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Sunday, December 25, 2016

The Great A.I. Awakening? Health care implications?

From a very interesting long read at the NY Times:

...A machine can already detect tumors in medical scans better than human radiologists, but the machine can’t tell you what’s causing the cancer.
Then again, can the radiologist?

Medical diagnosis is one field most immediately, and perhaps unpredictably, threatened by machine learning. Radiologists are extensively trained and extremely well paid, and we think of their skill as one of professional insight — the highest register of thought. In the past year alone, researchers have shown not only that neural networks can find tumors in medical images much earlier than their human counterparts but also that machines can even make such diagnoses from the texts of pathology reports. What radiologists do turns out to be something much closer to predictive pattern-matching than logical analysis. They’re not telling you what caused the cancer; they’re just telling you it’s there.

Once you’ve built a robust pattern-matching apparatus for one purpose, it can be tweaked in the service of others. One Translate engineer took a network he put together to judge artwork and used it to drive an autonomous radio-controlled car. A network built to recognize a cat can be turned around and trained on CT scans — and on infinitely more examples than even the best doctor could ever review. A neural network built to translate could work through millions of pages of documents of legal discovery in the tiniest fraction of the time it would take the most expensively credentialed lawyer. The kinds of jobs taken by automatons will no longer be just repetitive tasks that were once — unfairly, it ought to be emphasized — associated with the supposed lower intelligence of the uneducated classes. We’re not only talking about three and a half million truck drivers who may soon lack careers. We’re talking about inventory managers, economists, financial advisers, real estate agents. What Brain did over nine months is just one example of how quickly a small group at a large company can automate a task nobody ever would have associated with machines.

The most important thing happening in Silicon Valley right now is not disruption. Rather, it’s institution-building — and the consolidation of power — on a scale and at a pace that are both probably unprecedented in human history...

But even enormous institutions like Google will be subject to this wave of automation; once machines can learn from human speech, even the comfortable job of the programmer is threatened...
I've had a good recurrent run here at "AI" issues. e.g., see "What might Artificial Intelligence bring to humanity?"

See also my 2013 NYeC Conference coverage "Smiling Almighty Jesus" riff going to "interoperability" issues. Gonna have to re-run that experiment now in light of the reported Google Translate improvement. Stay tuned. One has to wonder: might this level of cutting-edge intellectual and technical effort (Google Brain) bear actual transformative fruit in the health IT space (e.g., "interoperability"), relative to all of this incremental API ankle biting of recent years? Seeing the potential health data transparency and fluidity connection requires close study of the Lewis-Kraus article.


From FoxBusiness "Predictions for 2017,"
Theranos will shut its doors. The lawsuits are piling up and that will drain the coffers of the embattled lab test technology startup. CEO Elizabeth Holmes will finally be forced to seek bankruptcy protection and fade into obscurity, at least until the movie Bad Blood comes out, starring Jennifer Lawrence as the troubled entrepreneur. 
How does one go from an estimated personal net worth of $4.5 billion to zero in the space of a year or two? Lordy. See "Theranos had an awful year, and it only has itself to blame."


From The New Yorker.
Through DNA editing, researchers hope to alter the genetic destiny of species and eliminate diseases.
By Michael Specter
A long read (may be paywalled; I'm a subscriber). Well worth your time. apropos of a trio of books I will soon be reviewing.

The arc of existence from the Big Bang to our worrisome Anthropocene. Advances in health IT functionality (including UX) may not mean diddley if we fail to attend to much larger existential issues.
"We have engineered the world around us since the beginning of humanity. The real question is not whether we will continue to alter nature for our purposes but how we will do so. Using a mixture of breeding techniques, we have transformed crops, created countless breeds of animals, and converted millions of wooded acres into farmland. Gene drives are different; one insect could affect the future of our species. But it is a difference of power, not of kind." - Michael Specter
 "Engineered traits fail in the wild. But what if we could change that?"

More to come...

Wednesday, December 21, 2016

And a Merry locus coeruleus Neuroergonomics Technology to All

Got this twitter Follow (to which I reciprocated) and subseqent DM.

 "...combines neuroscience and music...It's scientifically proven..."
Well, hey, who doesn't like music? This old, ailing, washed-up guitar player certainly does.

Oh, boy. "Scientifically proven." Bullshit Detector Yellow Alert, anyone? Recall this from one of my prior posts?

My repeated attempts to contact Mr. I-Build-Better-Brains guy Jim Kwik were to no avail.

Focus@Will has a nice YouTube presence.

Pretty slick video ad. Nicely done.

 [@01:00] "We have scientifically curated a new, vast library of proprietary music that quickly focuses your attention, reduces your distraction, increases your productivity, and keeps you in the zone."

Those are some pretty bold, unequivocal claims. I will run this stuff past Drs. Adam Gazzaley and Larry Rosen for reactions. See my recent post "Clinical workflow, clinical cognition, and The Distracted Mind."

In fairness to the Focus@Will peeps, they at least proffer some referential science documentation on their site.


Our senses are constantly inundated with information: the light streaming in the windows, the sight of people passing by on the street, the smells of a cafe, the sounds of conversations and dogs barking over the din of city traffic, the light scrape of a scarf around your neck, the pressure of the hardwood table on your elbows. Each time you notice something in your environment, you are paying attention to it. The ability to focus your attention on something while ignoring competing stimuli is called selective attention by psychologists, and we would never get anything done without it.

Selective attention has been likened to a spotlight that you focus on something, and like a spotlight, the beam can be wide or narrow. Right now, your spotlight is focused on this article, which means that it is probably rather narrow. Other aspects of your environment fade into the background in relation to what is in your attentional spotlight. That is, until something distracting happens in your environment, and refocuses your spotlight.

The question many people want answered is how they can maximize focus so that their environment becomes less distracting and their attentional spotlight is continuously focused on their projects of the day. Auditory neuroscience and psychoacoustics (the psychology of sound perception) can help us answer this question...

[T]he trick is occupying your brain just enough to let you work, but feeding your brain novel stimuli at just the right times so that you don’t try to seek novelty by distracting yourself. It turns out listening to music while you work can do the trick [26]. Of course, some music is better than others: music that has emotional or sentimental overtones is likely to stimulate your emotional and memory processing, and music that is too fast, variable, or loud will jar your locus coeruleus back into action [10, 12]. In support of the idea that the pitfalls of distraction and habituation need to be straddled for music to be helpful during work, Huang and Shih (2011) found that when choosing music for a workplace, it is best to use music that workers neither like nor dislike [13]. In 2012, the same researchers concluded that music with lyrics is distracting to workers when compared to instrumental music [14]. Cognitive load theory dictates that if a person is attending to a task like reading or writing, which depend on both the visual and auditory cortices, processing power will not be sufficient to ignore distractions in one of the modalities, like speech.

We believe focus@will works by keeping your brain at the right focus level at least in part by increasing beta and theta brainwave activity. Increases in beta waves have been tied to sustained focus and attentional control, and biofeedback technology that specifically increases beta waves has been successfully used to treat attention disorders [35]. Theta waves, in some situations, are also related to task focus (for example, [36]). We have found that when focus@will audio tracks are played during reading, both beta and theta activity are increased, relative to plain music, in areas of the brain related to task focus and preparedness (see our study).

