Early Indications August 2019: The YouTube Effect

Only five years after YouTube launched in 2005, Chris Anderson of TED gave a remarkably insightful talk not coincidentally on — and about — his online platform. He pointed first to the primacy of print for more than 500 years: to get words, still pictures, and ideas to mass audiences, face-to-face communication simply could not match the scale of print. In a blink of historical time, however, that primacy was dislodged by online video. As a medium, it conveys vocal inflection, body languages, and facial features: the cues humans spent millennia learning to discern. Even more importantly, online video conveys these nuances at often zero cost to massive audiences, nearly instantaneously but asynchronously. As of 2017, a billion hours of YouTube video were viewed every day and as of 2020, 2 billion people will be logging in at least once a month.

In contrast to print media, which is characterized by high costs and thus gatekeepers who ration scarce production and distribution capacity, online video is a big tent. The volume of contributed video that is available is simply staggering, unfathomable (not to mention uncatalogable) at human scale. This unprecedented access increases diversity of viewpoints but raises powerful questions about truth, fact, and accuracy. The lack of any cataloging system and only minimal content standards allows almost anything short of pornography and extreme violence to be allowed in. Furthermore, even though YouTube creates very little video (though this is changing), the curation process is extremely important. Since moving to new recommender systems in 2018, the YouTube algorithms that successfully keep viewers watching inexorably steer them toward videos with higher “engagement,” usually in the form of more extreme positions. The most benign query can lead to pseudoscience or worse in only six to eight auto-plays. (Zeynep Tufekci at UNC has done important work on YouTube and radicalization.) As we will see, every benefit brought by online video implies troubling downsides as well.

YouTube, Vimeo, and their kin act as a repository for everything from political speeches to standup comedians, serving as a sort of attic for many cultural artifacts, both widely popular and deeply personal to an individual or small group. As of 2018 YouTube alone streamed more songs than Amazon, Spotify, and Apply combined (while paying by far the lowest royalty rates: 48% of streams delivered but only 7% of artist revenue). For every Justin Bieber, there are many thousands of amateurs: one finds both Hollywood hits and anonymous piano practices. Self-made stars have emerged in areas from high school sports to fashion to online gaming to commentary at the same time that millions of videos get views in the single digits. 

Finally, online video is a terrific teacher, whether of piano, home appliance repair, makeup technique, or new languages. Former music professor Rick Beato has a series of videos explaining instrumental technique, composition, and dissections of “what makes this song great.” It’s hard to imagine a million people signing up to learn music theory in the physical world, but Beato is so good at his craft that he’s got a huge following. Haas machine tools does a "video tip of the day" that's incredibly engaging even if you've never come within 100 feet of a CNC machine. Along with the company's other quality content, I've never seen better corporate use of online video. 

In contrast to television and movies, the cultural ethos of online video is markedly more diverse. Wikipedia’s list of the 17 historically most viewed YouTube videos includes Brazilian soccer legend Ronaldinho, U.S. based amateur dancer Judson Laipply, the finger-biting English baby Charlie, and as I write, Luis Fonsi, a Puerto Rican singer singing in Spanish. The longest-tenured artist on the list is the Korean singer-songwriter-record producer-rapper Psy: “Gangnam Style” was the most-watched YouTube video in history for 1689 days -- more than 4 ½ years. Such cultural reach and range bring a multitude of opportunities and side effects.

Here’s one example. Content owners have a variety of available responses when Google finds videos that might include copyrighted material. One individual was accused of using the takedown process maliciously: he set YouTubers up with two notices, in preparation for a “three strikes and you’re banned” expulsion from what is for many a very profitable platform. Sometimes he asked for money to refrain from [fraudulently] shutting down the people's channels. In one case, said individual used the takedown process to obtain a real-world physical address — to which he sent police in a “swatting” raid. The entire DMCA apparatus was not designed for a planet-scale online video platform, but this is only one example of the many unintended consequences of YouTube and related services.

In line with this set of cultural functions, we have to find ways to think about online video as a medium, one bringing massive value but also putting new demands on regulators, viewers, uploaders, algorithm designers, advertisers, content owners, and others in the vast ecosystem. To take but one example, online video is a different kind of text compared to either print or broadcast TV, and new forms of literacy and illiteracy are emerging. Unlike television, where a linear schedule was the organizing principle (until the dawn of the streaming era), asynchronous online video is governed by search and recommendation, both human and algorithmic. This difference in wayfinding has many implications for what is made, seen, propagated, and imitated.

