect is an elegant and fascinating phenomenon that beckons us to dig deeper into its mysteries. It is at the same time broadly significant and deeply personal. It reaches to the earliest days of recorded history and out to a new, gleaming future.

pages: 307 words: 92,165

Fabricated: The New World of 3D Printing by Hod Lipson, Melba Kurman

3D printing, a long time ago in a galaxy far, far away, additive manufacturing, barriers to entry, Berlin Wall, carbon footprint, cloud computing, crowdsourcing, dumpster diving,, factory automation, game design, global supply chain, invisible hand, James Watt: steam engine, Jeff Bezos, Kickstarter, Lean Startup, lifelogging, Mars Rover, Marshall McLuhan, microcredit, Minecraft, new economy, off grid, personalized medicine, Ray Kurzweil, Richard Feynman, stem cell, Steve Jobs, technological singularity, the market place

Cells signal to one another in ways that we have yet to decode. Advances in traditional design software, medical imaging and data analysis will pave the way for 3D printing replacement parts for living creatures. But will we soon see commercial design software for body parts? Not yet. But we’re inching closer every year. “I’m seeing a convergence between the world of simulation software, medical imaging, and CAD systems.” Chris joked, “It will personalize medicine for us, which is good if you plan to need extra body parts in the future.” In industrial product design, designers are learning that as their design tools improve, nature becomes an increasingly useful source of inspiration. In body design, it will be the same. Living creatures are the product of millions of years of ruthless, iterative design cycles. Janine Benyus, an author and design visionary, said, “We’ve discovered again and again that biomimicry works because it offers a turnaround strategy for our species, a practical way for us to fit in and flourish on this planet by emulating 3.8 billion years of brilliant designs and strategies.”10 Shades of gray: Taking pictures inside the body If there’s no design software for body parts, how is it possible that people today are able to print teeth and bone replacements?

To cut the time and potential mishaps of a real surgery, surgeons practice assembling, pushing on, even stapling together these practice parts. Surgical models also help surgeons communicate surgical procedures to the patient’s families. Veterinarians practice an upcoming hip surgery for a dog using 3D printed surgical models of the dog’s bones. 3D printed surgical models and inanimate prosthetic body parts are just the beginning. Bioprinting will take personalized medicine to new heights. In the meantime, medical researchers and technologists face a broad array of barriers, from technological to biological to social to regulatory. Our bodies are composed of thousands of different sorts of materials and today’s 3D printers can print just a few materials at a time. Complex organs are full of blood vessels. Many critical organs such as the heart leave no room for technical glitches or adjustments.

pages: 340 words: 97,723

The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity by Amy Webb

Ada Lovelace, AI winter, Airbnb, airport security, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, artificial general intelligence, Asilomar, autonomous vehicles, Bayesian statistics, Bernie Sanders, bioinformatics, blockchain, Bretton Woods, business intelligence, Cass Sunstein, Claude Shannon: information theory, cloud computing, cognitive bias, complexity theory, computer vision, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, Deng Xiaoping, distributed ledger, don't be evil, Donald Trump, Elon Musk, Filter Bubble, Flynn Effect, gig economy, Google Glasses, Grace Hopper, Gödel, Escher, Bach, Inbox Zero, Internet of things, Jacques de Vaucanson, Jeff Bezos, Joan Didion, job automation, John von Neumann, knowledge worker, Lyft, Mark Zuckerberg, Menlo Park, move fast and break things, move fast and break things, natural language processing, New Urbanism, one-China policy, optical character recognition, packet switching, pattern recognition, personalized medicine, RAND corporation, Ray Kurzweil, ride hailing / ride sharing, Rodney Brooks, Rubik’s Cube, Sand Hill Road, Second Machine Age, self-driving car, SETI@home, side project, Silicon Valley, Silicon Valley startup, skunkworks, Skype, smart cities, South China Sea, sovereign wealth fund, speech recognition, Stephen Hawking, strong AI, superintelligent machines, technological singularity, The Coming Technological Singularity, theory of mind, Tim Cook: Apple, trade route, Turing machine, Turing test, uber lyft, Von Neumann architecture, Watson beat the top human players on Jeopardy!, zero day

The nanobot can walk around, pick up molecules, and deposit them in designated locations. Another variety of nanobot, propelled by gas bubbles, can deliver microscopic amounts of medicine without causing injury. The advent of commercially available nanobots, which share information with our PDRs, have replaced one-size-fits-most medications and therapies, treating our specific ailments without causing side effects. Now that both Amazon and Apple are offering personalized medicine, most people have willingly injected themselves with organic nanobots. Even Amazon families have access through a subsidized program approved by the US government. Nanobots continually monitor and treat us, so the life expectancy for average Americans shot from 76.1 years in 2019 up to 99.7 years today.6 It didn’t take long for us to see the potential drawbacks of injectable AGI. The nanobots did exactly what their creators had intended.

Government Coalition, 228; gender-nonconforming people and false accusations of identity theft, 222; Google Blue households, 217, 219, 225; Google Green households, 217, 219, 224, 225; Google households, 216–217, 218; Google Yellow households, 217, 219, 225; health and wellness minders, 219; health data open access, 209; healthcare, 224–226; high-tech brothels with AI-powered sexbots, 219–220; home AI kitchen appliance glitches, 214–215; ignoring AI’s developmental track, 207; intermarriage among Amazon, Apple, and Google households, 220; job displacement, 220; lack of AI education among government leaders, 211; life expectancy, 225; nanobot-induced abortions, 225; nanobot-induced deaths, 225–226; nanobot health monitoring and treatment, 224–226; OmniVision smart glasses, 221; Organization Data Records, 226; PDR as social credit score, 209; PDRs, 208–209, 218, 226; personalized medicine, 224; rising numbers of AI accidents and mistakes, 208; self-driving taxi services and Amazon riders, 218–219; self-driving taxi services and Google riders, 219; transparency among G-MAFIA, 208; 2049, 223–228; 2069, 228–229; 2029, 214–223; U.S. economic and diplomatic actions against China, 227; U.S. government ignoring China’s AI infrastructure and economy, 210–211; unemployment, 226. See also names of specific companies Future and AI, optimistic scenario of, 151, 155–178, 233; architectural trends, 171–172; brain-to-machine interfaces, 176–177; business management, 166; China adoption of GAIA norms and standards, 172; computational pharmacists and pharmacies, 173; construction and building industries, 165; Contributing Team Member Test, 169, 171, 175; crime, 172, 175–176; cubesat networks, 168; Dartmouth inaugural intergovernmental forum, 157–158; dating, sex, and marriage, 164–165, 174; education, 167; face recognition payment options in stores, 162; Federal Smart Infrastructure Administration (FSIA), 176; filmmaking, 165–166; first artificial general intelligence system (AGI), 169–171; G-MAFIA actions against China’s nefarious AI use, 156; G-MAFIA addressing climate change, 171–172; G-MAFIA Coalition adoption of transparency as core value, 157; G-MAFIA Coalition formalization, 157; G-MAFIA privacy commitment, 168; G-MAFIA mixed reality products and services partnerships, 160–161, 165; G-MAFIA nudging toward healthier lifestyles, 162–163; GAIA (Global Alliance on Intelligence Augmentation) and, 158, 159, 176; GAIA decision and actions to prevent ASI creation, 177–178; GAIA regular meetings, 160; genome sequencing, 174; grocery shopping and delivery services, 161–162; health care systems, 163–164, 173–174; home AI systems and appliances, 161, 172–173; job displacement and AGI, 172; journalism, 167–168, 175; law enforcement, 176; meal-kit services linked to household PDR, 162; music, 174–175; new types of criminal activity and AGI, 172; PDR individual ownership 159; PDRs treated as distributed ledgers, 159; PDRs and privacy, 168; Project Hermione (AGI), 169–171; quick-service stores, 162; robotic pets, 162; sensory computation, 160; smart camera surveillance in retail stores, 162; smart city pilot programs, 168, 176; 2049, 169–177; 2069, 177–178; 2029, 159–169; U.S. government AI funding, 156; workforce preparation for computing’s third era, 157.

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The Human Age: The World Shaped by Us by Diane Ackerman

23andMe, 3D printing, additive manufacturing, airport security, Albert Einstein, augmented reality, back-to-the-land, carbon footprint, clean water, dark matter, dematerialisation, double helix, Drosophila, epigenetics, Google Earth, Google Glasses, haute cuisine, Internet of things, Loebner Prize, Louis Pasteur, Masdar, mass immigration, megacity, microbiome, nuclear winter, personalized medicine, phenotype, Ray Kurzweil, refrigerator car, Search for Extraterrestrial Intelligence, SETI@home, skunkworks, Skype, stem cell, Stewart Brand, the High Line, theory of mind, urban planning, urban renewal, Whole Earth Catalog

“We’re in the midst of probably the biggest revolution in biology,” says Mark Mehler, chair of the Department of Neurology at Albert Einstein College of Medicine. “It’s forever going to transform the way we understand genetics, environment, the way the two interact, what causes disease. It’s another level of biology, which for the first time really is up to the task of explaining the biological complexity of life.” “The Human Genome Project was supposed to usher in a new era of personalized medicine,” Mehler told the American Academy of Neurology at its annual meeting in 2011. “Instead, it alerted us to the presence of a second, more sophisticated genome that needed to be studied.” Despite the DNA of twins, for example, they’re never perfect matches. If one has schizophrenia, the odds of her twin developing it are only 50 percent, not 100 percent as one might assume since they have identical genes.

I was bottle-fed formula, but breast-milk-fed babies grow stronger immune systems because breast milk, often the first source of nourishment, teems with more than seven hundred species of hubbub-loving, life-enhancing bacteria. Researchers are thinking of cobbling them into infant formula to help ward off asthma, allergies, and such autoimmune triggermen as diabetes, eczema, and multiple sclerosis. Babies pick up other useful bacteria in Mom’s dirt-and-crumb-garlanded home and landscape. At least, they should. Doctors are embracing the idea of personalized medicine based on a patient’s uniquely acquired flora and fauna, as revealed in his or her genome, epigenome, and microbiome. No more antibiotics prescribed by the jeroboam on the off chance they might prove useful. Instead, try unleashing enough beneficial bacteria to crowd out the pathogen. No more protecting children from the hefty stash of derring-do white-knight bacteria they need but we’ve learned to regard as icky.

pages: 371 words: 108,317

The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future by Kevin Kelly

A Declaration of the Independence of Cyberspace, AI winter, Airbnb, Albert Einstein, Amazon Web Services, augmented reality, bank run, barriers to entry, Baxter: Rethink Robotics, bitcoin, blockchain, book scanning, Brewster Kahle, Burning Man, cloud computing, commoditize, computer age, connected car, crowdsourcing, dark matter, dematerialisation, Downton Abbey, Edward Snowden, Elon Musk, Filter Bubble, Freestyle chess, game design, Google Glasses, hive mind, Howard Rheingold, index card, indoor plumbing, industrial robot, Internet Archive, Internet of things, invention of movable type, invisible hand, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Kevin Kelly, Kickstarter, lifelogging, linked data, Lyft, M-Pesa, Marc Andreessen, Marshall McLuhan, means of production, megacity, Minecraft, Mitch Kapor, multi-sided market, natural language processing, Netflix Prize, Network effects, new economy, Nicholas Carr, old-boy network, peer-to-peer, peer-to-peer lending, personalized medicine, placebo effect, planetary scale, postindustrial economy, recommendation engine, RFID, ride hailing / ride sharing, Rodney Brooks, self-driving car, sharing economy, Silicon Valley, slashdot, Snapchat, social graph, social web, software is eating the world, speech recognition, Stephen Hawking, Steven Levy, Ted Nelson, the scientific method, transport as a service, two-sided market, Uber for X, uber lyft, Watson beat the top human players on Jeopardy!, Whole Earth Review, zero-sum game

Every day the machine mixes the right doses of all the powders and stuffs them all into a single personalized pill (or two), which I take. During the day my biological vitals are tracked with wearable sensors so that the effect of the medicine is measured hourly and then sent to the cloud for analysis. The next day the dosage of the medicines is adjusted based on the past 24-hour results and a new personalized pill produced. Repeat every day thereafter. This appliance, manufactured in the millions, produces mass personalized medicine. My personal avatar is stored online, accessible to any retailer. It holds the exact measurements of every part and curve of my body. Even if I go to a physical retail store, I still try on each item in a virtual dressing room before I go because stores carry only the most basic colors and designs. With the virtual mirror I get a surprisingly realistic preview of what the clothes will look like on me; in fact, because I can spin my simulated dressed self around, it is more revealing than a real mirror in a dressing room.