We hear from our users that we help them reach a psychological state of decreased self-awareness, timelessness, and motivation known as “flow”. Songwriters, musicians, writers, athletes, and meditators separately describe similar experiences of flow [15]. We are preparing a series of experiments to examine this flow state in correlation with focus@will music, and we will post results here as soon as they are available...
I'm no neuroscientist, and notwithstanding that the foregoing short piece on their site (which I screen-scraped off and printed and read) comes with four pages of sciencey-looking citations, I still have questions. "We hear from our users" doesn't count (the plural of "anecdote" is not "data"). Methodologically fastidious pre-and-post "productivity testing" of them under controlled conditions would. Given that their DM cites "over 1 million users," seems like there's an ample available stratified sampling base via which to do so. A few questions:
Is this technology deployed via personal earphones/"buds" ("personalized") or piped in via office sound systems (the equivalent of "Muzak")?
What about peoples' potentially confounding personal music tastes (not to mention the potential transient variability in such preferences)?
Relatedly, demographic "stratification" -- age, gender, race/ethnicity, socioeconomic status, education level, field of employment, level of music instrument/vocal competency (e.g., music is inescapably "distracting" to someone with my background)?
"Productivity?" Relevant quantifiable metrics via which to [1] establish baselines, and [2] determine "significant" improvements? Is productivity assessed at the employee level, or aggregated/rolled up to the "team"/department/line functional level?
Bears further study. BTW, they provide another page of voluminous links: PUBLISHED LITERATURE ON MUSIC FOR CONCENTRATION AND FOCUS. While some of that may be "gilding the lily" (relevant quality and applicability matter, not nominally soothing quantity of cites), still, apparently no Jim Kwik reeking-of-BS all-Sizzle "infotainment" woo operation here.
Another head-scratch. Given that they tout that they've "scientifically curated a new, vast library of proprietary music," they might necessarily have a bit of a "Theranos opacity" problem, in not wanting to reveal the "secret sauce" comprising their "proprietary" methodology. Fine. I once worked as the Technical Editor for a digital industrial dignostics company that manufactured and marketed portable (and equally proprietary) digital FFT analyzers in the heavy industrial market (pdf, see here as well). We too had customer "testimonials" -- e.g., one happy client voluntarily reported an ROI of 17:1 after just one year of deployment of our technology. We had a number of those, with RIOs of 10:1 or better (in fairness, it was in part a "low-hanging fruit" phenomenon; they'd had no idea how much money they'd been wasting prior to adopting our tools). Focus@Will could come up with similar quantifiable and verifiable "we hear from our users" (properly their management) ROI testimonies. After all, what's being sold here is significantly improved net "productivity."

Amiable guy, that's for sure. Calls himself a "scientist." See his Sheet. Under "Education" he lists "Singularity University 2011-2011," and "the University of know the School of Hard knocks."


I might run this stuff past my former bass player (late 1970's), now Dr. Scott Lipscomb, (MA, and PhD, Systematic Musicology, UCLA). Underachiever Scott is now Associate Dean for Academic Affairs and Director of Graduate Studies at University of Cincinnati's College Conservatory of Music.


Scott responded.
You were absolutely correct to pay attention when your "BS alert" sounded ... whenever phrases like so *many* quoted in your post are used to represent (supposedly) scientific evidence for a commercially available product, it is critically important to be skeptical. In my view, without having any "inside" information about this product, it fails almost every test. What truly gives it away for me is the statement "We believe focus@will works because ...". That is a dead giveaway that they really have no frigging idea what is going on. I am not interested in "belief" (at all) ... what I want to know is what the evidence reveals about the efficacy of the product. The research citations in the blurb provided here hardly provide the kind of clear results that would alleviate my own skepticism.

While I do not consider myself a neuroscientist, I have presented collaboratively several presentations and posters (with real, living neuroscientists!) at scientific conferences that utilized brain imaging techniques (fMRI & MEG) to determine brain function when attending to music and/or visual images (e.g., motion picture excerpts and other forms of multimedia) ... in fact, my real interest in how the presence of sound (in general) or music (specifically) impacts the audience experience. My primary area of research - which has been carried out at The U of Texas at San Antonino (1995-2001); Northwestern University (2001-2006), the University of Minnesota (2006-2016), and the University of Cincinnati (2016-present) - is music perception & cognition. You can use this information to determine the extent to which you should be skeptical of my own response. ;)

Scott D Lipscomb, Ph.D. (that referenced bassist from the 70s)
Associate Dean, College-Conservatory of Music
Professor, Electronic Media
University of Cincinnati

Random thoughts. Might this "scientifically curated, proprietary" productivity-enhancing music be viewed as a "PED" analogue (Performance Enhancing Drug)? If so, might there then emerge a free-rider bootleg Bit Torrent mp3 black market for it? Were it incorporated in "mixtape" fashion into other audio track assemblages, might there be a Monsanto GMO patented/copyrighted seed type "infringement" cause of action? Just some Christmas Eve Johnny Walker Green Label-induced random ruminations...


Speaking of Theranos, the gift that keeps on giving. From Wired:

Theranos: Kinda Sounds Like a God, But Most Certainly Isn’t

No slow-motion-train wreck science story was more riveting this year than the implosion of Theranos, once the darling of the biomedical world. It promised accurate blood tests using just a drop of blood, which didn’t turn out to be strictly speaking “true.” So came the fraud investigations. The lawsuits. The inevitable pivot (a Silicon Valley word meaning “wow what we had in mind at first definitely isn’t a thing”). So where’s Theranos headed in 2017? Eh, probably not super great places, if we’re being real.
Coming soon, my take on Theranos' (misnomer) "QA data."

OK, speaking of music, how about a bit of Holiday music, in the spirit of the Season? 

If the embedded audio player doesn't appear or work, here's a direct link to the mp3 file.

I am half-owner in this project, which was produced by my Las Vegas friends Dave Richardson and Lenny Lopez of the amazing Santa Fe Band, comprised of 15 of Vegas's top casino show musicians (I used to do their photography and ran a blog for them). The Christmas CD, originally released in late 2001, had gone out of print, and I paid to have it re-published, re-doing the artwork myself and setting up a PayPal eCommerce page). I've since taken it offline, having made my money back and then some (most of my latter sales were starting to come from the EU, and the postage and customs documentation hassles were killing me). I have just a couple of boxes of CDs left out in the garage. I give them away to selected people.
The "Little Drummer Boy" rendition is interesting. Lenny told me that when it was first released, they got a lot of angry complaints from customers over the "offensive" Arabic-ish harmonic minor scale-transient-major 3rd-dissonance scat singing (which they'd deliberately put in for historical "religious syncretism" effect). Some people wanted to return the CD and get a refund.
Not kidding. Fifteen years later, widespread anti "Arab/Muslim" sentiments remain, 'eh?
Erratum: Lenny is my tightest of buds (my "brother from another mother"). He did the harmony vocals on my goofy "ObamaCare Free Riders" YouTube music video. Triple-tracked that stuff in all of 30 minutes on my iMac in my study. Dude is a musical genius.
A Merry locus coeruleus Neuroergonomics Technology to All

More to come...

Tuesday, December 20, 2016

Project Zygote shout-out

A very interesting initiative,

"Many early stage founders and technologists with healthcare ideas want to contribute to the field’s disruptive innovation but lack domain expertise.

"Likewise, many healthcare providers want to enter into the digital health field but lack the technology know-how make the shift.