To conclude, the story of Kenya’s Julius Yego is both heartwarming and instructive. His country boasts a rich tradition of distance running but has had little success in field events such as the high jump or shot put. In 2009 Yego was frustrated by his progress with the javelin, so he spent time in the cybercafe watching every javelin-related video he could find, with particular attention to training programs. In 2011 he became the first Kenyan to win a title in a field event at the All Africa games; by 2015 he was world champion. Yego then earned a silver medal at the 2016 Olympics despite suffering an ankle injury. There is no way an athlete from a developing economy could master a technique-intensive event looking at books: Yego’s medals show we are living in the presence of not only a new medium, but a new distribution system, a new curation method, and a new scale of knowledge exchange. 

Online video has the potential to redefine human institutions from sewing to citizenship to psychotherapy. One of the challenges is finding ways to study such a vast, dynamic, culturally significant, and heterogeneous platform. DM me if you have ideas.

Early Indications July 2019: Time for innovation?

Before we dive into this month’s newsletter, I have some professional news. In August I will join the faculty of the Syracuse University school of information sciences. My first task is to investigate restarting the school’s professional doctorate program. Much like a DBA (doctorate in business administration) in contrast to a Ph.D. in accounting, finance, or whatever, the Doctorate in Professional Studies is aimed at mid-career professionals in IT, librarianship, analytics fields, and similar domains (including the military). The emphasis is on applying academic knowledge to real-world situations, usually in some form of a case study method, as opposed to creating new knowledge. If you know of people in your network who might be interested, or if you have thoughts on what or how we should be teaching, please let me know: I’m in exploratory mode and many options are still in play regarding curriculum, class formation, admissions, and the thesis process. There is a personal side to the story as well. All in all, I’m very fortunate and excited to be starting on a new chapter.

If you look at this month’s title, it can be read two different ways, and I will address both. I’m working with a technical executive at a private equity-owned company, and he has crystallized some things I sort of knew. If you are a new CEO, let’s suppose, you need some time to learn the business but also need to deliver results sooner rather than later. Let’s suppose you have 3 years to bring home some solid results. There are a very small number of levers you can pull:

-buy more revenues via corporate acquisition
-expand the existing market by demographics, geography, or new use cases
-buy back shares with cash
-cut costs, usually via layoffs or selling off a business
-get more out of existing assets by motivation, improving execution, improving the talent base, etc
-change the business model: products can be sold as services, retailers can go omnichannel, point offerings can become systems solutions, and so on
-launch something completely new after some form of innovation process.

Which of those tasks can you achieve in 3 years? True innovation may offer the biggest upside, but given the short time window for executives to keep their jobs, innovation is too risky to bet one’s job on.

The history of Kraft Heinz proves instructive here. Private equity bankers started with Heinz in 2013, radically cut costs, then bought the larger Kraft two years later. Unlike 3G Capital’s previous success stories (Anheuser Busch and Burger King), Kraft has not responded to the ruthless cost cutting that included memos encouraging employees to print on two sides of each page. The merged Kraft Heinz (revenues of $26 billion) then in 2017 tried to buy Unilever (revenues about $54 billion), reflecting 3G’s fondness for the ratchet play it had more successfully executed in the beer business. Execution in the food world proved harder to demonstrate, however, and the stock price dropped 27% in a single day following a $15 billion write-down this past spring. A line of healthy but “comfort” foods co-launched with Oprah Winfrey has failed to gain traction, for example, and the SEC is investigating accounting practices in the firm’s procurement area. Meanwhile Kraft’s power brands lag competitors and the current upheaval has resulted in financial reports being issued months behind schedule. (For more, see this and this.)

Consider that the Kraft Heinz CEO who left in July was a 3G partner: even he had a finite timetable. Innovation in consumer goods segments is notoriously difficult: “New” Coke is still taught as a cautionary tale in business schools 30 years after the debacle. Now consider business-to-business markets like chemicals or industrial components like ball bearings or hydraulic fittings, where innovation requires some combination of extraordinary insight, luck, and precise execution. It’s no surprise that CEOs and management teams shy away from innovation, no matter how promising or how needed, in the name of self-preservation.