The average normal is not very useful to you specifically. But with long-term self-tracking, you’d arrive at a very personal baseline—your normal—which becomes invaluable when you are not feeling well, or when you want to experiment. The achievable dream in the near future is to use this very personal database of your body’s record (including your full sequence of genes) to construct personal treatments and personalized medicines. Science would use your life’s log to generate treatments specifically for you. For instance, a smart personalized pill-making machine in your home (described in Chapter 7) would compound medicines in the exact proportions for your current bodily need. If the treatment in the morning eased the symptoms, the dosage in the evening would be adjusted by the system. The standard way of doing medical research today is to run experiments on as many subjects as one possibly can.

pages: 133 words: 42,254

Big Data Analytics: Turning Big Data Into Big Money by Frank J. Ohlhorst

algorithmic trading, bioinformatics, business intelligence, business process, call centre, cloud computing, create, read, update, delete, data acquisition, DevOps, fault tolerance, linked data, natural language processing, Network effects, pattern recognition, performance metric, personalized medicine, RFID, sentiment analysis, six sigma, smart meter, statistical model, supply-chain management, Watson beat the top human players on Jeopardy!, web application

It is the platform of Big Data that is making such lofty goals attainable. The validation of Big Data analytics can be illustrated by advances in science. The biomedical corporation Bioinformatics recently announced that it has reduced the time it takes to sequence a genome from years to days, and it has also reduced the cost, so it will be feasible to sequence an individual’s genome for $1,000, paving the way for improved diagnostics and personalized medicine. The financial sector has seen how Big Data and its associated analytics can have a disruptive impact on business. Financial services firms are seeing larger volumes through smaller trading sizes, increased market volatility, and technological improvements in automated and algorithmic trading. DATA AND DATA ANALYSIS ARE GETTING MORE COMPLEX One of the surprising outcomes of the Big Data paradigm is the shift of where the value can be found in the data.

pages: 179 words: 43,441

The Fourth Industrial Revolution by Klaus Schwab

3D printing, additive manufacturing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, barriers to entry, Baxter: Rethink Robotics, bitcoin, blockchain, Buckminster Fuller, call centre, clean water, collaborative consumption, commoditize, conceptual framework, continuous integration, crowdsourcing, digital twin, disintermediation, disruptive innovation, distributed ledger, Edward Snowden, Elon Musk, epigenetics, Erik Brynjolfsson, future of work, global value chain, Google Glasses, income inequality, Internet Archive, Internet of things, invention of the steam engine, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, life extension, Lyft, mass immigration, megacity, meta analysis, meta-analysis, more computing power than Apollo, mutually assured destruction, Narrative Science, Network effects, Nicholas Carr, personalized medicine, precariat, precision agriculture, Productivity paradox, race to the bottom, randomized controlled trial, reshoring, RFID, rising living standards, Sam Altman, Second Machine Age, secular stagnation, self-driving car, sharing economy, Silicon Valley, smart cities, smart contracts, software as a service, Stephen Hawking, Steve Jobs, Steven Levy, Stuxnet, supercomputer in your pocket, TaskRabbit, The Future of Employment, The Spirit Level, total factor productivity, transaction costs, Uber and Lyft, uber lyft, Watson beat the top human players on Jeopardy!, WikiLeaks, winner-take-all economy, women in the workforce, working-age population, Y Combinator, Zipcar

In much the same process as for printed objects, an organ is printed layer by layer from a digital 3D model.97 The material used to print an organ would obviously be different from what is used to print a bike, and experimenting can be done with the kinds of materials that will work, such as titanium powder for making bones. 3D printing has great potential to service custom design needs; and, there is nothing more custom than a human body. Positive impacts – Addressing the shortage of donated organs (an average of 21 people die each day waiting for transplants that can’t take place because of the lack of an organ)98 – Prosthetic printing: limb/body part replacements – Hospitals printing for each patient requiring surgery (e.g. splints, casts, implants, screws) – Personalized medicine: 3D printing growing fastest where each customer needs a slightly different version of a body part (e.g. a crown for a tooth) – Printing components of medical equipment that are difficult or expensive to source, such as transducers99 – Printing, for example, dental implants, pacemakers and pens for bone fracture at local hospitals instead of importing them, to reduce the cost of operations – Fundamental changes in drug testing, which can be done on real human objects given the availability of fully printed organs – Printing of food, thus improving food security Negative impacts – Uncontrolled or unregulated production of body parts, medical equipment or food – Growth in waste for disposal, and further burden on the environment – Major ethical debates stemming from the printing of body parts and bodies: Who will control the ability to produce them?

pages: 428 words: 121,717

Warnings by Richard A. Clarke

active measures, Albert Einstein, algorithmic trading, anti-communist, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, Bernie Madoff, cognitive bias, collateralized debt obligation, complexity theory, corporate governance, cuban missile crisis, data acquisition, discovery of penicillin, double helix, Elon Musk, failed state, financial thriller, fixed income, Flash crash, forensic accounting, friendly AI, Intergovernmental Panel on Climate Change (IPCC), Internet of things, James Watt: steam engine, Jeff Bezos, John Maynard Keynes: Economic Possibilities for our Grandchildren, knowledge worker, Maui Hawaii, megacity, Mikhail Gorbachev, money market fund, mouse model, Nate Silver, new economy, Nicholas Carr, nuclear winter, pattern recognition, personalized medicine, phenotype, Ponzi scheme, Ray Kurzweil, Richard Feynman, Richard Feynman: Challenger O-ring, risk tolerance, Ronald Reagan, Sam Altman, Search for Extraterrestrial Intelligence, self-driving car, Silicon Valley, smart grid, statistical model, Stephen Hawking, Stuxnet, technological singularity, The Future of Employment, the scientific method, The Signal and the Noise by Nate Silver, Tunguska event, uranium enrichment, Vernor Vinge, Watson beat the top human players on Jeopardy!, women in the workforce, Y2K

Already, Chinese scientists have used the technique in goat embryos to delete genes that suppress hair and muscle growth, resulting in animals with longer hair and more muscle, ostensibly better at producing both meat and wool. In fact, dozens of Chinese labs have plunged headlong into CRISPR/Cas9 experimentation in fields ranging from animals to agriculture to biomedicine to human transformation.7 Personalized medicine and the elimination of genetic disorders is another potential bright spot in the future of CRISPR/Cas9. Scientists can now snip out defective genes that cause disease, replacing them with healthy ones. Such a procedure would be most easily carried out for conditions caused by a single genetic mutation, such as sickle-cell anemia, Huntington’s disease, or cystic fibrosis. A CRISPR-based therapy would substitute a properly functioning gene for the defective section of DNA in the patient’s cells.

., 153, 161 Options trading, 103–4 Oregon State University, 240–41, 352 Organic Act of 1910, 124–25 Organizing Committee for the International Conference on Recombinant DNA, 337 Orient No. 2 mine explosion, 127 O-rings, and Challenger disaster, 11–13 Orthogonal thinking, 184, 235 Oswald, Lee Harvey, 99 Our Final Invention (Barrat), 202 Outbreak (movie), 219–20 Outlandishness, 174 Oxford University, 212 Pacific Plateau, 80 Pacific Ring of Fire, 94 Pakistan, 261–73 bin Laden raid, 268–69 Cold Start, 267, 270 Mumbai terrorist attacks of 2008, 261–64 nuclear weapons and India, 264–73, 281–82 partition of, 265–66 Pakistani Army, 266–67 Pakistani Navy, 264, 270 Pakistan War College, 269 Palm Beach Country Club, 101 Panasenko, Sharon, 327 Pandemic disease, 217–36 Panetta, Leon, 64, 200 Panoramic Survey Telescope and Rapid Response System (Pan-STARRS), 310–11, 315 Paris Agreement, 247–50 Path Where No Man Thought, A: Nuclear Winter and the End of the Arms Race (Sagan and Turco), 276–77 Paulson, John, 149 Peabody Prize, 226 Peace Corps, 62 Pearl Harbor: Warning and Decision (Wohlstetter), 19, 21 Pearl Harbor attack, 20–21 Penicillin, 229 Penney, Alexander, 186 People’s Liberation Army Navy, 199 Performance Coal Company, 130, 134, 139 “Permabears,” 236 Persian Gulf War. See Gulf War Personal investment, of critics, 187–88 Personalized medicine, 331–32, 342 Personal responsibility, sense of, 185–86 Persuasion campaign, 364–65 Pessimism, 2, 3, 50, 236 “Pet Rock problem,” 321 Piccone, Michele, 380n Pielke, Roger, Jr., 254 Planetary Defense Program Office, 317, 322–23 Plant elevation, and Fukushima nuclear disaster, 89–90 Plaquemines Parish, 39 Plutonium spheres (pits), 83 Polar ice melt, 239, 245–52, 258–60, 360 Political threshold problem, 321–22 Polk Prize, 226 Pollack, James B., 273 Pomona College, 327 Pontchartrain, Lake, 40 Ponzi, Charles, 105 Ponzi scheme, 102–3, 105, 110–11, 113, 115 Population bomb, 192–93 Population Bomb, The (Ehrlich), 192–93 Population growth, 16, 192–93 Predictions, 13–15 Predictor (possible Cassandra), 168, 170, 182–86 President’s Daily Briefing, 24, 35 Prevention strategy, 362–64 Prince, Chuck, 145, 154, 156, 157 Professional investment, of critics, 187–88 Programmable logic controller (PLC), 291–92 Protecting Industrial Control Systems from Electronic Threats (Weiss), 286 Protein & Cell, 340 Providian, 152 Prykarpattyaoblenergo, 284–85 Public Health Service, 354–55 Pulitzer Prize, 50, 226 Putin, Vladimir, 285 Pyrrho of Elis, 185 Questioners, 184–85 Radiation exposure, 88 Ramadi, Iraq, 69 Rampart Investment Management, 101, 102, 105, 106, 109, 110 Raqqa, 68 Reacting, Ronald, 26 Reagan, Ronald, 21, 32, 277–78, 280 Recombinant DNA technology, 336–40 Red Army, 25, 26, 266 Red Team (Zenko), 379n Regulatory capture, 94–95, 96, 98, 115, 177–78 Reid, Ann, 222 Reis Crater, 307 Rendezvous with Rama (Clarke), 313 Response Availability, 170–71 Response strategies, 358–64 hedging, 361–62 mitigation and prevention, 362–64 surveillance, 359–60 Responsibility, diffusion of, 176–77, 215, 235, 321, 348 Revkin, Andrew, 244 Ribozymes, 328 Ring of Fire, 94 RNA, 327–28 Robock, Alan, 261, 273–74, 277–82 Robo-traders, 211 Roche, 225 Rockefeller Institute, 193 Roedersheimer, Keefe, 205 Rolling Stone (magazine), 338 Rometty, Ginni, 209 Roosevelt, Franklin D., 213 Roper, William, 214 Ross, Bill, 136 Ross, Lee, 184 Royal Academy, 345 Royal Air Force, 10 Royal Navy, 9 Royal Netherlands Meteorological Institute, 253 Rubenstein, Ariel, 380n Ruby, Jack, 99 Rumsfeld, Donald, 28–29 Russo, Rene, 219 Rutgers University, 261 Sagan, Carl, 273–77 Sago Mine disaster, 129–30 Salling, John Peter, 122 Samuel, Arthur, 381n San Bruno pipeline explosion of 2010, 293–94 Sandler O’Neill & Partners, 154 Sandworm, 285 Sanriku earthquake of 869, 77–81, 91, 97–98 Sarbanes-Oxley Act (SOX), 157 Sarin, 23, 230 Satisficing, 116, 117, 180–81, 319, 322, 359 Savage, Stefan, 297–98 Scacco, Gus, 149 Scanning for problems, 354–56 Scarface (movie), 99 Scenario modeling, 360, 363–64 Schapiro, Mary, 118–19 Schlesinger, Michael, 240–41 Schneider, Stephen, 241 Science (journal), 242 Science Story (show), 226 Scientific American, 278–79 Scientific method, 248–49 Scientific reticence, 79–80, 186–87, 234, 248–49, 259, 335 “Scope neglect,” 174 Sea-level rise, 238, 244–60, 360 Search for extraterrestrial intelligence (SETI), 304 Seawalls, and Fukushima nuclear disaster, 77, 85, 89–90, 92–93 Securities and Exchange Commission (SEC), 100, 105–12, 114–20, 189–90 Security by obscurity, 270 Seismologist Warns, A (Ishibashi), 91–92 Selection effect, 380n Self-confidence, 184, 240, 365 Self-interest, of critics, 187–88 Sendai, Japan, 80, 81, 82 Sentinel intelligence, 3, 16, 356 “Separation of parts” policy, 270 September 11 attacks, 7–9, 230, 361–62 Seven Pillars of Wisdom: A Triumph (Lawrence), 57 Sextus Empiricus, 185 Shearson Lehman, 162 Shia Muslims, 63 Shoemaker, Gene, 306–7 Shultz, George, 280 Siberian Unified Dispatch Control Center (SUDCC), 290 Siegel, Jeremy, 157–58 Siegfried Line, 10 Sieur de Bienville, Jean-Baptiste Le Moyne, 41 Signal and the Noise, The (Silver), 15 Signal from noise, separating, 356–58 Silver, Nate, 13, 15 Silver mining, 128–29 Simon, Herbert, 180–81, 322 Simons, Daniel, 175 Singularity, the, 209 60 Minutes (TV show), 119, 162, 244 Skepticism, 151–53, 168, 185, 240, 248–49 Skynet, 205 Smith & Wesson, 99, 109 Snowden, Edward, 211 Solid rocket boosters, and Challenger disaster, 11–13 Somalia, 65 Soothsayers, 1–2 “Sophistication effect,” 187 South Africa, 42–43 Soviet Union, 25–26, 266, 267–68, 271, 273–74, 277–78 Spaceguard goal, 312–17, 319 Space Shuttle Challenger disaster, 11–13 SpaceX, 202 Spanish flu pandemic of 1918, 195, 198, 217, 221–24 Spielberg, Steven, 101 Split-strike conversion, 103–5 SSH (Sayano-Shushenskaya Hydro), 289–2917 Stalin, Joseph, 174, 213 Standard project hurricane (SPH), 52–53 “Standing start,” 266 Stanford University, 89, 184, 192, 226, 337, 338 Steam engine, 174–75 Stock trading.