"Project Zygote brings these two groups together, plus go-to-market professionals, to form teams that develop, vet, and validate new digital health solutions.

"As an idea conceived and run by members of the Health 2.0 San Francisco Chapter, we are leveraging local talent to ensure the next wave of digital health products holistically solve meaningful healthcare problems.  Our goal is to broker relationships, educate participants, and vet new concepts.  Ultimately, we nurture teams to the point where they are ready to credibly approach healthcare accelerators and investors to take flight."

I just reached out to the Health 2.0 SF group, and a link to the above stuff quickly showed in in my LinkedIn email feed. I'll be watching and reporting on developments with great interest.

apropos of the foregoing:
What Is Causing Startups to Go Bankrupt?
Shellye Archambeau
December 20th, 2016

Many startups have a great product that’s viable, marketable, and ripe with potential. But if that was the only indicator of success, then nine out of 10 startups wouldn’t fail. The annals of startup history wouldn’t be littered with instances of companies like Friendster or Color that had fantastic products, but eventually sank.

The truth is that startups often go bankrupt for reasons that extend beyond the viability of their products. Many of them fall prey to missteps that ultimately dry up their cash flow, and cause the company to fold. So what are some of these pitfalls to avoid?...
Good article. I would also commend to you again my citation of Steve Tobak's highly relevant new book, cited in a recent post.

...Given all the hype, we should be seeing the mother of all business creation movements, but we’re not. What we are seeing is a massive long-term decline in new startups and small businesses across all demographics and geographies. We’ll get into this in more detail later, but for now, suffice to say that new business creation has dropped a whopping 28 percent from 1977 to 2011, according to U.S. Census Bureau data. The greatest irony of all is that the steepest declines are coming from those aged 20 to 34, who created just 22 percent of all new companies in 2013, down from 34 percent in 1996. That’s right. The entrepreneurial generation is nothing of the kind. It’s just a media fabrication. (Not to mention that unemployment and underemployment rates among Millennials are almost twice that of the general population.) 

With new business creation and workforce participation rates at multidecade lows across the board— especially among young people— the truth is inescapable: Instead of enabling and empowering a new generation of successful innovators and business leaders, this mythical movement and all the virtual content it generates is leading countless would-be entrepreneurs down a utopian path toward a dream that simply doesn’t exist. 

Why all the gloom and doom? For starters, you can’t fix a problem until you identify it...
Nobody ever changed the world by doing what everyone else is doing. That’s not just common sense— it’s biology. Species evolve when beneficial genetic mutations arise out of competitive ecosystems and take over. Likewise, civilization advances when unique individuals who think and act differently shatter the status quo and forever change how we do things. Leaders lead. Followers follow. You can’t be both. Real leaders don’t follow, and neither do real entrepreneurs...

Tobak, Steve (2015-10-19). Real Leaders Don't Follow: Being Extraordinary in the Age of the Entrepreneur (Kindle Locations 550-575). Entrepreneur Press. Kindle Edition.
I'd like to see Steve present to Project Zygote participants. Really enjoyed and learned from his book. He should also be on a WinterTech Panel.

Also pertinent, my Sept. 2015 post, What exactly is "Leadership," anyway? And, go all the way back to 2012 and my thoughts on "Effectuation."

Then there's my April 2016 post On Disruption: "OMG! Awesome!! Dan Lyons for President!!!

More to come...

Sunday, December 18, 2016

A quick note of thanks to KHIT readers

Earlier this month I thought that perhaps this blog would get to 600,000 hits by the end of December. Launched my MacAir this morning at 9:02 when I got up. Lordy.

My traffic has been on a significant upspike for the past 2 weeks or so. Not sure as to the cause(s), but I am grateful for you readers. The recent accelerated traffic spurt looks to have begun with my post about Trump HHS Secretary nominee Tom Price (committed ObamaCare, Medicare, and women's reproductive rights foe), then on to my latest on the continuing woes of Theranos (regarding which there will be more shortly; their sorry QA data deserve an entire post), followed by my post about the fabulous new Michael Lewis book The Undoing Project on the lives and important work of Daniel Kahneman and Amos Tversky, and finally my most recent post on the Donald Trump-Silicon Valley CEO Trump Tower "Summit."

All I can say is a "sincere thanks" for continuing to stop by. I'll keep at it. I don't do this for money; I just continue to do it because it's important -- no sponsors or other "monetization." The overlapping topics of Health IT (including coding/database platforms, mHealth, UX, HIE, and hardy perennial misnomer "interoperability"), Biomed Tech, health care delivery and economics, "upstream" issues (apropos of "population health"), workflow, organizational culture, leadership, startups and venture capital, intellectual property, privacy and security, clinical cognition, clinical pedagogy, clinical science, genomics, analytics, policy and law...

No shortage of relevant subject matter and contentious issues.


I will again be there. Register here.

Below, the next day (January 12th), the NorCal HIMSS Chapter is hosting a one-day event in Santa Clara.

From the email I got:
Come hear leading innovation physicians and national clinical HIT innovation experts offer forward leaning perspectives that include:
  • Innovation thinking from outside healthcare to transform personalized health and patient engagement through digital, mobile and the cloud.
  • Genomic and IOT - behavioral, clinical and genetic data capture/analysis - Intel's "inside-out model."
  • How formal collaboration optimizes "inside-out" commercialization, research and tech transfer, and venture fund approaches to bringing ideas to fruition and fertile markets.
  • Generating actionable insights and speeding innovation by continually looking at new and better ways to manage data
  • Understand how machine learning can be woven into existing population health and personalized care business intelligence and analytics efforts.
Who should attend: C-Level, Physicians, Nursing Informaticists, IT professionals, health innovation leadership, venture capitalists, entrepreneurs, startups and anyone involved with and passionate about improving the delivery of care.
I asked for a press pass. I don't think they're gonna grant me one. Got an equivocal response (after having to bypass their broken "event organizer contact" template on the conference pitch page), asking how much I would do to promote the event in advance (just a tad late, 'eh?), but never answering my media pass question.

Maybe my timing was unfortunate, in light of my snarky, tangentially "off-topic" prior post.

Pretty sleepy over at the NorCalHIMSS TwitterVerse. Last tweet was about 10 months ago?

Whatever. There's lots else to do. Just FYI anyway, in case you might want to attend.



Below, duh: it occurs to me that I have long been remiss, and need to join the Health 2.0 San Francisco Chapter and contribute.

I just put a permanent link in the right hand links column.

More to come...

Wednesday, December 14, 2016

His Serene Highness Trumplethinskin Summons Silicon Valley Technocracy Titans to Trump Tower

Props to Recode wag Kara Swisher for the "Trumplethinskin" moniker heads-up.

The Trump Tower High Tech Summit, December 14th, 2016. Summonees:
Founders Fund partner Peter Thiel
Oracle CEO Safra Catz

Amazon CEO Jeff Bezos

Apple CEO Tim Cook

Intel CEO Brian Krzanich

Google co-founder Larry Page

Former Google CEO and executive chairman of Alphabet Inc. Eric Schmidt

Cisco CEO Chuck Robbins

IBM CEO Ginni Rommety

Facebook’s chief operating officer Sheryl Sandberg

Tesla CEO Elon Musk

Microsoft CEO Satya Nadell
Palantir CEO Alex Karp
The combined Google search net worth estimate of the foregoing Summonees is roughly $72 billion. Wonder what the #BiglyFakeBillionaire thinks about that? Probably thoroughly enjoying Lording over them.
“I’m here to help you folks do well,” Mr. Trump told 13 tech executives, seated with about a dozen Trump team and family members around a large rectangular table.
Okee-Dokee, then. News to me that they've not been doing well of late.

