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Friday, May 25, 2018

Holmes and Balwani should be indicted

I finished John Carryrou's riveting Theranos expose´ book Bad Blood in short order.

I closely studied every word from cover to cover. It is now awash in Kindle yellow highlighter and bookmarks.

Click to enlarge

It is infuriating.

The latest hardcopy issue of my AAAS Science Magazine showed up in my mailbox yesterday. Among the book reviews:
A biotech company’s blood test proves too good to be true
By Jennifer Couzin-Frankel

In the opening pages of Bad Blood, the chief financial officer for the blood-testing company Theranos meets with his boss, Elizabeth Holmes, a charismatic 20-something Stanford University dropout, and warns her that the company must stop lying to its investors. Holmes’s expression turns icy. She informs him that he’s not a team player. Then she fires him on the spot.

Variations on this story recur throughout this engrossing new book by John Carreyrou, the Wall Street Journal reporter whose articles—guided by dozens of frightened but determined sources—brought down Theranos. The fraud that fooled everyone from Walgreens to U.S. statesmen is almost too fantastical to be believed. Holmes, vindictive and paranoid, and the company’s number two, Ramesh “Sunny” Balwani, a bully almost 20 years her senior with whom she was in a romantic relationship, are pitted against employees frantic that patients will be harmed by a technology that doesn’t work.

Holmes dreamed up Theranos in 2004, while at Stanford. She had recently completed an internship at the Genome Institute of Singapore, where she tested patient samples for the severe acute respiratory syndrome (SARS) virus that had devastated Asia. Determined to transform the clunky testing technology, Holmes imagined an arm patch that would diagnose and treat medical conditions. This morphed into Theranos testing devices, which she claimed could run hundreds of tests on a few drops of blood.

It was a remarkable idea. There was just one problem: Scientists and engineers at Theranos couldn’t produce reliable results, at least not in the time frame demanded. That didn’t stop Holmes and Balwani from raking in hundreds of millions of investor dollars or from deploying the error-prone machines for use on unsuspecting patients…
Science Magazine book reviews typically take the obligatory "Praise-Criticism-Praise" format.

Not this one.

See my many prior posts on Theranos here.

In addition to the tsunami of civil litigation that will surely henceforth consume the lives of Elizabeth Holmes and her thuggish co-conspirator Sunny Balwani, these two should be criminally indicted. John Carryrou's book overflows with comprehensively vetted elements of probable cause for charges of egregious felony fraud.
...[O]n March 14, 2018, the Securities and Exchange Commission charged Theranos, Holmes, and Balwani with conducting “an elaborate, years-long fraud.” To resolve the agency’s civil charges, Holmes was forced to relinquish her voting control over the company, give back a big chunk of her stock, and pay a $ 500,000 penalty. She also agreed to be barred from being an officer or director in a public company for ten years. Unable to reach a settlement with Balwani, the SEC sued him in federal court in California. In the meantime, the criminal investigation continued to gather steam. As of this writing, criminal indictments of both Holmes and Balwani on charges of lying to investors and federal officials seem a distinct possibility.

Carreyrou, John. Bad Blood: Secrets and Lies in a Silicon Valley Startup (p. 341). Knopf Doubleday Publishing Group. Kindle Edition.
An important book, IMO. Reads like a suspense novel. Great job, sir.


CBS "60 Minutes: The Theranos Deception."
John Carreyrou: She [Elizabeth Holmes] is a pathological liar. She wanted to be a -- celebrated tech entrepreneur. She wanted to be rich and famous. And she wouldn't let anything get in the way of that.
Norah O'Donnell: What kind of job did the board do in holding Holmes accountable?
John Carreyrou: This is one of the most epic failures in corporate governance in the annals of American capitalism. They did nothing to verify that her scientific claims were true...
Watch all of it. Read the book.

BTW, random note. Google "Naked Capitalism Horan Uber" and bring a Snickers (you'll be a while; a book's worth of accrued analysis). They make the Theranos fraud look like relative chump change. They're trying to hang on and blow enough smoke long enough to IPO their way out of their multi-billion dollar mess (they lost about $4.5 billion in 2017) and foist their intractable losses onto the markets (meaning, in part, into your retirement funds).


Another "Holy Shit" book. Just started it. Yikes.

ALMOST two decades ago, when I wrote the preface to my book Causality (2000), I made a rather daring remark that friends advised me to tone down. “Causality has undergone a major transformation,” I wrote, “from a concept shrouded in mystery into a mathematical object with well-defined semantics and well-founded logic. Paradoxes and controversies have been resolved, slippery concepts have been explicated, and practical problems relying on causal information that long were regarded as either metaphysical or unmanageable can now be solved using elementary mathematics. Put simply, causality has been mathematized.”

Reading this passage today, I feel I was somewhat shortsighted. What I described as a “transformation” turned out to be a “revolution” that has changed the thinking in many of the sciences. Many now call it “the Causal Revolution,” and the excitement that it has generated in research circles is spilling over to education and applications. I believe the time is ripe to share it with a broader audience.

This book strives to fulfill a three-pronged mission: first, to lay before you in nonmathematical language the intellectual content of the Causal Revolution and how it is affecting our lives as well as our future; second, to share with you some of the heroic journeys, both successful and failed, that scientists have embarked on when confronted by critical cause-effect questions.

Finally, returning the Causal Revolution to its womb in artificial intelligence, I aim to describe to you how robots can be constructed that learn to communicate in our mother tongue— the language of cause and effect. This new generation of robots should explain to us why things happened, why they responded the way they did, and why nature operates one way and not another. More ambitiously, they should also teach us about ourselves: why our mind clicks the way it does and what it means to think rationally about cause and effect, credit and regret, intent and responsibility…

Pearl, Judea; Mackenzie, Dana. The Book of Why: The New Science of Cause and Effect (Kindle Locations 47-61). Basic Books. Kindle Edition.
This one is gonna be fun. Stay tuned. From the Atlantic interview article: Pearl sees it, the field of AI got mired in probabilistic associations. These days, headlines tout the latest breakthroughs in machine learning and neural networks. We read about computers that can master ancient games and drive cars. Pearl is underwhelmed. As he sees it, the state of the art in artificial intelligence today is merely a souped-up version of what machines could already do a generation ago: find hidden regularities in a large set of data. “All the impressive achievements of deep learning amount to just curve fitting,” he said recently...
"If I could sum up the message of this book in one pithy phrase, it would be that you are smarter than your data. Data do not understand causes and effects; humans do."
In short, being unreflectively "data-driven" (that fashionable tech cliche) is a both naive and a cop-out. (Note: some of this will surely go -- at least tangentially --  to the "information ethics" topic of my prior post.)

More to come...

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