pages: 168 words: 47,972

Vagabonding: An Uncommon Guide to the Art of Long-Term World Travel by Rolf Potts

dematerialisation, Exxon Valdez, financial independence, follow your passion, George Santayana, Lao Tzu, large denomination, personalized medicine, Ralph Waldo Emerson, the map is not the territory

The best way to deal with “traveler’s D” is to simply keep well hydrated and eat bland foods (rice, bread, yogurt) for a few days, until it improves. If any kind of sickness persists for more than a few days, it can’t hurt to relate your symptoms to a local doctor or pharmacist. Most will be familiar with local maladies and happy to set you up with inexpensive prescriptions for whatever ails you. (Of course, a small first-aid kit full of bandages, antiseptic, painkillers, and personal medicines should already be a part of your travel gear.) If your sickness threatens to get serious, make your way to a major city and check into a modern hospital. Crime and scams are common wherever travelers are found, though they are generally no more dangerous than the average annoyances in your hometown. All it takes to avoid such theft is a little awareness. Many local scams are detailed in guidebooks, for example, so be sure to study up whenever you arrive in a new region.

pages: 447 words: 141,811

Sapiens: A Brief History of Humankind by Yuval Noah Harari

Admiral Zheng, agricultural Revolution, Albert Einstein, Alfred Russel Wallace, Atahualpa, British Empire, cognitive dissonance, correlation does not imply causation, credit crunch, David Graeber, Edmond Halley, European colonialism, Francisco Pizarro, glass ceiling, global village, greed is good, income per capita, invention of gunpowder, Isaac Newton, joint-stock company, joint-stock limited liability company, Kickstarter, liberal capitalism, life extension, Mahatma Gandhi, megacity, Mikhail Gorbachev, out of africa, personalized medicine, Ponzi scheme, Silicon Valley, South China Sea, stem cell, Steven Pinker, The Wealth of Nations by Adam Smith, trade route, transatlantic slave trade, urban planning, zero-sum game

Lawyers need to rethink issues of privacy and identity; governments are faced with rethinking matters of health care and equality; sports associations and educational institutions need to redefine fair play and achievement; pension funds and labour markets should readjust to a world in which sixty might be the new thirty. They must all deal with the conundrums of bioengineering, cyborgs and inorganic life. Mapping the first human genome required fifteen years and $3 billion. Today you can map a person’s DNA within a few weeks and at the cost of a few hundred dollars.20 The era of personalized medicine – medicine that matches treatment to DNA – has begun. The family doctor could soon tell you with greater certainty that you face high risks of liver cancer, whereas you needn’t worry too much about heart attacks. She could determine that a popular medication that helps 92 per cent of people is useless to you, and you should instead take another pill, fatal to many people but just right for you.

., ‘Human Genome Sequencing Using Unchained Base Reads on Self-Assembling DNA Nanoarrays’, Science 327:5961 (2010), 78–81; ‘Complete Genomics’ website:; Rob Waters, ‘Complete Genomics Gets Gene Sequencing under $5000 (Update 1)’, Bloomberg, 5 November 2009, accessed 10 December 2010;; Fergus Walsh, ‘Era of Personalized Medicine Awaits’, BBC News, last updated 8 April 2009, accessed 22 March 2012,; Leena Rao, ‘PayPal Co-Founder and Founders Fund Partner Joins DNA Sequencing Firm Halcyon Molecular’, TechCrunch, 24 September 2009, accessed 10 December 2010,​fund-partner-joins-dna-sequencing-firm-halcyon-molecular/.

pages: 588 words: 131,025

The Patient Will See You Now: The Future of Medicine Is in Your Hands by Eric Topol

23andMe, 3D printing, Affordable Care Act / Obamacare, Anne Wojcicki, Atul Gawande, augmented reality, bioinformatics, call centre, Clayton Christensen, clean water, cloud computing, commoditize, computer vision, conceptual framework, connected car, correlation does not imply causation, creative destruction, crowdsourcing, dark matter, data acquisition, disintermediation, disruptive innovation, don't be evil, Edward Snowden, Elon Musk,, Erik Brynjolfsson, Firefox, global village, Google Glasses, Google X / Alphabet X, Ignaz Semmelweis: hand washing, information asymmetry, interchangeable parts, Internet of things, Isaac Newton, job automation, Julian Assange, Kevin Kelly, license plate recognition, lifelogging, Lyft, Mark Zuckerberg, Marshall McLuhan, meta analysis, meta-analysis, microbiome, Nate Silver, natural language processing, Network effects, Nicholas Carr, obamacare, pattern recognition, personalized medicine, phenotype, placebo effect, RAND corporation, randomized controlled trial, Second Machine Age, self-driving car, Silicon Valley, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, Snapchat, social graph, speech recognition, stealth mode startup, Steve Jobs, the scientific method, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, Turing test, Uber for X, uber lyft, Watson beat the top human players on Jeopardy!, WikiLeaks, X Prize

There is indeed now a “race against machines” that is pervasive, and it would be naïve to think that medicine is immune from the impact.6 The medical thriller novelist and physician Robin Cook wrote Cell, his thirty-third book, about iDoc—“a smartphone functioning as a twenty-first-century primary-care physician,”7 an avatar doctor equipped with algorithms to “create a true ersatz physician on duty twenty-four-seven for a particular individual, truly personalized medicine.”7 Each individual signing up selects an avatar doctor, choosing their gender, attitude, whether they are paternal or maternal in tone, and how they want to be notified. The system involves a remote command center staffed with hundreds of physicians who work four-hour shifts to keep them mentally crisp, and a supercomputer that, in real time, continuously monitors extensive physiological data on all iDoc users.

Proctor Harvey, one of the most well-regarded bedside cardiologists. Here is what Dr. Knowlan, age eighty-six, included in his address to the incoming students: But what can you, the class of 2017, expect? In a recent thought-provoking book, The Creative Destruction of Medicine . . . [Topol] anticipate[d] future changes in the health care delivery system. He commented on changes such as use of smartphones for complex diagnostic challenges and personalized medicine with use of genetic information. He even suggested that the stethoscope, so revered here at Georgetown, will be replaced by a handheld ultrasound device. He admitted to not using his own stethoscope for over 2 years, which suggests to me he never learned to use it properly and appreciate its value. Despite all these future advances, he probably hardly scratches the surface.114 I’ve never met Dr.

pages: 548 words: 147,919

How Everything Became War and the Military Became Everything: Tales From the Pentagon by Rosa Brooks

airport security, Albert Einstein, Berlin Wall, big-box store, clean water, cognitive dissonance, continuation of politics by other means, different worldview, disruptive innovation, drone strike, Edward Snowden, facts on the ground, failed state, illegal immigration, Internet Archive, John Markoff, Mark Zuckerberg, moral panic, pattern recognition, Peace of Westphalia, personalized medicine, RAND corporation, Silicon Valley, South China Sea, Turing test, unemployed young men, Valery Gerasimov, Wall-E, War on Poverty, WikiLeaks

As former Air Force deputy judge advocate general Charles Dunlap notes in a recent article on what he calls “the hyper-personalization of war,” these capabilities are rapidly being militarized: “In the not-too distant future, the U.S. military—and likely other militaries—will be able to launch swarms of drones equipped with facial recognition software to roam battlefields looking for very specific members of an enemy’s force.”2 In the bioscience world, breakthroughs in our understanding of genetics are opening up the possibility of personalized medicine: cancer treatments tailored to a specific person’s genetic code, for instance. But the same discoveries that may soon allow doctors to tailor life-saving treatments to the needs of specific individuals may also allow the development of DNA-linked bioweapons: a virus designed to disable or kill only a specific individual. In some ways, the individualization of warfare may be a good thing.

., 72, 147, 389 Padilla, Jose, 33 Pakistan, 5–6, 12, 60, 226, 349 U.S. drone strikes in, 106–7, 113 U.S. military intervention in, 251 Pakistani Taliban, 278, 279 Paleolithic period, 264 Panetta, Leon, 119–20 Papua New Guinea, 9, 21, 175, 350 Paris Declaration (1856), 49 pattern analysis, 303, 304, 414 peace: blurred line between war and, 8–9, 13, 21–24, 35–36, 141, 143, 148, 213, 225, 267, 273, 276, 305, 333, 334, 338, 341–42, 343, 345, 350, 351, 366 as exception in history, 348–49, 352 “space between” war and, 352–54 Pearl Harbor, Japanese attacks on, 11 Pentagon: as physical environment, 39–40 see also Defense Department, U.S.; September 11, 2001, terrorist attacks People’s Liberation Army, Chinese, 10 Perino, Dana, 61 Perry, John, 299 Persia, ancient, 255 personalized medicine, 132 Peru, 173–74 Petraeus, David, 5, 66, 94 Phase Zero, 7, 82, 143–44, 148–49 Philippines, 12, 349 Phillips, Richard, 40 Pilica, Bosnia, 206 Pinochet, Augusto, 271–72, 273 pirates, piracy: Barbary coast and, 47–49 Defense Department policy on, 42–45 international law and, 42–43, 49 Maersk Alabama seized by, 40–41, 45 state-sponsored, 47–49 “PlayStation mentality,” 109–10 plebes, 182 policing: civil liberties and, 354 war on terror and, 298–99 policymakers, misunderstanding and mistrust between military and, 305–6, 362 “Politics of the Geneva Conventions, The” (conference), 199 polonium-210, 273 population, global, 262 post-traumatic stress disorder (PTSD), of drone pilots, 110 Power, Matthew, 115 Power, Samantha, 67, 234 power grid, cyberattacks on, 11 precision weapons, 129 Predator drones, 105, 106, 112, 135, 199 president, U.S.: constitutional powers of, 294 inherent powers of, 200, 202 preventive detention, 63–65, 66–67 rule of law and, 63–64, 65 Prins, Brandon, 46 prisoners of war, 63 privacy, war on terror and, 303–4 private contractors: laws of war and, 123 U.S. reliance on, 123–24, 258, 326 war on terror and, 297–98, 300 Problem from Hell, A (Power), 234 “proportionality,” in law of armed conflict, 196–97 proportionality, principle of, 288, 405 Pro Publica, 119 proxy conflicts, 339, 349 Pruitt, Gary, 304 public education, 322 Public Interest Declassification Board (PIDB), 126 Purchas, Samuel, 256–57 Putin, Vladimir, 273, 280 Qiao Liang, 10, 11, 12, 22, 341 RAF, see regionally aligned forces Railway Wood, Battle of (1916), 114 Ramallah, West Bank, 242 Rasul v.