Perhaps innovation cannot be funded by public or private equities markets, so what about venture capital? VCs have longer time horizons and generally don’t sweat quarterly profitability numbers. Lyft and Uber both went public as money-losing concerns, Tesla has yet to report a profit, and Netflix is financing its massive expansion of programming development with debt at the same time that subscriber growth is slowing. Where are VCs investing? According to CB Insights and PWC, Internet companies received the bulk of investment in Q2 of this year, followed by healthcare (at about 1/3 the investment in Internet) followed by mobile and telecommunications. And which companies have raised the most money? This is depressing:

1) Juul e-cigarettes
2) WeWork (how much is really there? Lead investor Softbank dialed back a planned $16 billion investment to $2 billion)
3) Airbnb
4) SpaceX
5) Magic Leap (VR software said to be very impressive by people I trust)

The biggest deal that quarter was Honda, GM, and Softbank investing in an AI self-driving startup. Meal delivery is still hot. Student loan refinancing is a big driver of growth at SoFi, another prominent startup. How many of these innovators will deliver something “insanely great”? We’ve got a new hyper-addictive toxin marketed at high schoolers, a couple financial engineering plays, a billionaire’s rocket company, a genuinely transformational online real estate marketplace, and a software that so far has been mainly used for gaming.

Compare those targets with the genuinely big social needs we face:

-rising ocean levels are beyond the “how much are humans responsible” phase of concern
-urban migration means hundreds of millions of people will soon need places to live, ways to be fed, and modes of transportation that scale to the mega-cities we are building
-increased longevity has the implication of elder care and no big country has adequate infrastructure in place for the numbers and needs of the aged expected in 2030
-democracy as a mode of governance has been broken by Internet-related technologies
-technical, financial, career, and other forms of literacy need to be improved to match the world that is emerging
-in the U.S., cities and states struggle with long-term pension and retiree health care obligations. Alaska is slashing education spending in the aftermath of low oil prices, Illinois has unfunded pension obligations of $133 billion, and New Jersey is close behind at $100 billion.

Not all of these represent market opportunities, but many do. As I have noted previously, it’s difficult to see where new planet-scale innovations will come from. DARPA, universities, and the private sector each have factors inhibiting them from driving major new thinking. Given the amount of VC investment in China, perhaps that country's mode of economic organization will give us pathbreaking medical treatments like penicillin, technologies like the Internet and GPS, healthy agricultural productivity improvements, and transportation improvements on par with the shipping container rather than the electric scooter.

But I doubt it (China has had scooter messes of its own, for starters) and the question remains: where will we see enough resources invested with a long enough time horizon in the massive market opportunities noted above? What will the investors accept as success? And in several areas (climate change and pension reform?), how will a delayed start on serious action make the ultimate task much harder than it needed to have been?

Early Indications June 2019: Watched and Lonely?

The processes by which technologies become adopted, accommodated, and normalized (and by extension, rejected, resisted, and marginalized) are incredibly complex. Existing culture, other technologies, demographics, and economics all interact, and all the while each of those factors also evolves over time. Taste-makers and the power of habit both play a role. Given that the latest wave of technologies affect people's minds and psyches in powerful ways that are not yet well understood, a few musings seem to be in order.

The MIT psychologist Sherry Turkle talks of our dependence on smartphones as a mechanism whereby people are reduced in importance; she says we expect more from devices and less from friendships. Despite the huge communications matrix in which we live, it’s common to fear that nobody is listening when we speak (or type). As a result, discourse can get amplified beyond healthy levels as people yell louder, literally and metaphorically, taking more and more extreme positions in the pursuit of clicks.

Turkle suggests that a fear of being alone is yet another of many paradoxes generating our communications practices. She posits, convincingly to my ear, that we need to learn how to be alone and to reflect before we can enter into meaningful, healthy relationships. Obviously the sheer volume of tweets, posts, and texts suggests that there isn't a lot of time for reflection, in the industrial west anyway, especially among those whose identities are still forming. 

At the same time, we also leave more digital bread crumbs than ever before, making being alone a dubious proposition. I'm told school-age kids now routinely walk into a room and ask if Amazon's Alexa is present. Weirdly, we may feel like no _body_ is listening even as multiple _devices_ may be doing so. Numerous apps surreptitiously trigger the smartphone microphone without notifying the user; in one instance, sports fans were unwittingly turned into beacons alerting rights-holders to pubs broadcasting games without paying for the required license.