Not attending, Uber CEO Travis Kalanick (net worth $6 billion). Notably not invited? Twitter CEO Jack Dorsey (net worth $2.2B). LOL. From the L.A. Times:
...Trump’s favorite social media platform, Twitter, was absent, for example. Politico attributed it to retribution for the company refusing during the campaign to abide Trump’s request to generate a #CrookedHillary emoji.

Twitter’s refusal to create a digital running stick figure holding a money bag is a grievance that his director of digital advertising aired on Medium a few weeks ago.

Trump representatives denied that was why Twitter was left out of the high-tech confab. They said Twitter didn’t make the cut because it wasn’t a big enough company. It has a market capitalization of about $13.8 billion, less than half that of Tesla, which was included in the meeting.

 Trump himself boasted at the top of the meeting about the deluge of requests to attend.

“I won't tell you the hundreds of calls we've had, asking to come to this meeting,” Trump said. He looked to Pay Pal co-founder Peter Thiel, an eccentric billionaire who was among the lone tech giants to back Trump’s campaign — and who now is seen by many tech executives as a potential lifeline in the new administration — as he sent out invitations.

“Peter would sort of say, ‘You know, that company's too small.’”

Those executives that did make the cut, Trump declared, led “monster companies.” They included Tim Cook of Apple, Jeff Bezos of Amazon, Elon Musk of Tesla, Sheryl Sandberg of Facebook, and Larry Page and Eric Schmidt of Google’s parent company, Alphabet.

“I'm here to help you folks do well,” Trump said, before taking credit for the bump in the stock market that followed his election. “And you're doing well right now and I'm very honored by the bounce. They're all talking about the bounce. So right now everybody in this room has to like me — at least a little bit.”

It was the get-along side of Trump on full display. The meeting was to be a symbol of an administration that would not hew to ideology but the best ideas.

Trump’s representatives spent the hours leading up to the meeting talking to the press about how good Trump is at listening, even to the people who despise him.

Plenty of folks back in Silicon Valley weren’t buying it. The executives who flew to New York found themselves confronted with letters, petitions and public scoldings from colleagues who reminded them that Trump has yet to disavow any parts of his agenda that most appalled Silicon Valley during the election.

“Now, more than ever, tech leaders must stand up for human dignity, and examine their role in public discourse,” EBay founder Pierre Omidyar wrote as he retweeted an article that pilloried tech leaders for going to Trump Tower...
Trump support among top digerati execs begins and ends with the name Peter Thiel. I doubt much of substance will come from this Technocracy Celebrity Apprentice photo-op. Beyond nil federal regulation in general, Silicon Valley wants the continuation of unfettered outsourcing of manufacturing (principally to China), ongoing "insourcing" of high tech (H-1B visa) immigrant talent, and the sheltering of profits overseas. Trump nominally opposes all of that (though he's voiced the usual platitudes about summarily and unilaterally striking down regulations), but it's hard to divine exactly what he truly believes or will try to act upon as Presidential priorities.

This was interesting, too:
The Royal Family.

Speaking of tech (and the future of employment), just in my inbox from The New Yorker:

How long will it be before you lose your job to a robot?

by Elizabeth Kolbert

...How long will it be before you, too, lose your job to a computer? This question is taken up by a number of recent books, with titles that read like variations on a theme: “The Industries of the Future,” “The Future of the Professions,” “Inventing the Future.” Although the authors of these works are employed in disparate fields—law, finance, political theory—they arrive at more or less the same conclusion. How long? Not long.

“Could another person learn to do your job by studying a detailed record of everything you’ve done in the past?” Martin Ford, a software developer, asks early on in “Rise of the Robots: Technology and the Threat of a Jobless Future” (Basic Books). “Or could someone become proficient by repeating the tasks you’ve already completed, in the way that a student might take practice tests to prepare for an exam? If so, then there’s a good chance that an algorithm may someday be able to learn to do much, or all, of your job.”

Later, Ford notes, “A computer doesn’t need to replicate the entire spectrum of your intellectual capability in order to displace you from your job; it only needs to do the specific things you are paid to do.” He cites a 2013 study by researchers at Oxford, which concluded that nearly half of all occupations in the United States are “potentially automatable,” perhaps within “a decade or two.” (“Even the work of software engineers may soon largely be computerisable,” the study observed.)...

Imagine a matrix with two axes, manual versus cognitive and routine versus nonroutine. Jobs can then be arranged into four boxes: manual routine, manual nonroutine, and so on. (Two of Brynjolfsson and McAfee’s colleagues at M.I.T., Daron Acemoglu and David Autor, performed a formal version of this analysis in 2010.) Jobs on an assembly line fall into the manual-routine box, jobs in home health care into the manual-nonroutine box. Keeping track of inventory is in the cognitive-routine box; dreaming up an ad campaign is cognitive nonroutine.

The highest-paid jobs are clustered in the last box; managing a hedge fund, litigating a bankruptcy, and producing a TV show are all cognitive and nonroutine. Manual, nonroutine jobs, meanwhile, tend to be among the lowest paid—emptying bedpans, bussing tables, cleaning hotel rooms (and folding towels). Routine jobs on the factory floor or in payroll or accounting departments tend to fall in between. And it’s these middle-class jobs that robots have the easiest time laying their grippers on.

During the recent Presidential campaign, much was said—most of it critical—about trade deals like the North American Free Trade Agreement and the Trans-Pacific Partnership. The argument, made by both Bernie Sanders and Donald Trump, was that these deals have shafted middle-class workers by encouraging companies to move jobs to countries like China and Mexico, where wages are lower. Trump has vowed to renegotiate nafta and to withdraw from the T.P.P., and has threatened to slap tariffs on goods manufactured by American companies overseas. “Under a Trump Presidency, the American worker will finally have a President who will protect them and fight for them,” he has declared.

According to Brynjolfsson and McAfee, such talk misses the point: trying to save jobs by tearing up trade deals is like applying leeches to a head wound. Industries in China are being automated just as fast as, if not faster than, those in the U.S. Foxconn, the world’s largest contract-electronics company, which has become famous for its city-size factories and grim working conditions, plans to automate a third of its positions out of existence by 2020.The South China Morning Post recently reported that, thanks to a significant investment in robots, the company already has succeeded in reducing the workforce at its plant in Kunshan, near Shanghai, from a hundred and ten thousand people to fifty thousand. “More companies are likely to follow suit,” a Kunshan official told the newspaper.

“If you look at the types of tasks that have been offshored in the past twenty years, you see that they tend to be relatively routine,” Brynjolfsson and McAfee write. “These are precisely the tasks that are easiest to automate.” Off-shoring jobs, they argue, is often just a “way station” on the road to eliminating them entirely.