pages: 523 words: 61,179

Human + Machine: Reimagining Work in the Age of AI by Paul R. Daugherty, H. James Wilson

3D printing, AI winter, algorithmic trading, Amazon Mechanical Turk, augmented reality, autonomous vehicles, blockchain, business process, call centre, carbon footprint, cloud computing, computer vision, correlation does not imply causation, crowdsourcing, digital twin, disintermediation, Douglas Hofstadter,, Erik Brynjolfsson, friendly AI, future of work, industrial robot, Internet of things, inventory management, iterative process, Jeff Bezos, job automation, job satisfaction, knowledge worker, Lyft, natural language processing, personalized medicine, precision agriculture, Ray Kurzweil, recommendation engine, RFID, ride hailing / ride sharing, risk tolerance, Rodney Brooks, Second Machine Age, self-driving car, sensor fusion, sentiment analysis, Shoshana Zuboff, Silicon Valley, software as a service, speech recognition, telepresence, telepresence robot, text mining, the scientific method, uber lyft

From chapter 2, we saw how AI can turn routine back-office interactions into more personalized services that improve customer experience. AI is also operating in the R&D departments responsible for these changes in mass customization. (For a brief discussion of the balance between personalization and privacy, see side bar “Responsible AI: Ethics as a Precursor to Discovery.”) Take, for example, the health-care industry. AI is now enabling the era of “personalized medicine” based on genetic testing. In the past, it was virtually impossible to analyze and manage all the combinations of possible treatments for each patient by hand. Today, intelligent systems are taking over that job. Decades from now (or sooner), it will seem absurd that doctors prescribed the same treatment to a wide swath of their patients. Everyone’s treatments will be personalized. Along these lines, GNS, the analytics firm, has been crunching huge amounts of data to match specific drugs and nondrug interventions to individual patients.

pages: 552 words: 168,518

MacroWikinomics: Rebooting Business and the World by Don Tapscott, Anthony D. Williams

accounting loophole / creative accounting, airport security, Andrew Keen, augmented reality, Ayatollah Khomeini, barriers to entry, Ben Horowitz, bioinformatics, Bretton Woods, business climate, business process, buy and hold, car-free, carbon footprint, Charles Lindbergh, citizen journalism, Clayton Christensen, clean water, Climategate, Climatic Research Unit, cloud computing, collaborative editing, collapse of Lehman Brothers, collateralized debt obligation, colonial rule, commoditize, corporate governance, corporate social responsibility, creative destruction, crowdsourcing, death of newspapers, demographic transition, disruptive innovation, distributed generation, don't be evil,, energy security, energy transition, Exxon Valdez, failed state, fault tolerance, financial innovation, Galaxy Zoo, game design, global village, Google Earth, Hans Rosling, hive mind, Home mortgage interest deduction, information asymmetry, interchangeable parts, Internet of things, invention of movable type, Isaac Newton, James Watt: steam engine, Jaron Lanier, jimmy wales, Joseph Schumpeter, Julian Assange, Kevin Kelly, Kickstarter, knowledge economy, knowledge worker, Marc Andreessen, Marshall McLuhan, mass immigration, medical bankruptcy, megacity, mortgage tax deduction, Netflix Prize, new economy, Nicholas Carr, oil shock, old-boy network, online collectivism, open borders, open economy, pattern recognition, peer-to-peer lending, personalized medicine, Ray Kurzweil, RFID, ride hailing / ride sharing, Ronald Reagan, Rubik’s Cube, scientific mainstream, shareholder value, Silicon Valley, Skype, smart grid, smart meter, social graph, social web, software patent, Steve Jobs, text mining, the scientific method, The Wisdom of Crowds, transaction costs, transfer pricing, University of East Anglia, urban sprawl, value at risk, WikiLeaks, X Prize, young professional, Zipcar

You can search the site by pollutant, industry, and hazard level. Or simply type in a zip code and pull up a list of polluters in their neighborhood. Data sharing also drives economic opportunity and, on occasions, has been known to spark new growth industries. When the National Institutes of Health released data from the Human Genome Project it spurred massive innovation around a new era of personalized medicine. President Reagan’s directive to provide free and open access to the Defense Department’s GPS signals gave rise to a plethora of commercial uses ranging from mapmaking, land surveying, scientific analysis, and surveillance to hobbies such as geo-caching and waymarking. The Obama administration hopes—an open hub for federal data—will amplify and accelerate this tradition of innovation.

Just over 59 percent of obese Americans exercised at least one day per week, compared to 70 percent of overweight people, and 74 percent of healthy-weight people. Obese people are less likely than people in every other weight category (overweight, normal weight, underweight) to have eaten five servings of fruits and vegetables on at least three days of the past seven. Obese Americans also are less likely to say they ate healthy “all day yesterday.” 19. Thomas Goetz, The Decision Tree: Taking Control of Your Health in the New Era of Personalized Medicine (Rodale Books, 2010), p. 238. 20. M. Kwan and N. Haque, “Sermo and PatientsLikeMe: A Revolution in Collaborative Healthcare,” Enterprise 2.0 Lighthouse Case Study, nGenera Corporation (2008). 21. Ibid. 22. Ibid. 23. Ibid. 24. “Social Networking May Benefit Patients with Common Skin Disease,” Center for Connected Health (January 21, 2009). 25. Ibid. 26. “Testimonials,” WeAre.Us (accessed May 15, 2010). 27.

The Psychopath Inside: A Neuroscientist's Personal Journey Into the Dark Side of the Brain by James Fallon

Bernie Madoff, epigenetics, Everything should be made as simple as possible, meta analysis, meta-analysis, personalized medicine, phenotype, Rubik’s Cube, selective serotonin reuptake inhibitor (SSRI), stem cell, theory of mind

Successful examples exist for complex diseases never previously understood through “omics” medicine, including genomics (genes and related nucleic acids in the nucleus), transcriptomics (various mRNA levels in tissues), proteomics (different levels of proteins and their interactions in relevant tissues), and metabolomics (blood and urine levels of several thousand hormones, metabolites, sugar, etc., and their dynamic interactions over time). Personal genomics and personalized medicine emerge as new feasible applications and not only as future possibilities, thanks to the developments in analyzing genomes and complex traits and visualizing these results into a unified framework. In any case, it would be a while before someone took the time to give my genes a good looking-over. In the years between sending my blood sample and receiving my genetic results, I did consider now and again what the genetics results might tell me about what my brain scans meant.

pages: 239 words: 70,206

Data-Ism: The Revolution Transforming Decision Making, Consumer Behavior, and Almost Everything Else by Steve Lohr

"Robert Solow", 23andMe, Affordable Care Act / Obamacare, Albert Einstein, big data - Walmart - Pop Tarts, bioinformatics, business cycle, business intelligence, call centre, cloud computing, computer age, conceptual framework, Credit Default Swap, crowdsourcing, Daniel Kahneman / Amos Tversky, Danny Hillis, data is the new oil, David Brooks, East Village, Edward Snowden, Emanuel Derman, Erik Brynjolfsson, everywhere but in the productivity statistics, Frederick Winslow Taylor, Google Glasses, impulse control, income inequality, indoor plumbing, industrial robot, informal economy, Internet of things, invention of writing, Johannes Kepler, John Markoff, John von Neumann, lifelogging, Mark Zuckerberg, market bubble, meta analysis, meta-analysis, money market fund, natural language processing, obamacare, pattern recognition, payday loans, personalized medicine, precision agriculture, pre–internet, Productivity paradox, RAND corporation, rising living standards, Robert Gordon, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley startup, six sigma, skunkworks, speech recognition, statistical model, Steve Jobs, Steven Levy, The Design of Experiments, the scientific method, Thomas Kuhn: the structure of scientific revolutions, unbanked and underbanked, underbanked, Von Neumann architecture, Watson beat the top human players on Jeopardy!

It is the industrial machinery equivalent to Google Now, a predictive search service for mobile devices, including Google glasses, that presents driving directions, recommendations for nearby restaurants, sports scores for teams you follow, based on your location, your interests, and what you’ve done in the past—the context of your life. GE wants to push contextual computing in the machine world to another dimension. Most of the current focus has been on gathering data from machines to learn about them—to reduce lost operating time by applying data-driven preventive maintenance. With machines, as with vineyards, the comparison typically offered is to preventive and personalized medicine. You can prevent machine failures with tailored treatment, informed by data. But the next step is technology to enable the machines themselves to learn about their environment and adapt to it. Take the case of a jet engine on an airliner whose route takes it to different climates, like flying from Arizona to Canada. The temperatures, humidity, and air density, for example, are usually very different in those locations.

pages: 254 words: 69,276

The Metric Society: On the Quantification of the Social by Steffen Mau

Airbnb, cognitive bias, collaborative consumption, connected car, crowdsourcing, double entry bookkeeping, future of work, income inequality, informal economy, invisible hand, knowledge economy, labour market flexibility, lifelogging, Mark Zuckerberg, mittelstand, moral hazard, personalized medicine, positional goods, principal–agent problem, profit motive, QR code, reserve currency, school choice, selection bias, sharing economy, smart cities, the scientific method, Uber for X, web of trust, Wolfgang Streeck

The resulting information may also go to doctors or other professional consultants for purposes of remote health monitoring, which is currently used in the main for chronic diseases such as diabetes or heart failure, but can potentially be extended to include all aspects of sickness or health. This approach to health monitoring yields a hitherto unimaginable wealth of vital signs which are clearly invaluable for science, prophylaxis, early detection and treatment, including new possibilities of personalized medicine. Nowadays, there are even implants on the market that can remain permanently in situ, transmitting data signals on an ongoing basis. These built-in measuring stations create new interfaces between the inner and outer body. Currently, their main purpose is to improve the efficiency of disease monitoring, but increasing numbers of people are now also using them for everyday health tracking.

pages: 233 words: 67,596

Competing on Analytics: The New Science of Winning by Thomas H. Davenport, Jeanne G. Harris

always be closing, big data - Walmart - Pop Tarts, business intelligence, business process, call centre, commoditize, data acquisition, digital map,, global supply chain, high net worth, if you build it, they will come, intangible asset, inventory management, iterative process, Jeff Bezos, job satisfaction, knapsack problem, late fees, linear programming, Moneyball by Michael Lewis explains big data, Netflix Prize, new economy, performance metric, personalized medicine, quantitative hedge fund, quantitative trading / quantitative finance, recommendation engine, RFID, search inside the book, shareholder value, six sigma, statistical model, supply-chain management, text mining, the scientific method, traveling salesman, yield management

But the multiline company had only recently begun to expand its analytical orientation beyond the traditionally quantitative actuarial function, and thus far there was little cooperation across the life and property and casualty business units. We also interviewed executives from three different pharmaceutical firms, and we categorized two of the three into stage 3 at present. It was clear to all the managers that analytics were the key to the future of the industry. The combination of clinical, genomic, and proteomic data will lead to an analytical transformation and an environment of personalized medicine. Yet both the science and the application of informatics in these domains are as yet incomplete.13 Each of our interviewees admitted that their company, and the rest of the industry, has a long way to go before mastering their analytical future. One of the companies, Vertex Pharmaceuticals, has made significant progress toward analytical competition—not by striving toward the analytical holy grail described earlier, but by making more analytical decisions in virtually every phase of drug development and marketing.

pages: 238 words: 68,914

Where Does It Hurt?: An Entrepreneur's Guide to Fixing Health Care by Jonathan Bush, Stephen Baker

Affordable Care Act / Obamacare, Atul Gawande, barriers to entry, Clayton Christensen, commoditize, informal economy, inventory management, job automation, knowledge economy, lifelogging, obamacare, personalized medicine, ride hailing / ride sharing, Ronald Reagan, Silicon Valley, Steve Jobs, web application, women in the workforce, working poor

If a drug works for certain people, or under certain conditions, researchers combing through the data should be able to identify niche markets for it. Think of the possibilities. For every medicine that makes it from the laboratory to the pharmacy shelf, 999 fail, some of them in the second, third, or fourth stage of testing—in other words, after being deemed safe. Some of those drugs too could be placed on the market, where consumers participate in a kind of informal laboratory. This could be one of the pathways leading toward personalized medicine. A lot of those researchers will be amateurs, compiling data on wikis, writing their conclusions on blogs, or debating them on social networks. In this way, they will not only carry out the experiments but also handle lots of the research and analysis. (They won’t replace all of the professionals, but will force them to adapt to a widening market.) Engaged health care citizens will also be researching hospitals and urgent care centers.