What will be the consequences of being tracked by what Shoshanna Zuboff (professor emerita at Harvard Business School) calls "big other"? What will be the personality traits of young adults who grow up on and around screens? What will be used for shaming, both publicly and privately? It’s instructive to consider that after electric lights came into household use, housewives were exhorted to keep kitchens sanitary, in part by buying white appliances (that are still called "white goods" in the trade). To probe just one facet of the comparison, will our kitchen counters get the equivalents of Fitbits, broadcasting germ or ant counts to waiting audiences?

What will potential feedback from everyday use (generated by these listening devices) mean for design? Today, if I'm responsible for a steering wheel or office chair, I have little sense of how people actually use it in life. Given how cheap sensors are becoming, who will collect the usage data, package it, and sell it back, potentially to my competitors or (as today) to advertisers? As of a year or two ago, Internet-connected Roombas were sending maps of their owners' houses back to the mothership, to take but one example. Will our physical world parallel the wide use of A/B testing in digital user experience design? What might such an environment look and feel like? (Disneyland might be one guess.)

What will become acceptable that was problematic only a few years ago? How will we know who's watching, listening, measuring, counting? What will be the legislative responses, and how much will they reflect massive lobbying by Facebook, Google, Amazon, games companies, insurers, and other businesses with many billions of dollars at stake? Google alone has been fined more than $9 billion for privacy violations by the EU in the past 3 years and it's hard to see any change in the company's culture or behavior. If fines don’t change anything, what will?

Will there be backlash, possibly in the form of a return to analog? A paper diary is invisible and thus worthless to anyone outside the author, and letters may be found to have a new-found charm compared to phone calls, texts, and emails. Movies and songs from streaming services can disappear suddenly: will more people want the certainty of physical ownership? Will any other deep-seated emotions overcome the fear of missing out that drives so much attraction to social media among my students who realize some of the costs of their use of the various services? 

Never before have so many people been micro-targeted in massive behavioral experiments with little or no regulation or accountability. This is deeply concerning. Given the resilience of the human psyche, it's unclear what will turn out to be injurious, enhancing, and/or background noise in the long-term view of these matters: at the same time that people can survive horrific experiences, little nudges can also add up. Looking back from 2030 or 2050, what will people view of today’s world with amusement, horror, disgust, or bewilderment? What will be the equivalent of Big Tobacco, asbestos, margarine, or the moon landing?

One question looms large: given the pervasiveness of this stuff, how will anyone be able to find control populations for meaningful research? That is, how can anyone compare a psyche that is under constant surveillance and manipulation to that of someone with fewer external factors at work? That leaves us where we started: what Zuboff calls “surveillance capitalism” appears to have become normalized, another extension of Sun Microsystems CEO Scott McNealy’s 1999 admonition to “get over it” when people asked him about privacy. 

The fact that such an attitude was shocking 20 years ago feels almost quaint in light of the intervening revelations about Facebook, the NSA, and dozens of entities in between: what McNealy controversially saw as routine was significantly less invasive than what is done today. It feels a bit like the parable (now well debunked) of the frog in boiling water. Whether the metaphorical water is heating fast or slowly, it does seem like some jumping out of the pot might be in order, and quickly.