In “Rise of the Robots,” Ford takes this argument one step further. He notes that a “significant ‘reshoring’ trend” is now under way. Reshoring reduces transportation costs and cuts down on the time required to bring new designs to market. But it doesn’t do much for employment, because the operations that are moving back to the U.S. are largely automated. This is the major reason that there is a reshoring trend; salaries are no longer an issue once you get rid of the salaried. Ford cites the example of a factory in Gaffney, South Carolina, that produces 2.5 million pounds of cotton yarn a week with fewer than a hundred and fifty workers. A story about the Gaffney factory in the Times ran under the headline “u.s. textile plants return, with floors largely empty of people.”...

How much technology has contributed to the widening income gap in the U.S. is a matter of debate; some economists treat it as just one factor, others treat it as the determining factor. In either case, the trend line is ominous. Facebook is worth two hundred and seventy billion dollars and employs just thirteen thousand people. In 2014, Facebook acquired Whatsapp for twenty-two billion dollars. At that point, the messaging firm had a grand total of fifty-five employees. When a twenty-two-billion-dollar company can fit its entire workforce into a Greyhound bus, the concept of surplus labor would seem to have run its course. [emphasis mine - BG]

Ford worries that we are headed toward an era of “techno-feudalism.” He imagines a plutocracy shut away “in gated communities or in elite cities, perhaps guarded by autonomous military robots and drones.” Under the old feudalism, the peasants were exploited; under the new arrangement, they’ll merely be superfluous...
Yeah. I've had a good run at these AI/Robotics issues before. See, e.g., my recent post "What might Artificial Intelligence bring to humanity?" and the recursive links therein (pay particular attention to "Four Futures"). I've studied and cited many of the books mentioned in Elizabeth Kolbert's article, along with related others she did not reference.

Interesting how one thing leads to another. Reading more on Elizabeth Kolbert led me to her recent Pulitzer Prize-winning book, which I bought and have begun.

Doesn't nominally have anything to do with health care and health InfoTech, but it certainly goes to the fundamental "upstream" issue of human survival.
Beginnings, it’s said, are apt to be shadowy. So it is with this story, which starts with the emergence of a new species maybe two hundred thousand years ago. The species does not yet have a name— nothing does— but it has the capacity to name things. 

As with any young species, this one’s position is precarious. Its numbers are small, and its range restricted to a slice of eastern Africa. Slowly its population grows, but quite possibly then it contracts again— some would claim nearly fatally— to just a few thousand pairs. 

The members of the species are not particularly swift or strong or fertile. They are, however, singularly resourceful. Gradually they push into regions with different climates, different predators, and different prey. None of the usual constraints of habitat or geography seem to check them. They cross rivers, plateaus, mountain ranges. In coastal regions, they gather shellfish; farther inland, they hunt mammals. Everywhere they settle, they adapt and innovate. On reaching Europe, they encounter creatures very much like themselves, but stockier and probably brawnier, who have been living on the continent far longer. They interbreed with these creatures and then, by one means or another, kill them off. 

The end of this affair will turn out to be exemplary. As the species expands its range, it crosses paths with animals twice, ten, and even twenty times its size: huge cats, towering bears, turtles as big as elephants, sloths that stand fifteen feet tall. These species are more powerful and often fiercer. But they are slow to breed and are wiped out. 

Although a land animal, our species— ever inventive— crosses the sea. It reaches islands inhabited by evolution’s outliers: birds that lay foot-long eggs, pig-sized hippos, giant skinks. Accustomed to isolation, these creatures are ill-equipped to deal with the newcomers or their fellow travelers (mostly rats). Many of them, too, succumb. 

The process continues, in fits and starts, for thousands of years, until the species, no longer so new, has spread to practically every corner of the globe. At this point, several things happen more or less at once that allow Homo sapiens, as it has come to call itself, to reproduce at an unprecedented rate. In a single century the population doubles; then it doubles again, and then again. Vast forests are razed. Humans do this deliberately, in order to feed themselves. Less deliberately, they shift organisms from one continent to another, reassembling the biosphere.
Meanwhile, an even stranger and more radical transformation is under way. Having discovered subterranean reserves of energy, humans begin to change the composition of the atmosphere. This, in turn, alters the climate and the chemistry of the oceans. Some plants and animals adjust by moving. They climb mountains and migrate toward the poles. But a great many— at first hundreds, then thousands, and finally perhaps millions— find themselves marooned. Extinction rates soar, and the texture of life changes. No creature has ever altered life on the planet in this way before, and yet other, comparable events have occurred. Very, very occasionally in the distant past, the planet has undergone change so wrenching that the diversity of life has plummeted. Five of these ancient events were catastrophic enough that they’re put in their own category: the so-called Big Five. In what seems like a fantastic coincidence, but is probably no coincidence at all, the history of these events is recovered just as people come to realize that they are causing another one. When it is still too early to say whether it will reach the proportions of the Big Five, it becomes known as the Sixth Extinction...

Kolbert, Elizabeth (2014-02-11). The Sixth Extinction: An Unnatural History (pp. 1-3). Henry Holt and Co.. Kindle Edition.

On a brighter note, the Bald Eagle McNuggets one day soon to be available at the President Donald J. Trump® Yellowstone National Golf Resort and Spa are gonna be pretty yummie. And the Point Barrow Alaskan North Slope Pinot Noir will no doubt be delicious.

BTW: You might find my 2008 post "0.0143%" of interest.


Elizabeth Kolbert NPR interview.


More to come...

Sunday, December 11, 2016

Kahneman and Tversky: clinical judgment and decisionmaking

Acclaimed author Michael Lewis has hit another one out of the park. I recommend that you stop what you're doing ASAP and read it.

Lewis' biography of Daniel Kahneman and his collaborator the late Amos Tversky is simply a compelling, must-read. This odd couple of Israeli psychologists, two of the clearest thinkers of our times, changed the course of the psych discipline and founded the field now known as "behavioral economics."

Beyond Lewis's excellent lay-accessible translations of the core elements of the Kahneman-Tversky "Prospect Theory" (as it would come to be widely known), his riveting, poignant recounting the personal stories of the lives of these two unique men is itself worthy of some kind of literary award.

With regard to the technical specifics as they go to clinical cognition and decisionmaking, the book is a gold mine. Chapter 8 in particular.
8: Going Viral
The young woman they called him to examine that summer day was still in a state of shock. As Don Redelmeier understood it, her car had smashed head-on into another car a few hours earlier, and the ambulance had rushed her straight to Sunnybrook Hospital. She’d suffered broken bones everywhere— some of which they had detected and others, it later became clear, they had not. They’d found the multiple fractures in her ankles, feet, hips, and face. (They’d missed the fractures in her ribs.) But it was only after she arrived in the Sunnybrook operating room that they realized there was something wrong with her heart.

Sunnybrook was Canada’s first and largest regional trauma center, an eruption of red-brown bricks in a quiet Toronto suburb. It had started its life as a hospital for soldiers returning from the Second World War, but as the veterans died, its purpose shifted. In the 1960s the government finished building what would become at its widest a twenty-four-lane highway across Ontario. It would also become the most heavily used road in North America, and one of its busiest stretches passed close by the hospital. The carnage from Highway 401 gave the hospital a new life. Sunnybrook rapidly acquired a reputation for treating victims of automobile accidents; its ability to cope with one sort of medical trauma inevitably attracted other sorts of trauma. “Business begets business,” explained one of Sunnybrook’s administrators. By the turn of the twenty-first century, Sunnybrook was the go-to destination not only for victims of car crashes but for attempted suicides, wounded police officers, old people who had taken a fall, pregnant women with serious complications, construction workers who had been hurt on the job, and the survivors of gruesome snowmobile crashes— who were medevaced in with surprising frequency from the northern Canadian boondocks. Along with the trauma came complexity. A lot of the damaged people who turned up at Sunnybrook had more than one thing wrong with them. 