Woolly: The True Story of the Quest to Revive History's Most Iconic Extinct Creature by Ben Mezrich

butterfly effect, Danny Hillis, double helix, Electric Kool-Aid Acid Test, Jeff Bezos, Kickstarter, life extension, Louis Pasteur, mass immigration, microbiome, personalized medicine, Peter Thiel, Silicon Valley, Silicon Valley ideology, stem cell, Stewart Brand

Church had actually met Brand through Phelan, with whom he had a more basic shared area of interest. Ten years after her 1995 start-up Direct Medical Knowledge had become the backbone of what was now known as WebMD, Phelan had founded a company called DNA Direct, offering genetic testing to customers via the Internet. By screening for preconditions for more than a half dozen diseases, DNA Direct had been aimed at the same sort of personalized medicine that Church foresaw for his Personal Genome Project. Phelan had sought Church out for the advisory board of her company. He had happily accepted and asked her to be on the board of his Personal Genome Project. But they didn’t reconnect for another few years, a short time before the trip to Petaluma, because of an odd little email Brand had sent Church, which had landed in his inbox just a few days after his phone call with Nicholas Wade.

pages: 218 words: 70,323

Critical: Science and Stories From the Brink of Human Life by Matt Morgan

agricultural Revolution, Atul Gawande, biofilm, Black Swan, Checklist Manifesto, cognitive dissonance, crew resource management, Daniel Kahneman / Amos Tversky, David Strachan, discovery of penicillin,, hygiene hypothesis, job satisfaction, John Snow's cholera map, meta analysis, meta-analysis, personalized medicine, publication bias, randomized controlled trial, Silicon Valley, stem cell, Steve Jobs

‘Functional MRI studies, scanning areas of the brain involved in cognition, now show that subconscious processes predetermine our choices long before we are even aware of “us”making a decision.’ Hallett, M. Volitional control of movement: the physiology of free will. Clin Neurophysiol 118, 1179–1192 (2007). ‘With the development of machines such as IBM’s supercomputer Watson, even this human integration based on knowledge and experience can be replicated.’ Goetz, L. H. & Schork, N. J. Personalized medicine: motivation, challenges, and progress. Fertil. Steril. 109, 952–963 (2018). ‘. . . the first weekend of March saw sixteen weather-related deaths as the heaviest snowfall in more than thirty-five years was dumped on an ill-prepared UK.’ ‘. . . one of the busiest periods for critical care services ever described, with my ICU swelling to over 170 per cent of its funded capacity.’

pages: 265 words: 74,000

The Numerati by Stephen Baker

Berlin Wall, Black Swan, business process, call centre, correlation does not imply causation, Drosophila, full employment, illegal immigration, index card, Isaac Newton, job automation, job satisfaction, McMansion, Myron Scholes, natural language processing, PageRank, personalized medicine, recommendation engine, RFID, Silicon Valley, Skype, statistical model, Watson beat the top human players on Jeopardy!

In many ways, these promises of preventive care echo others coming from genomics laboratories, another growing empire for the Numerati. In universities and pharmaceutical labs around the world, computer scientists and computational biologists are designing algorithms to sift through billions of gene sequences, looking for links between certain genetic markers and diseases. The goal is to help us sidestep the diseases we're most likely to contract and to provide each one of us with a cabinet of personalized medicines. Each one should include just the right dosage and the ideal mix of molecules for our bodies. Between these two branches of research, genetic and behavioral, we're being parsed, inside and out. Even the language of the two fields is similar. In a nod to geneticists, Dishman and his team are working to catalog what they call our "behavioral markers." The math is also about the same. Whether they're scrutinizing our strands of DNA or our nightly trips to the bathroom, statisticians are searching for norms, correlations, and anomalies.

pages: 269 words: 70,543

Tech Titans of China: How China's Tech Sector Is Challenging the World by Innovating Faster, Working Harder, and Going Global by Rebecca Fannin

Airbnb, augmented reality, autonomous vehicles, blockchain, call centre, cashless society, Chuck Templeton: OpenTable:, cloud computing, computer vision, connected car, corporate governance, cryptocurrency, data is the new oil, Deng Xiaoping, digital map, disruptive innovation, Donald Trump, El Camino Real, Elon Musk, family office, fear of failure, glass ceiling, global supply chain, income inequality, industrial robot, Internet of things, invention of movable type, Jeff Bezos, Kickstarter, knowledge worker, Lyft, Mark Zuckerberg, megacity, Menlo Park, money market fund, Network effects, new economy, peer-to-peer lending, personalized medicine, Peter Thiel, QR code, RFID, ride hailing / ride sharing, Sand Hill Road, self-driving car, sharing economy, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart transportation, Snapchat, social graph, software as a service, South China Sea, sovereign wealth fund, speech recognition, stealth mode startup, Steve Jobs, supply-chain management, Tim Cook: Apple, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, urban planning, winner-take-all economy, Y Combinator, young professional

Baidu has its DuerOS line of smart household goods and Apollo, an open platform for self-driving technology solutions, and detoured on the AI journey several years before Google in 2015. Alipay uses facial recognition for payments, and Alibaba has an AI cloud platform called City Brain that crunches data and determines patterns for better urban planning. Tencent is integrating rich media formats such as face-swapping effects and video chat filters into its social media and is investing in personalized medicine, digitized patient health-care records, and remote health-care monitoring. In their quest to win the AI challenge, the three titans are hunting for new AI technologies and applications by investing in AI startups globally. Since 2014, this trio of Chinese tech giants has made 39 equity deals in startups that are building AI chips and software.2 Despite scrutiny over Chinese investments in US technology startups, this cross-border pipeline is active in artificial intelligence.

pages: 281 words: 79,958

Denialism: How Irrational Thinking Hinders Scientific Progress, Harms the Planet, and Threatens Our Lives by Michael Specter

23andMe, agricultural Revolution, Anne Wojcicki, Any sufficiently advanced technology is indistinguishable from magic, Asilomar, carbon footprint, Cass Sunstein, clean water, Drosophila, food miles, invention of gunpowder, out of africa, personalized medicine, placebo effect, profit motive, randomized controlled trial, Richard Feynman, Richard Feynman: Challenger O-ring, Ronald Reagan, Simon Singh, Skype, stem cell, Ted Kaczynski, the scientific method, Thomas Malthus, twin studies, Upton Sinclair, X Prize

You can’t look at the data and make those assumptions,” Burchard said. “But if reality upsets people, they will simply look in another direction. People deny what makes them uncomfortable, and many—even in my business—say we shouldn’t use the word ‘race’ at all.” It has never been easy to invoke the subject of race in America. Discrimination has long been as obvious in medicine as in other areas of society. In the era of personalized medicine, where relevant new information seems to appear daily, the issue has become more volatile than ever. At many meetings where race and genetics are discussed, researchers spend as much time debating semantics as they do discussing scientific results. (In 2008, one participant at a National Institutes of Health conference on genomics and race argued that not only is the term “race” unacceptable, but so is the term “Caucasian,” because it implies racial rather than geographic ancestry.)

pages: 339 words: 94,769

Possible Minds: Twenty-Five Ways of Looking at AI by John Brockman

AI winter, airport security, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, artificial general intelligence, Asilomar, autonomous vehicles, basic income, Benoit Mandelbrot, Bill Joy: nanobots, Buckminster Fuller, cellular automata, Claude Shannon: information theory, Daniel Kahneman / Amos Tversky, Danny Hillis, David Graeber, easy for humans, difficult for computers, Elon Musk, Eratosthenes, Ernest Rutherford, finite state, friendly AI, future of work, Geoffrey West, Santa Fe Institute, gig economy, income inequality, industrial robot, information retrieval, invention of writing, James Watt: steam engine, Johannes Kepler, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, Kickstarter, Laplace demon, Loebner Prize, market fundamentalism, Marshall McLuhan, Menlo Park, Norbert Wiener, optical character recognition, pattern recognition, personalized medicine, Picturephone, profit maximization, profit motive, RAND corporation, random walk, Ray Kurzweil, Richard Feynman, Rodney Brooks, self-driving car, sexual politics, Silicon Valley, Skype, social graph, speech recognition, statistical model, Stephen Hawking, Steven Pinker, Stewart Brand, strong AI, superintelligent machines, supervolcano, technological singularity, technoutopianism, telemarketer, telerobotics, the scientific method, theory of mind, Turing machine, Turing test, universal basic income, Upton Sinclair, Von Neumann architecture, Whole Earth Catalog, Y2K, zero-sum game

The same method has recently been generalized: Starting from scratch, within just twenty-four hours, an equivalent AlphaZero chess program was able to beat today’s top “conventional” chess programs, which in turn have beaten the best humans. Progress has not been restricted to games. Computers are significantly better at image and voice recognition and speech synthesis than they used to be. They can detect tumors in radiographs earlier than most humans. Medical diagnostics and personalized medicine will improve substantially. Transportation by self-driving cars will keep us all safer, on average. My grandson may never have to acquire a driver’s license, because driving a car will be like riding a horse today—a hobby for the few. Dangerous activities, such as mining, and tedious repetitive work will be done by computers. Governments will offer better targeted, more personalized and efficient public services.

pages: 332 words: 90,186

Dances With Wolves by Michael Blake

personalized medicine

He was thrilled with the gift and sought out an older warrior named Stone Calf, who taught him the finer points of its use. In the space of a week the two became fast friends, and Dances With Wolves showed up regularly at Stone Calf’s lodge. He learned how to care for and make quick repairs on weapons. He learned the words to several important songs and how to sing them. He watched Stone Calf make fire from a little wooden kit and saw him make his own personal medicine. He was a willing pupil for these lessons and quick to learn, so quick that Stone Calf gave him the nickname Fast. He scouted a few hours each day, as did most of the other men. They went out in groups of three or four, and in a short time Dances With Wolves had a rudimentary knowledge of necessary things, like how to read the age of tracks and determine weather patterns. The buffalo came and went in their mysterious way.

pages: 372 words: 92,477

The Fourth Revolution: The Global Race to Reinvent the State by John Micklethwait, Adrian Wooldridge

Admiral Zheng, affirmative action, Affordable Care Act / Obamacare, Asian financial crisis, assortative mating, banking crisis, barriers to entry, battle of ideas, Berlin Wall, Bernie Madoff, Boris Johnson, Bretton Woods, British Empire, cashless society, central bank independence, Chelsea Manning, circulation of elites, Clayton Christensen, Corn Laws, corporate governance, credit crunch, crony capitalism, Deng Xiaoping, Detroit bankruptcy, disintermediation, Edward Snowden, Etonian, failed state, Francis Fukuyama: the end of history, full employment, Gunnar Myrdal, income inequality, Khan Academy, Kickstarter, knowledge economy, Kodak vs Instagram, labor-force participation, laissez-faire capitalism, land reform, liberal capitalism, Martin Wolf, means of production, minimum wage unemployment, mittelstand, mobile money, Mont Pelerin Society, Nelson Mandela, night-watchman state, Norman Macrae, obamacare, oil shale / tar sands, old age dependency ratio, open economy, Parag Khanna, Peace of Westphalia, pension reform, pensions crisis, personalized medicine, Peter Thiel, plutocrats, Plutocrats, popular capitalism, profit maximization, rent control, rent-seeking, ride hailing / ride sharing, road to serfdom, Ronald Coase, Ronald Reagan, school choice, school vouchers, Silicon Valley, Skype, special economic zone, too big to fail, total factor productivity, War on Poverty, Washington Consensus, Winter of Discontent, working-age population, zero-sum game