Early Indications May 2019: The Next Infrastructure

If we look ahead into the medium term, to 2025 or 2030, there could be some subtle  but significant changes to US infrastructure to cope with the implications of several  emerging technologies. Many of these may be emerging in quiet locations, but if one  knows where to look, the landscape might be changing before our eyes. Let’s start with telecommunications, much of which is a matter of access. When you  look at the world’s nations ranked by land mass, it’s easy to neglect how vast Russia  is, even downsized from the former USSR: it’s twice as big as the #5 nation (Brazil).  Also, I was surprised to see that both Canada and the US are larger than China.  India, despite its massive population, is only 1/5 as large as Russia and about 1/3  the size of the US. The US total is deceiving: about 400,000 square kilometers are  water, and Alaska counts for about 1/6 of the #3-ranking total.  Why does this matter, apart from trivia night? Connecting people into the Internet is  expensive, difficult, and complicated. Rural broadband is emerging as a hot political  topic here in Pennsylvania: the state defines “broadband” as a measly 1.4 Mbps (the  FCC definition is 25), and many people can’t get that except by expensive and  unreliable satellite coverage. By way of comparison, Finland has established  broadband access as a right of citizenship, with the goal of getting every citizen  access to _at least_ a 100 Mbps connection by 2025.  A few hundred miles to Pennsylvania’s southwest, Kentucky shares our  prevalence of sparsely populated areas featuring rugged terrain. A statewide project  known as KentuckyWired that launched in late 2014 aimed to address the digital  divide: Kentucky is fifth worst in the US in high-speed Internet use and not  coincidentally fifth poorest as measured by median household income. To fund the  buildout, the state engaged an Australian bank with a long history of infrastructure  projects. In the five years since the deal was signed, construction progress is far  behind schedule and the complexity of the debt covenants is kicking in: the state  auditor estimates KentuckyWired will now cost $1.5 billion over the next 30 years,  or 50 times the original proposal. (ProPublica’s reporting in conjunction with the  Louisville Journal-Courier is detailed and dispiriting. ) This situation is common in the US: Take away the metroplexes (146 densely  populated counties) that are home to half of the population, and the other half is  scattered across the remaining 95% of counties. Cell coverage can be spotty in  these locales, which makes the prospect of 5G wireless broadband unlikely, given  the expensive necessity of more cells for the smaller coverage footprint of the new  technology. Whether for wired or wireless access, something as seemingly simple  as a telephone pole can be legally complicated, financially costly, and logistically  tricky to maintain: at our local airport I’ve seen helicopters that lower saws in flight  to cut away brush and branches from otherwise inaccessible wires. Absent Internet connectivity, millions of people can’t see doctors, access learning  materials, or work remotely. As robotics, telemedia, and Internet of Things  applications increase in importance, these citizens will fall still farther behind their  better-connected counterparts, both in the US and abroad. At some point, focused  effort on a national scale will be required to update the communications infrastructure.  This will happen as bridges and roads continue to crumble, and as the generation of  federal, state, and local workers who began to join public payrolls in the 1960s  continues to retire. Oh, and Social Security is due to run out of money in 2034.  Funding broadband will not be a simple matter in any state. Let’s turn from flyover zones to cities. Here, the combination of crushing population  density, demographic trends, and technology change will bring a very different set of  scenarios. Given the recent IPOs of Lyft and Uber, let’s start with cars. It’s currently  unclear what autonomous vehicles will do for traffic: some studies predict  increased delays while others foresee improvement. In any event, it would seem  intuitive to predict that the need for parking will drop, to take only one aspect of change.  