That’s where Redelmeier entered. By nature a generalist, and by training an internist, his job in the trauma center was, in part, to check the understanding of the specialists for mental errors. “It isn’t explicit but it’s acknowledged that he will serve as a check on other people’s thinking,” said Rob Fowler, an epidemiologist at Sunnybrook. “About how people do their thinking. He keeps people honest. The first time people interact with him they’ll be taken aback: Who the hell is this guy, and why is he giving me feedback? But he’s lovable, at least the second time you meet him.” That Sunnybrook’s doctors had come to appreciate the need for a person to serve as a check on their thinking, Redelmeier thought, was a sign of how much the profession had changed since he entered it in the mid-1980s. When he’d started out, doctors set themselves up as infallible experts; now there was a place in Canada’s leading regional trauma center for a connoisseur of medical error. A hospital was now viewed not just as a place to treat the unwell but also as a machine for coping with uncertainty. “Wherever there is uncertainty there has got to be judgment,” said Redelmeier, “and wherever there is judgment there is an opportunity for human fallibility.” 

Across North America, more people died every year as a result of preventable accidents in hospitals than died in car crashes— which was saying something. Bad things happened to patients, Redelmeier often pointed out, when they were moved without extreme care from one place in a hospital to another. Bad things happened when patients were treated by doctors and nurses who had forgotten to wash their hands. Bad things even happened to people when they pressed hospital elevator buttons. Redelmeier had actually co-written an article about that: “Elevator Buttons as Unrecognized Sources of Bacterial Colonization in Hospitals.” For one of his studies, he had swabbed 120 elevator buttons and 96 toilet seats at three big Toronto hospitals and produced evidence that the elevator buttons were far more likely to infect you with some disease. 

But of all the bad things that happened to people in hospitals, the one that most preoccupied Redelmeier was clinical misjudgment. Doctors and nurses were human, too. They sometimes failed to see that the information patients offered them was unreliable— for instance, patients often said that they were feeling better, and might indeed believe themselves to be improving, when they had experienced no real change in their condition. Doctors tended to pay attention mainly to what they were asked to pay attention to, and to miss some bigger picture. They sometimes failed to notice what they were not directly assigned to notice. “One of the things Don taught me was the value of observing the room when the patient isn’t there,” says Jon Zipursky, chief of residents at Sunnybrook. “Look at their meal tray. Did they eat? Did they pack for a long stay or a short one? Is the room messy or neat? Once we walked into the room and the patient was sleeping. I was about to wake him up and Don stops me and says, "There is a lot you can learn about people from just watching.” 

Doctors tended to see only what they were trained to see: That was another big reason bad things might happen to a patient inside a hospital. A patient received treatment for something that was obviously wrong with him, from a specialist oblivious to the possibility that some less obvious thing might also be wrong with him. The less obvious thing, on occasion, could kill a person. 

The conditions of people mangled on the 401 were often so dire that the most obvious things wrong with them demanded the complete attention of the medical staff, and immediate treatment. But the dazed young woman who arrived in the Sunnybrook emergency room directly from her head-on car crash, with her many broken bones, presented her surgeons, as they treated her, with a disturbing problem. The rhythm of her heartbeat had become wildly irregular. It was either skipping beats or adding extra beats; in any case, she had more than one thing seriously wrong with her. 

Immediately after the trauma center staff called Redelmeier to come to the operating room, they diagnosed the heart problem on their own— or thought they had. The young woman remained alert enough to tell them that she had a past history of an overactive thyroid. An overactive thyroid can cause an irregular heartbeat. And so, when Redelmeier arrived, the staff no longer needed him to investigate the source of the irregular heartbeat but to treat it. No one in the operating room would have batted an eye if Redelmeier had simply administered the drugs for hyperthyroidism. Instead, Redelmeier asked everyone to slow down. To wait. Just a moment. Just to check their thinking— and to make sure they were not trying to force the facts into an easy, coherent, but ultimately false story. 

Something bothered him. As he said later, “Hyperthyroidism is a classic cause of an irregular heart rhythm, but hyperthyroidism is an infrequent cause of an irregular heart rhythm.” Hearing that the young woman had a history of excess thyroid hormone production, the emergency room medical staff had leaped, with seeming reason, to the assumption that her overactive thyroid had caused the dangerous beating of her heart. They hadn’t bothered to consider statistically far more likely causes of an irregular heartbeat. In Redelmeier’s experience, doctors did not think statistically. “Eighty percent of doctors don’t think probabilities apply to their patients,” he said. “Just like 95 percent of married couples don’t believe the 50 percent divorce rate applies to them, and 95 percent of drunk drivers don’t think the statistics that show that you are more likely to be killed if you are driving drunk than if you are driving sober applies to them.” 

Redelmeier asked the emergency room staff to search for other, more statistically likely causes of the woman’s irregular heartbeat. That’s when they found her collapsed lung. Like her fractured ribs, her collapsed lung had failed to turn up on the X-ray. Unlike the fractured ribs, it could kill her. Redelmeier ignored the thyroid and treated the collapsed lung. The young woman’s heartbeat returned to normal. The next day, her formal thyroid tests came back: Her thyroid hormone production was perfectly normal. Her thyroid never had been the issue. “It was a classic case of the representativeness heuristic,” said Redelmeier. “You need to be so careful when there is one simple diagnosis that instantly pops into your mind that beautifully explains everything all at once. That’s when you need to stop and check your thinking.”
It wasn’t that what first came to mind was always wrong; it was that its existence in your mind led you to feel more certain than you should be that it was correct. “Beware of the delirious guy in the emergency unit with the long history of alcoholism,” said Redelmeier, “because you will say, ‘He’s just drunk,’ and you’ll miss the subdural hematoma.” The woman’s surgeons had leapt from her medical history to a diagnosis without considering the base rates. As Kahneman and Tversky long ago had pointed out, a person who is making a prediction— or a diagnosis— is allowed to ignore base rates only if he is completely certain he is correct. Inside a hospital, or really anyplace else, Redelmeier was never completely certain about anything, and he didn’t see why anybody else should be, either...

Lewis, Michael (2016-12-06). The Undoing Project: A Friendship That Changed Our Minds (Kindle Locations 2821-2890). W. W. Norton & Company. Kindle Edition.
That's just the opening stanza. Chapter 8 is a tour de force. Just a taste more:
Redelmeier had grown up in Toronto, in the same house in which his stockbroker father had been raised. The youngest of three boys, he often felt a little stupid; his older brothers always seemed to know more than he did and were keen to let him know it. Redelmeier also had a speech impediment— a maddening stammer he would never cease to work hard, and painfully, to compensate for. (When he called for restaurant reservations, he just told them his name was “Don Red.”) His stammer slowed him down when he spoke; his weakness as a speller slowed him down when he wrote. His body was not terribly well coordinated, and by the fifth grade he required glasses to correct his eyesight. His two great strengths were his mind and his temperament. He was always extremely good at math; he loved math. He could explain it, too, and other kids came to him when they couldn’t understand what the teacher had said. That is where his temperament entered. He was almost peculiarly considerate of others. From the time he was a small child, grown-ups had noticed that about him: His first instinct upon meeting someone else was to take care of the person. 