Just as drones have helped the armed forces, machines will allow doctors to be more precise, making incisions more neatly than human hands can—and even to do it at long distance: As long ago as 2001 doctors in New York used robotic instruments under remote control across the Web to remove the gall bladder of a (rather brave) woman in Strasbourg. Or take those banks of computers and jumbles of health records. Just as computers are now allowing companies to make connections and target services at consumers ever more accurately, so “Big Data” could also allow health departments to personalize medicine. The biggest change maker of all, however, is the Internet. Naming and shaming is gradually coming to health care in the same way it has to education, with doctors’ organizations and public hospitals playing the same role as teachers’ unions, denouncing any attempt to assess their performance as simplistic. To the rest of us it does not seem unreasonable to know how much money a hospital spends, how quickly it deals with its cases, and what the chances of somebody coming out of it alive are.

pages: 347 words: 90,234

You Can't Make This Stuff Up: The Complete Guide to Writing Creative Nonfiction--From Memoir to Literary Journalism and Everything in Between by Lee Gutkind

airport security, Albert Einstein, Atul Gawande, Columbine, Electric Kool-Aid Acid Test, In Cold Blood by Truman Capote, Joan Didion, Mark Zuckerberg, New Journalism, non-fiction novel, Norman Mailer, out of africa, personalized medicine, publish or perish, Ronald Reagan, Stephen Hawking, working poor, Year of Magical Thinking

—Lauren Slater, author of Welcome to My Country, Prozac Diary, and Opening Skinner’s Box ALSO BY LEE GUTKIND Almost Human: Making Robots Think Anatomy of Baseball The Art of Creative Nonfiction At The End of Life: True Stories About How We Die Becoming a Doctor: From Student to Specialist, Doctor-Writers Share Their Experiences The Best Creative Nonfiction, Volumes 1, 2, and 3 The Best Seat in Baseball, But You Have to Stand Bike Fever Creative Nonfiction: How to Live It and Write It The Essayist at Work Forever Fat: Essays by the Godfather God’s Helicopter Healing An Immense New Power to Heal: The Promise of Personalized Medicine Keep It Real: Everything You Need to Know About Researching and Writing Creative Nonfiction Many Sleepless Nights One Children’s Place On Nature: Great Writers on the Great Outdoors Our Roots are Deep with Passion The People of Penn’s Woods West Silence Kills Stuck in Time: The Tragedy of Childhood Mental Illness Surviving Crisis Truckin’ with Sam The Veterinarian’s Touch A View from the Divide This book is dedicated to Gay Talese in appreciation of his talent, his integrity, his unwavering dedication to his work, and most of all his friendship.

pages: 336 words: 93,672

The Future of the Brain: Essays by the World's Leading Neuroscientists by Gary Marcus, Jeremy Freeman

23andMe, Albert Einstein, bioinformatics, bitcoin, brain emulation, cloud computing, complexity theory, computer age, computer vision, conceptual framework, correlation does not imply causation, crowdsourcing, dark matter, data acquisition, Drosophila, epigenetics, global pandemic, Google Glasses, iterative process, linked data, mouse model, optical character recognition, pattern recognition, personalized medicine, phenotype, race to the bottom, Richard Feynman, Ronald Reagan, semantic web, speech recognition, stem cell, Steven Pinker, supply-chain management, Turing machine, twin studies, web application

Molecular biology has finally delivered on the early promises of the Human Genome Project, albeit decades later than forecast. Previous monolithic diseases, such as breast cancer, brain cancer, depression, dementia and autism, have splintered off into a myriad of more specific pathologies, defined not so much by common behavioral phenotypes but by shared mutations, molecular pathways and biochemical mechanisms. In combination with cheap, reliable, and fast genetic tests, the age of personalized medicine, long trumpeted by Leroy Hood, Craig Venter, and other pioneers, arrived in which familial predispositions to behavioral traits, pharmacological interventions, and diseases, permit much more targeted interventions. Bioterrorism has occasionally struck, but the combination of personal genomics, personal immunizers, and a ubiquitous surveillance state has largely kept the population safe.

Rockonomics: A Backstage Tour of What the Music Industry Can Teach Us About Economics and Life by Alan B. Krueger

accounting loophole / creative accounting, Affordable Care Act / Obamacare, Airbnb, autonomous vehicles, bank run, Berlin Wall, bitcoin, Bob Geldof, butterfly effect, buy and hold, creative destruction, crowdsourcing, disintermediation, diversified portfolio, Donald Trump, endogenous growth, George Akerlof, gig economy, income inequality, index fund, invisible hand, Jeff Bezos, John Maynard Keynes: Economic Possibilities for our Grandchildren, Kenneth Arrow, Kickstarter, Live Aid, Mark Zuckerberg, Moneyball by Michael Lewis explains big data, moral hazard, Network effects, obamacare, offshore financial centre, Paul Samuelson, personalized medicine, pre–internet, price discrimination, profit maximization, random walk, recommendation engine, rent-seeking, Richard Thaler, ride hailing / ride sharing, Saturday Night Live, Skype, Steve Jobs, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, ultimatum game, winner-take-all economy, women in the workforce, Y Combinator, zero-sum game

In professional sports, most of the revenue that teams earn is generated from selling television and cable rights to broadcast live games.28 Revenue from the gate for live sporting events is the equivalent of a live concert—but there is rarely an opportunity for musicians to earn additional money from recording or broadcasting their live shows. In the future, it would make economic sense for fans to purchase recordings and videos of live events, and for more artists to experiment with live-streaming their concerts to increase revenues. Personalization may also be coming to recorded music, just as personalized medicine is the frontier in health care. The multitalented singer and musician Jacob Collier has offered to personalize music for his patrons on Patreon. Fans submit a recording of their lyrics, and Collier puts it to music and harmonizes it. Not surprisingly, the music ends up sounding much better once the Grammy Award–winning musician is done. Other musicians offer to sing “Happy Birthday” or other songs for a customer, for a price.

pages: 321 words: 97,661

How to Read a Paper: The Basics of Evidence-Based Medicine by Trisha Greenhalgh

call centre, complexity theory, conceptual framework, correlation coefficient, correlation does not imply causation, deskilling, knowledge worker, longitudinal study, meta analysis, meta-analysis, microbiome, New Journalism, p-value, personalized medicine, placebo effect, publication bias, randomized controlled trial, selection bias, the scientific method

Shared decision making: a model for clinical practice. Journal of General Internal Medicine 2012;27(10):1361–7. 26 March L, Irwig L, Schwarz J, et al. n of 1 trials comparing a non-steroidal anti-inflammatory drug with paracetamol in osteoarthritis. BMJ: British Medical Journal 1994;309(6961):1041–6. 27 Lillie EO, Patay B, Diamant J, et al. The n-of-1 clinical trial: the ultimate strategy for individualizing medicine? Personalized Medicine 2011;8(2):161–73. 28 Moore A, Derry S, Eccleston C, et al. Expect analgesic failure; pursue analgesic success. BMJ: British Medical Journal 2013;346:f2690. Chapter 17 Criticisms of evidence-based medicine What's wrong with EBM when it's done badly? This new chapter is necessary because evidence-based medicine (EBM) has long outlived its honeymoon period. There is, quite appropriately, a growing body of scholarship that offers legitimate criticisms of EBM's assumptions and core approaches.

pages: 364 words: 99,897

The Industries of the Future by Alec Ross

23andMe, 3D printing, Airbnb, algorithmic trading, AltaVista, Anne Wojcicki, autonomous vehicles, banking crisis, barriers to entry, Bernie Madoff, bioinformatics, bitcoin, blockchain, Brian Krebs, British Empire, business intelligence, call centre, carbon footprint, cloud computing, collaborative consumption, connected car, corporate governance, Credit Default Swap, cryptocurrency, David Brooks, disintermediation, Dissolution of the Soviet Union, distributed ledger, Edward Glaeser, Edward Snowden,, Erik Brynjolfsson, fiat currency, future of work, global supply chain, Google X / Alphabet X, industrial robot, Internet of things, invention of the printing press, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Joi Ito, Kickstarter, knowledge economy, knowledge worker, lifelogging, litecoin, M-Pesa, Marc Andreessen, Mark Zuckerberg, Mikhail Gorbachev, mobile money, money: store of value / unit of account / medium of exchange, Nelson Mandela, new economy, offshore financial centre, open economy, Parag Khanna, paypal mafia, peer-to-peer, peer-to-peer lending, personalized medicine, Peter Thiel, precision agriculture, pre–internet, RAND corporation, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Rubik’s Cube, Satoshi Nakamoto, selective serotonin reuptake inhibitor (SSRI), self-driving car, sharing economy, Silicon Valley, Silicon Valley startup, Skype, smart cities, social graph, software as a service, special economic zone, supply-chain management, supply-chain management software, technoutopianism, The Future of Employment, Travis Kalanick, underbanked, Vernor Vinge, Watson beat the top human players on Jeopardy!, women in the workforce, Y Combinator, young professional

One Chinese CEO told me he believes that the wealth and power that came from being the center of the Internet’s commercialization extended America’s reign as a superpower by ten years. Many of the most powerful Chinese leaders believe that genomics is the next trillion-dollar industry, and they are determined to be its leader. One opportunity being monitored by the Chinese relates to the drug-development process in the United States. If the FDA does not change its drug-development process to speed the delivery of the kinds of personalized medicines made possible by genetic sequencing, as described by Luis Diaz and Lukas Wartman, then patients may go abroad (perhaps to China) for individualized treatment therapies. At the core of the Chinese strategy are companies and institutes like BGI that live in the gray space between state and private sector. These are nominally private organizations, but they are engorged with capital and blessed with support from China’s central authorities, who are determined to see them succeed for the benefit of China.

pages: 309 words: 114,984

The Digital Doctor: Hope, Hype, and Harm at the Dawn of Medicine’s Computer Age by Robert Wachter

"Robert Solow", activist fund / activist shareholder / activist investor, Affordable Care Act / Obamacare, AI winter, Airbnb, Atul Gawande, Captain Sullenberger Hudson, Checklist Manifesto, Chuck Templeton: OpenTable:, Clayton Christensen, collapse of Lehman Brothers, computer age, creative destruction, crowdsourcing, deskilling, disruptive innovation,, Erik Brynjolfsson, everywhere but in the productivity statistics, Firefox, Frank Levy and Richard Murnane: The New Division of Labor, Google Glasses, Ignaz Semmelweis: hand washing, Internet of things, job satisfaction, Joseph Schumpeter, Kickstarter, knowledge worker, lifelogging, medical malpractice, medical residency, Menlo Park, minimum viable product, natural language processing, Network effects, Nicholas Carr, obamacare, pattern recognition, peer-to-peer, personalized medicine,, Productivity paradox, Ralph Nader, RAND corporation, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley startup, six sigma, Skype, Snapchat, software as a service, Steve Jobs, Steven Levy, the payments system, The Wisdom of Crowds, Thomas Bayes, Toyota Production System, Uber for X, US Airways Flight 1549, Watson beat the top human players on Jeopardy!, Yogi Berra

For the 46-year-old man with high blood pressure, the target will no longer be a fixed number, like today’s 140/90. Rather, the system will determine each patient’s optimal blood pressure value, based on an analysis of risk factors, genes, and the ongoing monitoring of thousands of patients with similar risk profiles. The same will be true of cholesterol, glucose, and even cancer screening. The promise of personalized medicine will become a reality. Clinical research will also be transformed through the analysis of vast amounts of data on millions of patients. Determining the best treatment for high cholesterol, Crohn’s disease, or acute lymphocytic leukemia will no longer require expensive and elaborately choreographed clinical trials. Rather, there will be a true “learning healthcare system” in which real-world variations in tests and treatments are analyzed, and the ones associated with the best outcomes are identified.

pages: 386 words: 114,405

The Death of Cancer: After Fifty Years on the Front Lines of Medicine, a Pioneering Oncologist Reveals Why the War on Cancer Is Winnable--And How We Can Get There by Vincent T. Devita, Jr., M. D., Elizabeth Devita-Raeburn