The coexistence of cars (autonomous or human-driven) and bicycles will require new  urban designs, assumptions, and attitudes; infrastructure cannot be built in isolation,  as New York would seem to prove. No city in the US appears to be rethinking the role  of cars in the city core, apart from a congestion pricing experiment about to launch  in New York. I was in a meeting earlier this month where logistics experts discussed the future of  food. Meal delivery appears to be resonating with large audiences, which raises the  issue of where all that food will be prepared. Fast-food outlets are in much the same  situation as Macy’s stores attempting to implement omnichannel logistics: neither the  retailer nor the food franchises were built to support delivery of product to customers  off the store premises. Kitchens at McDonalds are already coping with more menu  options including salads and parfaits along with all-day breakfast; where and how  should UberEats and Grubhub customers be serviced in the existing kitchen and  cashier architecture? What should the new design seek to optimize? Some restaurants are pulling out of the delivery business, or are opting for branded  drivers rather than contractors who may or may not represent the restaurant with its  desired courtesy, promptness, and attention to detail. Dominos has long wrestled with  the dilemma of drivers who speed or otherwise poorly represent the company, and  there are no easy answers. The UberEats driver is a contractor to a contractor, so  allegiance is a fluid proposition: most Lyft drivers are also signed up with Uber, and  UberEats delivers for many restaurants. There’s a lot of room for competing priorities  in such a labor pool. Assuming the driver quality issue can be addressed, possibly by better pay, the kitchen  situation remains problematic. Around the world, multiple startups are launching  so-called ghost or cloud kitchens. These kitchens are commissaries that serve multiple  ethnic formats from a common infrastructure that has no visible presence or dining (or  carryout) area. Uber’s co-founder Travis Kalanick is involved with a firm called  Cloudkitchens that only services meal delivery firms. SoftBank’s Vision Fund has  invested $357 million in Zume Pizza, which uses robotics to prepare pizza for  delivery en route to the customer. On a smaller scale but already in market, Good Uncle is a food delivery startup  aimed at college students. Like Zume, it cooks pizzas en route to the customer,  which improves both speed and quality, but the service is also working on an  aggregated delivery model: rather than stop at every house or apartment that  has ordered food, it delivers at visible, logical campus locations. Right now the  service is operating in Bethlehem, PA, College Park, MD, and Hamilton and  Syracuse, NY. The talent behind the food includes chefs from Michelin- tar restaurants, and the service is in some cases replacing the student dining hall.  Good Uncle delivers groceries as well as cooked meals, does not add delivery  charges, and offers daily discounts, presumably to cut down on food waste of  slow-selling perishable items. Speaking of delivery, infrastructure will need to evolve to address the Amazon  issue of how to manage the last 50 feet. For apartment buildings without a  doorman or similar attendant, for free-standing houses with visible porches,  and for gig workers who might operate out of a Starbucks or other temporary  space, the delivery model (especially for frequently ordered items such as groceries)  doesn’t scale: UPS can’t keep coming back day after day if nobody will ever be  home during business hours. At the local FedEx ground location where I pick up  wine shipments that require an in-person signature, I was told that mine was one  of up to 50 such shipments per day; the holding room for packages sometimes  overflows into the main store. As autonomous vehicles reset the economics of automobile ownership, what happens  to tens of millions of US garages? At the same time, where will urban dwellers without  a garage charge electric cars at night? Will parking meters need to be rewired to include  high-voltage chargers? As the nature of the car and its relation to the city change,  everything from carry-out windows to parking lots to domestic architecture will change  in response. Will garage-door openers selectively allow access to deliveries, and will  refrigerators become commonplace in these post-garage spaces? The days of the  foyer, ice-delivery boxes, and milk boxes on porches may be circling back.  Will we see more use of e-bicycles that function like small pickup trucks? If so,  how will laws, norms, and space co-evolve? What will constitute a “bike lane”  for such chunky vehicles? All told, changes in connectivity, whether 5G or rural broadband, will bring with  them implications for how people get around, especially in relation to what the tech  analyst Horace Dediu calls “micromobility” centered around scooters, bicycles, and  related technologies. As old as the bicycle may be, it remains a wonder of technological  efficiency and with changes to batteries, motors, GPS, and other emerging technologies,  the mid-21st century could mark a new blossoming of interest and innovation. If Dediu is  right, and I believe he is, then many parts of the world will look very different (read: more  like Amsterdam) in a decade or two.