Still, even from math class, where he often wound up helping all the other students, what he took away was a sense of his own fallibility. In math there was a right answer and a wrong answer, and you couldn’t fudge it. “And the errors are sometimes predictable,” he said. “You see them coming a mile away and you still make them.” His experience of life as an error-filled sequence of events, he later thought, might be what had made him so receptive to an obscure article, in the journal Science, that his favorite high school teacher, Mr. Fleming, had given him to read in late 1977. He took the article home with him and read it that night at his desk. 

The article was called “Judgment Under Uncertainty: Heuristics and Biases.” It was in equal parts familiar and strange— what the hell was a “heuristic”? Redelmeier was seventeen years old, and some of the jargon was beyond him. But the article described three ways in which people made judgments when they didn’t know the answer for sure. The names the authors had given these— representativeness, availability, anchoring— were at once weird and seductive. They made the phenomenon they described feel like secret knowledge. And yet what they were saying struck Redelmeier as the simple truth— mainly because he was fooled by the questions they put to the reader... [ibid, Kindle Locations 2891-2908].
I first got onto "Judgement Under Uncertainty" more than a quarter century ago. My hardcopy of the book, along with the subsequent Kahneman-Tversky "Choices, Values, and Frames," sits right here on the bookshelf above my iMac in my office.

If you want to go down deep in the scholarly/technical weeds, see their 1979 paper "Prospect Theory: An analysis of Decision under Risk" (pdf).

Also recommended. Daniel Kahneman's acclaimed recent solo book "Thinking, Fast and Slow."

BTW, apropos of current U.S. political events, I found this little passage in "The Undoing Project" of relevance:
In late 1973 or early 1974, [Daniel Kahneman] gave a talk, which he would deliver more than once, and which he called “Cognitive Limitations and Public Decision Making.” It was troubling to consider, he began, “an organism equipped with an affective and hormonal system not much different from that of the jungle rat being given the ability to destroy every living thing by pushing a few buttons.” Given the work on human judgment that he and [Amos Tversky] had just finished, he found it further troubling to think that “crucial decisions are made, today as thousands of years ago, in terms of the intuitive guesses and preferences of a few men in positions of authority.” The failure of decision makers to grapple with the inner workings of their own minds, and their desire to indulge their gut feelings, made it “quite likely that the fate of entire societies may be sealed by a series of avoidable mistakes committed by their leaders.” [op cit, Kindle Locations 3316-3322].
Are we reminded of anyone? This guy?

With respect to the allusion to "base rates" above, I should alert readers to this cool little book.

My Bayes chops are pretty tight, so I don't really need it. Nonetheless, it never hurts to review stuff from yet another perspective, so I bought it. And, at $2.99 Kindle price you can't go wrong.

Relevant to all of the foregoing is a current post over at THCB, "Lead Time Bias and Court Rooms," by regular contributor Saurabh Jha, MD.
"...Physicians are asked to be mindful of the population, not just the individual patient. The message from policy makers is that we must be sensitive of limited resources. We’re chastised for overutilization of imaging. Yet it’s hard to see how excess utilization can be curbed unless courts respect evidence-based medicine. It’s at times like this that meaningful tort reform appears painfully conspicuous by its absence from the Affordable Care Act..."
Yeah. There's some very interesting stuff going to Dr. Jha's observations in the Michael Lewis book -- i.e., the vexing tension between trying to optimally treat this patient vs. setting effective "EBM" policy (Evidence Based Medicine) optimally impacting all patients. to wit:
As it happens, a movement was taking shape right then and there in Toronto that came to be called “evidence-based medicine.” The core idea of evidence-based medicine was to test the intuition of medical experts— to check the thinking of doctors against hard data. When subjected to scientific investigation, some of what passed for medical wisdom turned out to be shockingly wrong-headed. When Redelmeier entered medical school in 1980, for instance, the conventional wisdom held that if a heart attack victim suffered from some subsequent arrhythmia, you gave him drugs to suppress it. By the end of Redelmeier’s medical training, seven years later, researchers had shown that heart attack patients whose arrhythmia was suppressed died more often than the ones whose condition went untreated. No one explained why doctors, for years, had opted for a treatment that systematically killed patients— though proponents of evidence-based medicine were beginning to look to the work of Kahneman and Tversky for possible explanations. But it was clear that the intuitive judgments of doctors could be gravely flawed: The evidence of the medical trials now could not be ignored. And Redelmeier was alive to the evidence. “I became very aware of the buried analysis— that a lot of the probabilities were being made up by expert opinion,” said Redelmeier. “I saw error in the way people think that was being transmitted to patients. And people had no recognition of the mistakes that they were making. I had a little unhappiness, a little dissatisfaction, a sense that all was not right in the state of Denmark.”... [op cit, Kindle Locations 2961-2971].
More on this later. I gotta run off to my semi-annual radiation oncology f/up visit. Stay tuned.


I'm back. Prognosis is looking good one year out of tx. My PSA is down to nil, and there are no other signs of further trouble.

Back on topic. Other works to consider when ruminating on clinical cognition?

Dr. Groopman cites Kahneman and Tversky multiple times. e.g.,
As there are classic clinical maladies, there are classic cognitive errors. Alter's misdiagnosis resulted from such an error, the use of a heuristic called "availability." Amos Tversky and Daniel Kahneman, psychologists from the Hebrew University in Jerusalem, explored this shortcut in a seminal paper more than two decades ago. Kahneman won the Nobel Prize in economics in 2002 for work illuminating the way certain patterns of thinking cause irrational decisions in the marketplace; Tversky certainly would have shared the prize had he not died an untimely death in 1996. 

"Availability" means the tendency to judge the likelihood of an event by the ease with which relevant examples come to mind. Alter's diagnosis of subclinical pneumonia was readily available to him because he had seen numerous cases of the infection over recent weeks. As in any environment, there is an ecology in medical clinics. For example, large numbers of patients who abuse alcohol populate inner-city hospitals like Cook County in Chicago, Highland in Oakland, or Bellevue in Manhattan; over the course of a week, an intern in one of these hospitals may evaluate ten trembling alcoholics, all of whom have DTs—delirium tremens, a violent shaking due to withdrawal. He will tend to judge it as highly likely that the eleventh jittery alcoholic has DTs because it readily comes to mind, although there is a long list of diagnostic possibilities for uncontrolled shaking. DTs is the most available hypothesis based on his most recent experience. He is familiar with DTs, and that familiarity points his thinking that way. 

Alter experienced what might be called "distorted pattern recognition," caused by the background "ecology" of Begaye's case. Instead of integrating all the key information, he cherry-picked only a few features of her illness: her fever, her rapid breathing, and the shift in the acid-base balance in her blood. He rationalized the contradictory data—the absence of any streaking on the chest x-ray, the normal white blood cell count—as simply reflecting the earliest stage of an infection. In fact, these discrepancies should have signaled to him that his hypothesis was wrong. 