Affordable Care Act / Obamacare, Albert Einstein, double helix, mouse model, personalized medicine, RAND corporation, randomized controlled trial, Ronald Reagan, stem cell

Or you can switch cell death on, which amounts to handing the cancer cell a sword and telling it to commit hara-kiri, thereby attacking another hallmark. An important part of managing patients now is to do a genetic analysis of their tumor tissue to determine its molecular structure and find treatable mutations and then to select a treatment based on the mutations. This is the essence of personalized medicine. We are no longer shooting in the dark. The best example is the treatment for chronic myeloid leukemia (CML), developed by my friend Brian Druker, the director of the Knight Cancer Institute at the Oregon Health and Science University. In the early 1970s, CML was incurable, and the average survival for CML was thirty-two months. The cancer went through a chronic phase and a phase of accelerated growth and finally ended in “blastic crisis,” a phase indistinguishable from acute leukemia.

pages: 437 words: 113,173

Age of Discovery: Navigating the Risks and Rewards of Our New Renaissance by Ian Goldin, Chris Kutarna

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, Airbnb, Albert Einstein, AltaVista, Asian financial crisis, asset-backed security, autonomous vehicles, banking crisis, barriers to entry, battle of ideas, Berlin Wall, bioinformatics, bitcoin, Bonfire of the Vanities, clean water, collective bargaining, Colonization of Mars, Credit Default Swap, crowdsourcing, cryptocurrency, Dava Sobel, demographic dividend, Deng Xiaoping, Doha Development Round, double helix, Edward Snowden, Elon Musk,, epigenetics, experimental economics, failed state, Fall of the Berlin Wall, financial innovation, full employment, Galaxy Zoo, global pandemic, global supply chain, Hyperloop, immigration reform, income inequality, indoor plumbing, industrial cluster, industrial robot, information retrieval, Intergovernmental Panel on Climate Change (IPCC), intermodal, Internet of things, invention of the printing press, Isaac Newton, Islamic Golden Age, Johannes Kepler, Khan Academy, Kickstarter, low cost airline, low cost carrier, low skilled workers, Lyft, Malacca Straits, mass immigration, megacity, Mikhail Gorbachev, moral hazard, Nelson Mandela, Network effects, New Urbanism, non-tariff barriers, Occupy movement, On the Revolutions of the Heavenly Spheres, open economy, Panamax, Pearl River Delta, personalized medicine, Peter Thiel, post-Panamax, profit motive, rent-seeking, reshoring, Robert Gordon, Robert Metcalfe, Search for Extraterrestrial Intelligence, Second Machine Age, self-driving car, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, Skype, smart grid, Snapchat, special economic zone, spice trade, statistical model, Stephen Hawking, Steve Jobs, Stuxnet, The Future of Employment, too big to fail, trade liberalization, trade route, transaction costs, transatlantic slave trade, uber lyft, undersea cable, uranium enrichment, We are the 99%, We wanted flying cars, instead we got 140 characters, working poor, working-age population, zero day

This matters to health, because it turns out that the oldest parts of the human genome—those lines of our DNA code that have been battle-tested over eons of evolution and are the same in most all of us—are also the most bullet-proof. Most of the genetic weak spots in our armor lie amidst so-called rare variations—more recent lines of code that occur in less than 1 percent of people. In other words, human beings are the same, but different. Mass-produced medicine glosses over the latter point; personalized medicine will embrace it. In 2015, the US Food and Drug Administration (FDA) approved the first 3D-printed drugs, which can be custom-made to match each patient’s ideal dosage requirements and absorption capabilities. And parents can already purchase genetic tests to screen their children for hundreds of known mutations and disorders. The day of a sequencing machine in every doctor’s surgery is beckoning.

pages: 523 words: 112,185

Doing Data Science: Straight Talk From the Frontline by Cathy O'Neil, Rachel Schutt

Amazon Mechanical Turk, augmented reality, Augustin-Louis Cauchy, barriers to entry, Bayesian statistics, bioinformatics, computer vision, correlation does not imply causation, crowdsourcing, distributed generation, Edward Snowden, Emanuel Derman, fault tolerance, Filter Bubble, finite state, Firefox, game design, Google Glasses, index card, information retrieval, iterative process, John Harrison: Longitude, Khan Academy, Kickstarter, Mars Rover, Nate Silver, natural language processing, Netflix Prize, p-value, pattern recognition, performance metric, personalized medicine, pull request, recommendation engine, rent-seeking, selection bias, Silicon Valley, speech recognition, statistical model, stochastic process, text mining, the scientific method, The Wisdom of Crowds, Watson beat the top human players on Jeopardy!, X Prize

Average Versus the Individual Randomized clinical trials measure the effect of a certain drug averaged across all people. Sometimes they might bucket users to figure out the average effect on men or women or people of a certain age, and so on. But in the end, it still has averaged out stuff so that for a given individual we don’t know what they effect would be on them. There is a push these days toward personalized medicine with the availability of genetic data, which means we stop looking at averages because we want to make inferences about the one. Even when we were talking about Frank and OK Cupid, there’s a difference between conducting this study across all men versus Frank alone. A/B Tests In software companies, what we described as random experiments are sometimes referred to as A/B tests. In fact, we found that if we said the word “experiments” to software engineers, it implied to them “trying something new” and not necessarily the underlying statistical design of having users experience different versions of the product in order to measure the impact of that difference using metrics.

pages: 356 words: 112,271

Brexit and Ireland: The Dangers, the Opportunities, and the Inside Story of the Irish Response by Tony Connelly

air freight, Berlin Wall, Big bang: deregulation of the City of London, Boris Johnson, call centre, centre right, Double Irish / Dutch Sandwich, eurozone crisis, Fall of the Berlin Wall, knowledge economy, LNG terminal, low skilled workers, non-tariff barriers, open borders, personalized medicine, race to the bottom, regulatory arbitrage, éminence grise

According to one senior academic source at Queen’s, a number of researchers who are funded by the European Research Council, the high-end EU panel described as a factory for future Nobel Prize winners, have turned down positions at Queen’s because they were convinced they would not be able to renew their ERC grants. ‘It’s hard to measure the effect of Brexit,’ says Professor Mark Lawler, who runs the Centre for Cancer Research and Cell Biology at Queen’s. ‘If you haven’t been invited to the party, you don’t know what you’ve missed.’ The centre is the jewel in the crown of UK cancer research, leading expertise on colorectal cancer, immunotherapy, genomics, precision and personalized medicine. In January 2017, Professor Lawler was the architect of a 60-strong coalition of patient advocates, healthcare professionals and scientists from 20 EU countries that published a blueprint for increasing cancer survival rates to 70 per cent by 2035. It works closely with industry, and has scientists working in its research building from Almac, the company that announced it was moving part of its manufacturing and distribution operations to Dundalk from Craigavon.

pages: 525 words: 116,295

The New Digital Age: Transforming Nations, Businesses, and Our Lives by Eric Schmidt, Jared Cohen

access to a mobile phone, additive manufacturing, airport security, Amazon Mechanical Turk, Amazon Web Services, anti-communist, augmented reality, Ayatollah Khomeini, barriers to entry, bitcoin, borderless world, call centre, Chelsea Manning, citizen journalism, clean water, cloud computing, crowdsourcing, data acquisition, Dean Kamen, drone strike, Elon Musk, failed state, fear of failure, Filter Bubble, Google Earth, Google Glasses, hive mind, income inequality, information trail, invention of the printing press, job automation, John Markoff, Julian Assange, Khan Academy, Kickstarter, knowledge economy, Law of Accelerating Returns, market fundamentalism, means of production, MITM: man-in-the-middle, mobile money, mutually assured destruction, Naomi Klein, Nelson Mandela, offshore financial centre, Parag Khanna, peer-to-peer, peer-to-peer lending, personalized medicine, Peter Singer: altruism, Ray Kurzweil, RFID, Robert Bork, self-driving car, sentiment analysis, Silicon Valley, Skype, Snapchat, social graph, speech recognition, Steve Jobs, Steven Pinker, Stewart Brand, Stuxnet, The Wisdom of Crowds, upwardly mobile, Whole Earth Catalog, WikiLeaks, young professional, zero day

Synthetic skin grafts, which exist today, will give way to grafts made from burn victims’ own cells. Inside hospitals, robots will take on more responsibilities, as surgeons increasingly let sophisticated machines handle difficult parts of certain procedures, where delicate or tedious work is involved or a wider range of motion is required.2 Advances in genetic testing will usher in the era of personalized medicine. Through targeted tests and genome sequencing (decoding a person’s full DNA), doctors and disease specialists will have more information about patients, and what might help them, than ever before. Despite steady scientific progress, severe negative reactions to prescribed drugs remain a leading cause of hospitalization and death. Pharmaceutical companies traditionally pursue a “one-size-fits-all” approach to drug development, but this is due to change as the burgeoning field of pharmacogenetics continues to develop.

pages: 476 words: 132,042

What Technology Wants by Kevin Kelly

Albert Einstein, Alfred Russel Wallace, Buckminster Fuller,, carbon-based life, Cass Sunstein, charter city, Clayton Christensen, cloud computing, computer vision, Danny Hillis, dematerialisation, demographic transition, double entry bookkeeping, Douglas Engelbart,, Exxon Valdez, George Gilder, gravity well, hive mind, Howard Rheingold, interchangeable parts, invention of air conditioning, invention of writing, Isaac Newton, Jaron Lanier, Joan Didion, John Conway, John Markoff, John von Neumann, Kevin Kelly, knowledge economy, Lao Tzu, life extension, Louis Daguerre, Marshall McLuhan, megacity, meta analysis, meta-analysis, new economy, off grid, out of africa, performance metric, personalized medicine, phenotype, Picturephone, planetary scale, RAND corporation, random walk, Ray Kurzweil, recommendation engine, refrigerator car, Richard Florida, Rubik’s Cube, Silicon Valley, silicon-based life, Skype, speech recognition, Stephen Hawking, Steve Jobs, Stewart Brand, Ted Kaczynski, the built environment, the scientific method, Thomas Malthus, Vernor Vinge, wealth creators, Whole Earth Catalog, Y2K

One billion live, always-on cameras serve as a community monitor and memory, they give the job of eyewitness to amateurs, they restructure the notion of the self, and they reduce the authority of authorities. One thousand teleportation stations rejuvenate vacation travel. One billion teleportation stations overturn commutes, reimagine globalism, introduce tele-lag sickness, reintroduce the grand spectacle, kill the nation-state, and end privacy. One thousand human genetic sequences jump-start personalized medicine. One billion genetic sequences every hour enable real-time genetic damage monitoring, upend the chemical industry, redefine illness, make genealogies hip, and launch “ultraclean” lifestyles that make organic look filthy. One thousand screens the size of buildings keep Hollywood going. One billion screens everywhere become the new art, create a new advertising medium, revitalize cities at night, accelerate locative computing, and rejuvenate the commons.

pages: 742 words: 137,937

The Future of the Professions: How Technology Will Transform the Work of Human Experts by Richard Susskind, Daniel Susskind

23andMe, 3D printing, additive manufacturing, AI winter, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, Andrew Keen, Atul Gawande, Automated Insights, autonomous vehicles, Big bang: deregulation of the City of London, big data - Walmart - Pop Tarts, Bill Joy: nanobots, business process, business process outsourcing, Cass Sunstein, Checklist Manifesto, Clapham omnibus, Clayton Christensen, clean water, cloud computing, commoditize, computer age, Computer Numeric Control, computer vision, conceptual framework, corporate governance, creative destruction, crowdsourcing, Daniel Kahneman / Amos Tversky, death of newspapers, disintermediation, Douglas Hofstadter,, Erik Brynjolfsson, Filter Bubble, full employment, future of work, Google Glasses, Google X / Alphabet X, Hacker Ethic, industrial robot, informal economy, information retrieval, interchangeable parts, Internet of things, Isaac Newton, James Hargreaves, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Khan Academy, knowledge economy, lifelogging, lump of labour, Marshall McLuhan, Metcalfe’s law, Narrative Science, natural language processing, Network effects, optical character recognition, Paul Samuelson, personalized medicine, pre–internet, Ray Kurzweil, Richard Feynman, Second Machine Age, self-driving car, semantic web, Shoshana Zuboff, Skype, social web, speech recognition, spinning jenny, strong AI, supply-chain management, telepresence, The Future of Employment, the market place, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, transaction costs, Turing test, Watson beat the top human players on Jeopardy!, WikiLeaks, young professional