Early Indications April 2019: Review essay: Deep Medicine by Eric Topol

Note: I neglected last month to announce that MIT Press has published my book on 3D printing,  and that an article on some managerial implications of same came out in the Journal of  Organizational Design.  ***** Eric Topol is a cardiologist who is very visible on the front lines of the medical field as it intersects  with smartphones, distributed sensors, and other emerging technologies. His most recent book  looks at "how artificial intelligence can make healthcare human again," in the words of the subtitle.  While I have plenty of honest disagreements with Topol's book, I very much respect it, and hope  that it jump-starts some way-overdue discussions about the future of medicine, particularly in the US. Given that I don't work in medicine, I'm extrapolating my lay experience here. The phrase  "personalized medicine" conjures up, for me at least, micro-targeted pharmaceuticals: my dose of  heart, anti-depressant, or chemotherapy medication will be fit precisely to my weight, age,  metabolism, and holistic health picture. Topol makes it clear that I am off base here. First, time  -- of day, of season, of life -- matters a lot: precision dosing entails understanding time-series  data in entirely new ways.  Second, precision medicine may likely begin not with pharmaceuticals but with diet. Recent  research on the role of gut flora and related participants in digestion helps explain why nutritional  research lacks any consistent consensus: meat was good, then bad, now it's sometimes good.  Butter was normal, then evil, but now it's not nearly as bad as margarine. Sugar was portrayed as  benign (so was cigarette smoking, for the same reasons), but now the "a calorie is just a calorie"  fiction is being exposed. One reason that dietary advice is so unreliable is that the degree of  uniqueness in our digestion and metabolization patterns is only now coming into focus. A key factor in that biomedical research into the gut biome and related processes is a massive  increase in the size of the data sets being researched. Much as with Facebook photos or Google  searches, machine learning algorithms need enormous volumes of training data to become reliable.  If for no other reason, Topol's book is valuable for chapter 11, where he explains the rapidly  changing literature of diet and digestion research. One point is made quite emphatically in the book, though I don't recall the author saying so directly.  Given the vast number of AI-infused startups for medical applications, we are nowhere remotely  close to general AI: every company he discusses, some of them in depth and/or with great  enthusiasm, is a point solution. Diabetes-related readings are the specialty of one company, while  mammograms are graded somewhere else, and retinopathy is diagnosed somewhere else. In short,  AI will not replace doctors anytime soon. This is not to say, however, that physicians' jobs won't change. Certain tasks -- image recognition  in particular -- are done quite capably by machines. Note, however, that image recognition is not  disease diagnosis (aided by up-to-date knowledge of a vast literature), treatment planning, end-of- life counseling, arguing with insurance companies, or any of the dozens of other things doctors are  called upon to do. The challenge ahead will be to team doctors and computers in the most effective  possible proportions, letting each contributor provide inputs that will lead to the whole patient  experience amounting to more than the sum of its parts. Topol also provides useful context for the role of AI in employment: there are plenty of subspecialties  in the US that are far understaffed, and globally, many nations have staggeringly few doctors. AI  provides the quite realistic possibility, in dermatology care for example, of enhancing family doctors  and nurse practitioners as they address one condition among many they see in a routine workweek.  Up-skilling generalists is entirely different from threatening the livelihoods of the relatively small  number of specialists called upon to address the major issue of deadly melanomas in the U.S.  and elsewhere.  Compared to a Watson-like digestion of medical research (something that seems plausible, if not  yet realized), for machine learning algorithms to read patient records remains a daunting task. Even  with electronic medical records, the lack of standardization in people's lives, descriptions of their  symptoms, health professionals' acuity in observation and notation, interoperability between  institutions (despite potentially using the same software package), and, again, the time of  observation means that mining EMRs is for practical purposes impossible for the foreseeable  future. In the meantime, EMRs are linked to physician burnout and decreased patient satisfaction  -- doctors navigating screens and typing with their backs to the patient in the exam room are  hugely troublesome for all concerned. Speech recognition powered by machine learning could  help alleviate this issue, and Topol ends the book by imagining a "super-Siri" personal health  assistant that helps each of us live our best life, medically speaking, through an advanced form  of what the military calls data fusion. For all the many drawbacks of current EMRs and other technologies, however, it's time to  address the elephant in the room: managed care. To the extent that my genomic, diagnostic,  behavioral, and other data becomes a tool for prediction of my health (and by extension, the  cost to maintain it), there will be a fundamental conflict of interest between me and my insurer.  Topol nods at this issue but never engages it (he is, however, a consultant to some of those  insurers). As the old saying goes, "follow the money," so my conviction is that the initial large- scale deployments of AI in health care will not be to reduce diabetic retinitis or arthrofibrosis,  but rather in a reimbursement arms race between insurers and providers. It's entirely possibly  that both Aetna and a health network will have deployed IBM Watson systems as the two  parties dispute a billed transaction, so we may see algorithms at war with themselves. It seems far fetched, but perhaps the EMR + AI convergence will be the beginning of the end  of the U.S.'s unique model of health care, in which more is spent per patient than anywhere  in the world while most major outcomes rank well down the list. That is, the fundamental conflict  of interest noted above will lead to such complex statutes, regulations, and/or case law that the  current U.S. arrangements become unsustainable. Already far too much effort is expended in  paperwork that does nothing for patient care, and the implications of predictive algorithm-driven  medicine for privacy, doctor-patient confidentiality, and ethics make HIPAA look positively  antiquated and inadequate.  If Topol can envision a new "virtual medical coach," perhaps the American Medical Association  can help construct a 21st-century alternative to its previous objections to single-payer health  care. Such a design for medicine would acknowledge the new roles of genomic science, data  analytics, robotics, and machine learning, along with addressing end-of-life, opioid, and other  political hot-button issues. I'm not convinced AI can give physicians time and tools to become  "human again" (beware anyone selling a golden age fallacy), but medicine absolutely needs  to become individualized, beginning from a data foundation, for the first time.