Such cognitive cherry-picking is termed "confirmation bias." This fallacy, confirming what you expect to find by selectively accepting or ignoring information, follows what Tversky and Kahneman referred to as "anchoring." Anchoring is a shortcut in thinking where a person doesn't consider multiple possibilities but quickly and firmly latches on to a single one, sure that he has thrown his anchor down just where he needs to be. You look at your map but your mind plays tricks on you—confirmation bias—because you see only the landmarks you expect to see and neglect those that should tell you that in fact you're still at sea. Your skewed reading of the map "confirms" your mistaken assumption that you have reached your destination. Affective error resembles confirmation bias in selectively surveying the data. The former is driven by a wish for a certain outcome, the latter driven by the expectation that your initial diagnosis was correct, even if it was bad for the patient...

Groopman, Jerome (2008-03-12). How Doctors Think (pp. 64-66). Houghton Mifflin Harcourt. Kindle Edition.
How about "Snowball in a Blizzard"?

Why do people— physician and patient alike— have such difficulties coping with concepts as probability and uncertainty? The answers can be found in the disciplines of evolution and psychology and are largely beyond the scope of this book, but the power of stories, and the influence of narratives on our thinking, is critically important. We think about ourselves, and of the universe around us, in absolute terms of cause and effect. We don’t regard our lives as being subject to mere chance; we assume that the variables are within our control and that our successes can be attributed to our strengths and our failures to our weaknesses. Medicine, too, is a story of sorts, and we resist the notion that chance plays a key role in the endeavor. 

But this just isn’t so. It is a trick of the mind, and it impedes us from understanding the modern world. Daniel Kahneman, a Nobel laureate in economics, refers to this as the “narrative fallacy,” writing that it inevitably arises “from our continuous attempt to make sense of the world,” adding that “the explanatory stories that people find compelling are simple; are concrete rather than abstract . . . and focus on a few striking events that happened rather than on the countless events that failed to happen.” In medicine— both at the personal and at the policy level— succumbing to the narrative fallacy can be disastrous...

Hatch, Steven (2016-02-23). Snowball in a Blizzard: A Physician's Notes on Uncertainty in Medicine (pp. 19-20). Basic Books. Kindle Edition.
I could go on at length. Kahneman and Tversky have been cited repeatedly throughout the literature. Suffice it to cite just one more:

Meehl’s work was extended by his coworker Robyn Dawes (1996), and both of them joined with David Faust in writing an influential paper (Dawes et al. 1989). This article provoked passionate controversy and did much to secure the prestige of the statistical approach in clinical psychology, medicine, and even the law. Psychotherapy was the main casualty of their campaign, even though Meehl was a practicing psychoanalyst. But their most important contribution is that a great many physicians now take statistics seriously when making diagnoses. (Unfortunately, they tend to call this the Bayesian method, which is the totally different game of pinning numbers on facts in an intuitive fashion.) 

The Nobel laureate psychologist Daniel Kahneman (2011), a lifelong admirer of Meehl, and one of the earliest users of his approach to psychological diagnosis and prognosis, asked why the “clinical” or intuitive approach is far inferior to the algorithmic (or statistical, or actuarial) one. He suggested the following reasons: the clinical predictor is a victim of the halo effect; he cannot avoid being impressed by irrelevant traits; he juggles at the same time too many variables that he has no time to weigh; he is often inconsistent; and, above all, he is “overconfident in his intuitions.” Clearly, algorithms do not have such flaws. (For the pros and cons of intuition, see Bunge 1962.) 

Of course, statistical reasoning, in focusing on whole populations, deliberately ignores personal characteristics. Does it follow that those using statistical data to diagnose cannot prescribe a treatment tailored to the patient’s peculiarities? Yes, if they use only statistics; no, if they also use personal data, such as age, family antecedents, surgeries, allergies, occupation, and recent relevant incidents. And this is, precisely, what all physicians and nurses do: to them, every patient is unique in several respects. All medicines have always been tailored, even though “personalization,” that is, therapy tailored to the individual genome, is a very recent development...

Bunge, Mario (2013-05-30). Medical Philosophy:Conceptual Issues in Medicine (Kindle Locations 1850-1865). World Scientific Publishing Co Pte Ltd. Kindle Edition. 
"Of course, statistical reasoning, in focusing on whole populations, deliberately ignores personal characteristics. Does it follow that those using statistical data to diagnose cannot prescribe a treatment tailored to the patient’s peculiarities? Yes, if they use only statistics; no, if they also use personal data, such as age, family antecedents, surgeries, allergies, occupation, and recent relevant incidents."

OK, and that brings me back around to the Michael Lewis book (particularly in the coxtext of issues raise by Dr. Jha over at the THCB post cited above):
“The physician is meant to be the perfect agent for the patient as well as the protector of society,” he said. “Physicians deal with patients one at a time, whereas health policy makers deal with aggregates.” 

But there was a conflict between the two roles. The safest treatment for any one patient, for instance, might be a course of antibiotics; but the larger society suffers when antibiotics are overprescribed and the bacteria they were meant to treat evolved into versions of themselves that were more dangerous and difficult to treat. A doctor who did his job properly really could not just consider the interests of the individual patient; he needed to consider the aggregate of patients with that illness. The issue was even bigger than one of public health policy. Doctors saw the same illness over and again. Treating patients, they weren’t merely making a single bet; they were being asked to make that same bet over and over again. Did doctors behave differently when they were offered a single gamble and when they were offered the same gamble repeatedly? 

The paper subsequently written by Amos with Redelmeier* showed that, in treating individual patients, the doctors behaved differently than they did when they designed ideal treatments for groups of patients with the same symptoms. They were likely to order additional tests to avoid raising troubling issues, and less likely to ask if patients wished to donate their organs if they died. In treating individual patients, doctors often did things they would disapprove of if they were creating a public policy to treat groups of patients with the exact same illness. Doctors all agreed that, if required by law, they should report the names of patients diagnosed with a seizure disorder, diabetes, or some other condition that might lead to loss of consciousness while driving a car. In practice, they didn’t do this— which could hardly be in the interest even of the individual patient in question. “This result is not just another manifestation of the conflict between the interests of the patient and the general interests of society,” Tversky and Redelmeier wrote, in a letter to the editor of the New England Journal of Medicine. “The discrepancy between the aggregate and the individual perspectives also exists in the mind of the physician. The discrepancy seems to call for a resolution; it is odd to endorse a treatment in every case and reject it in general, or vice versa.” 

The point was not that the doctor was incorrectly or inadequately treating individual patients. The point was that he could not treat his patient one way, and groups of patients suffering from precisely the same problem in another way, and be doing his best in both cases. Both could not be right. And the point was obviously troubling— at least to the doctors who flooded the New England Journal of Medicine with letters written in response to the article. “Most physicians try to maintain this facade of being rational and scientific and logical and it’s a great lie,” said Redelmeier. “A partial lie. What leads us is hopes and dreams and emotion.”... [Lewis, op cit, Kindle Locations 3051-3073].

From my KHIT perspective, my primary interest in all of this stuff goes to sharpening my understanding of potential problems with clinical cognition in order to better advocate for improved, dx-enhancing Health IT and workflows. See also my prior posts such as "Clinical workflow, clinical cognition, and The Distracted Mind," and "Are structured data the enemy of health care quality?" While much of the Kahneman-Tversky insights will necessarily go to reforms in medical pedagogy (i.e., teaching more effective clinically-focused "critical thinking" beginning with med school), all of the components have to cohere ongoing in practice.

Michael Lewis has done us all a great service with his new book.

BTW, You might also find this paper of interest [pdf]: "Why do humans reason?"

More to come...