., ‘Hydrogel bioprinted microchannel networks for vascularization of tissue engineering constructs’, Lab on a Chip, 14: 13 (2014), 2202–11. 47 <> and ‘Fact Sheets: Transplants save lives’, NHS website, Aug. 2014 <> (accessed 9 March 2015). 48 Erika Check Hayden, ‘Technology: The $1,000 Genome’, Nature, 19 Mar. 2014. 49 Francis S. Collins, The Language of Life: DNA and the Revolution in Personalized Medicine (2010), p. xviii discusses the services, but their costs are now far lower. See e.g. the $99 service at <> (accessed 27 March 2015). 50 Richard P. Feynman, ‘Plenty of Room at the Bottom’, talk to the American Physical Society at Caltech, Dec. 1959, p. 5 <> (accessed 27 March 2015). 51 Miguel Helft, ‘Google’s Larry Page: The Most Ambitious CEO in the Universe’, Fortune Magazine, 13 Nov. 2014 <> (accessed 27 March 2015). 52 David L.

pages: 565 words: 151,129

The Zero Marginal Cost Society: The Internet of Things, the Collaborative Commons, and the Eclipse of Capitalism by Jeremy Rifkin

"Robert Solow", 3D printing, active measures, additive manufacturing, Airbnb, autonomous vehicles, back-to-the-land, big-box store, bioinformatics, bitcoin, business process, Chris Urmson, clean water, cleantech, cloud computing, collaborative consumption, collaborative economy, Community Supported Agriculture, Computer Numeric Control, computer vision, crowdsourcing, demographic transition, distributed generation,, Frederick Winslow Taylor, global supply chain, global village, Hacker Ethic, industrial robot, informal economy, Intergovernmental Panel on Climate Change (IPCC), intermodal, Internet of things, invisible hand, Isaac Newton, James Watt: steam engine, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Julian Assange, Kickstarter, knowledge worker, longitudinal study, Mahatma Gandhi, manufacturing employment, Mark Zuckerberg, market design, mass immigration, means of production, meta analysis, meta-analysis, natural language processing, new economy, New Urbanism, nuclear winter, Occupy movement, off grid, oil shale / tar sands, pattern recognition, peer-to-peer, peer-to-peer lending, personalized medicine, phenotype, planetary scale, price discrimination, profit motive, QR code, RAND corporation, randomized controlled trial, Ray Kurzweil, RFID, Richard Stallman, risk/return, Ronald Coase, search inside the book, self-driving car, shareholder value, sharing economy, Silicon Valley, Skype, smart cities, smart grid, smart meter, social web, software as a service, spectrum auction, Steve Jobs, Stewart Brand, the built environment, The Nature of the Firm, The Structural Transformation of the Public Sphere, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas L Friedman, too big to fail, transaction costs, urban planning, Watson beat the top human players on Jeopardy!, web application, Whole Earth Catalog, Whole Earth Review, WikiLeaks, working poor, zero-sum game, Zipcar

More and more scientists in universities and foundation-sponsored laboratories around the world are abandoning the idea of patenting genetic information in favor of uploading their research in open-source networks to be shared freely with colleagues in managed Commons. The Creative Commons license has been implemented by the Harvard University Medical School in its Personal Genome Project.25 This is a long-term cohort study that aims to sequence and publicize the genome and records of 100,000 volunteers in order to advance research in the field of customized personal medicine.26 All the genome data covered by a Creative Commons license will be put in the public domain and be made available on the Internet to allow scientists open and free access for their laboratory research.27 Despite the success of the Creative Commons licensing, Lessig takes every opportunity to distance himself from what he calls “a growing copyright abolitionist movement.”28 He believes that copyright will remain a viable part of the coming era but will need to make room for open-source licensing in a world that will be lived partially in the market and partially on the Commons.

Never Bet Against Occam: Mast Cell Activation Disease and the Modern Epidemics of Chronic Illness and Medical Complexity by Lawrence B. Afrin M. D., Kendra Neilsen Myles, Kristi Posival

Affordable Care Act / Obamacare, Albert Einstein, epigenetics, invisible hand, Isaac Newton, megacity, microbiome, mouse model, obamacare, pattern recognition, personalized medicine, phenotype, pre–internet, selective serotonin reuptake inhibitor (SSRI), stem cell

Molderings’ group – again, that mast cell KIT is significantly mutated in a wide variety of ways across most subjects in an MCAS patient population (and, importantly, not significantly mutated in healthy control subjects). My study will be looking in the study subjects’ blood samples for mutations in a wide array of other mast cell regulatory genes, too. Results hopefully will be published by late 2016. Chapter 24: What We Know About the Genetics of Mast Cell Disease (Short Answer: Not Much – Yet) We’ve been hearing for several years now that the era of genomically personalized medicine is almost upon us, a time when at a cost of perhaps a few hundred dollars we will be able to determine anybody’s complete genetic code which – and here’s where we wave our hands in a magic gesture – will tell us all that’s wrong with us now and all that’s likely to go wrong with us. Yeah, right. If only. I don’t have a problem with the first part of that supposition. There’s really no question at all that “any time now” we will be able to determine anybody’s complete genetic code for a few hundred dollars, or less.

pages: 677 words: 206,548

Future Crimes: Everything Is Connected, Everyone Is Vulnerable and What We Can Do About It by Marc Goodman

23andMe, 3D printing, active measures, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, airport security, Albert Einstein, algorithmic trading, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, Bill Joy: nanobots, bitcoin, Black Swan, blockchain, borderless world, Brian Krebs, business process, butterfly effect, call centre, Charles Lindbergh, Chelsea Manning, cloud computing, cognitive dissonance, computer vision, connected car, corporate governance, crowdsourcing, cryptocurrency, data acquisition, data is the new oil, Dean Kamen, disintermediation, don't be evil, double helix, Downton Abbey, drone strike, Edward Snowden, Elon Musk, Erik Brynjolfsson, Filter Bubble, Firefox, Flash crash, future of work, game design, global pandemic, Google Chrome, Google Earth, Google Glasses, Gordon Gekko, high net worth, High speed trading, hive mind, Howard Rheingold, hypertext link, illegal immigration, impulse control, industrial robot, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Jaron Lanier, Jeff Bezos, job automation, John Harrison: Longitude, John Markoff, Joi Ito, Jony Ive, Julian Assange, Kevin Kelly, Khan Academy, Kickstarter, knowledge worker, Kuwabatake Sanjuro: assassination market, Law of Accelerating Returns, Lean Startup, license plate recognition, lifelogging, litecoin, low earth orbit, M-Pesa, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Metcalfe’s law, MITM: man-in-the-middle, mobile money, more computing power than Apollo, move fast and break things, move fast and break things, Nate Silver, national security letter, natural language processing, obamacare, Occupy movement, Oculus Rift, off grid, offshore financial centre, optical character recognition, Parag Khanna, pattern recognition, peer-to-peer, personalized medicine, Peter H. Diamandis: Planetary Resources, Peter Thiel, pre–internet, RAND corporation, ransomware, Ray Kurzweil, refrigerator car, RFID, ride hailing / ride sharing, Rodney Brooks, Ross Ulbricht, Satoshi Nakamoto, Second Machine Age, security theater, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart grid, smart meter, Snapchat, social graph, software as a service, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, Stuxnet, supply-chain management, technological singularity, telepresence, telepresence robot, Tesla Model S, The Future of Employment, The Wisdom of Crowds, Tim Cook: Apple, trade route, uranium enrichment, Wall-E, Watson beat the top human players on Jeopardy!, Wave and Pay, We are Anonymous. We are Legion, web application, Westphalian system, WikiLeaks, Y Combinator, zero day

In the end, for the first time ever, the National Science Advisory Board for Biosecurity stepped in and asked the journals to limit the details published, to which they temporarily agreed. This particular risk was momentarily avoided, but the code will eventually leak, and others will surely be created. While a broad-based bioterror attack would be devastating, synbio makes it possible to target not only a whole population but possibly a single individual among millions. Personalized medicine has demonstrated it is possible to target a single cancer cell while leaving all surrounding cells intact, but the flip side is personalized bioweapons. In the future, would-be bio-assassins need only recover some genetic material left behind on a fork or spoon at a restaurant, perhaps from a high-profile politician or celebrity, to create a bespoke weaponized virus. Though one might think such scenarios are relegated solely to the realm of science fiction, news broke as part of the WikiLeaks scandal that the U.S. government had allegedly sent diplomatic cables to its embassies overseas instructing personnel to attempt to collect the DNA of world leaders—presumably not to enroll them in Obamacare.

pages: 903 words: 235,753

The Stack: On Software and Sovereignty by Benjamin H. Bratton

1960s counterculture, 3D printing, 4chan, Ada Lovelace, additive manufacturing, airport security, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic trading, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, basic income, Benevolent Dictator For Life (BDFL), Berlin Wall, bioinformatics, bitcoin, blockchain, Buckminster Fuller, Burning Man, call centre, carbon footprint, carbon-based life, Cass Sunstein, Celebration, Florida, charter city, clean water, cloud computing, connected car, corporate governance, crowdsourcing, cryptocurrency, dark matter, David Graeber, deglobalization, dematerialisation, disintermediation, distributed generation, don't be evil, Douglas Engelbart, Douglas Engelbart, Edward Snowden, Elon Musk,, Eratosthenes, Ethereum, ethereum blockchain, facts on the ground, Flash crash, Frank Gehry, Frederick Winslow Taylor, future of work, Georg Cantor, gig economy, global supply chain, Google Earth, Google Glasses, Guggenheim Bilbao, High speed trading, Hyperloop, illegal immigration, industrial robot, information retrieval, Intergovernmental Panel on Climate Change (IPCC), intermodal, Internet of things, invisible hand, Jacob Appelbaum, Jaron Lanier, Joan Didion, John Markoff, Joi Ito, Jony Ive, Julian Assange, Khan Academy, liberal capitalism, lifelogging, linked data, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, Masdar, McMansion, means of production, megacity, megastructure, Menlo Park, Minecraft, MITM: man-in-the-middle, Monroe Doctrine, Network effects, new economy, offshore financial centre, oil shale / tar sands, packet switching, PageRank, pattern recognition, peak oil, peer-to-peer, performance metric, personalized medicine, Peter Eisenman, Peter Thiel, phenotype, Philip Mirowski, Pierre-Simon Laplace, place-making, planetary scale, RAND corporation, recommendation engine, reserve currency, RFID, Robert Bork, Sand Hill Road, self-driving car, semantic web, sharing economy, Silicon Valley, Silicon Valley ideology, Slavoj Žižek, smart cities, smart grid, smart meter, social graph, software studies, South China Sea, sovereign wealth fund, special economic zone, spectrum auction, Startup school, statistical arbitrage, Steve Jobs, Steven Levy, Stewart Brand, Stuxnet, Superbowl ad, supply-chain management, supply-chain management software, TaskRabbit, the built environment, The Chicago School, the scientific method, Torches of Freedom, transaction costs, Turing complete, Turing machine, Turing test, undersea cable, universal basic income, urban planning, Vernor Vinge, Washington Consensus, web application, Westphalian system, WikiLeaks, working poor, Y Combinator

Over the course of our individual lives, our bodies provide selection pressures on how our individual microbial biomes change and evolve inside us. What we eat, in particular, can fundamentally alter the alien ecology in our gut, for better or worse. A poor diet can force the evolution of the biome toward an unhealthy state in which it no longer supports our health and instead could contribute to significant malaise in the entire biological mechanism. Smarr's personal medicine is somewhat unusual in that the focus is shifted from the self-regard of his own somatic body toward the curation and gardening of this internal microbial civilization. Inside the shell of one's skin, there is far more DNA that is nonhuman than DNA that is human. You, the skin bag, are all too less human than human. Even to the extent that your individual corporeal machine is to be taken as the base unit of medical analysis and political subjectivity, it is already a multispecies arrangement.