“Exhilaration and Loneliness of Pioneering Thought”

(p. A15) In “The Riddle of the Rosetta: How an English Polymath and a French Polyglot Discovered the Meaning of Egyptian Hieroglyphs,” Jed Z. Buchwald and Diane Greco Josefowicz recount Thomas Young’s and Jean-François Champollion’s competing efforts toward decipherment.

. . .

The authors are chiefly concerned with Young’s and Champollion’s approaches to the hieroglyphic riddle. Rarely have I seen the false starts and blind alleys, firm beliefs and 180-degree recalibrations, exhilaration and loneliness of pioneering thought captured so well. On the other hand, not every reader will match Champollion’s stamina or persevere through the book’s densest thickets. Dramatic touches are few. Champollion probably didn’t, as commonly reported, faint at the moment of his triumph. And Young was no swashbuckler. Indiana Jones hates snakes. Young hated idioms.

If “The Riddle of the Rosetta” won’t be coming to screens anytime soon, its achievement is no less admirable. For nearly 500 pages we are invited to inhabit the minds of two of history’s finest linguists.

For the full review, see:

Maxwell Carter. “BOOKSHELF; Found In Translation.” The Wall Street Journal (Friday, September 18, 2020): A15.

(Note: ellipsis added.)

(Note: the online version of the review has the date Sep. 17, 2020, and has the title “BOOKSHELF; ‘The Riddle of the Rosetta’ Review: Found in Translation.”)

The book under review is:

Buchwald, Jed Z., and Diane Greco Josefowicz. The Riddle of the Rosetta: How an English Polymath and a French Polyglot Discovered the Meaning of Egyptian Hieroglyphs. Princeton, NJ: Princeton University Press, 2020.

In Primary Debates, Biden and Harris Led Democratic Presidential Candidates in Use of “Filler Phrases”

(p. A6) Here’s the deal: Presidential candidates issue plenty of pointed barbs in debates, but they use a lot of filler language, too.

Phrases such as “let’s be clear” and “the end of the day,” buy the speaker time to collect themselves, think ahead and formulate an answer. Among the Democratic contenders, the fact is, Vice President Joe Biden utters them most frequently (and “the fact is” has been his most-used phrase).

The Wall Street Journal identified 23 commonly used three-, four- and five-word phrases and their variations spoken by candidates during the four Democratic presidential debates and tracked the number of times they were said.

Mr. Biden used almost six filler phrases for every 1,000 words he spoke, the highest rate among the Democrats still running and far above their average of 2.6.

Asked about the findings, Biden spokesman TJ Ducklo said, “The fact of the matter is that poll after poll has shown that Joe Biden is the candidate who will defeat” President Trump.

. . .

After Mr. Biden, who racked up 77 instances of the phrases in the debates, the next highest totals belonged to Sens. Kamala Harris and Bernie Sanders.

For the full story, see:

Lindsay Huth and Lakshmi Ketineni. “The Fact Is, Candidates Use a lot of Filler Phrases.” The Wall Street Journal (Wednesday, November 20, 2019): A6.

(Note: ellipsis added.)

(Note: the online version of the story has the same date as the print version, and has the title “The Fact Is, Democratic Candidates Use a lot of Filler Phrases.”)

Venture Capitalists Can Be Easy to Fool

I admire much about Peter Thiel, but was stunned to read in his Zero to One (p. 160) that he only invests venture capital money in start-ups whose founding supplicant is wearing a t-shirt. The review quoted below confirms that other venture capitalists also use dubious criteria to evaluate entrepreneurs.

(p. C4) Neumann’s innovation with WeWork was to repurpose office space for freelancers worldwide — rebranding precarity into community.

. . .

. . . Neumann seemed to believe that the pesky demands of having to turn a profit didn’t quite apply to him, even as he was determined to live the ostentatious life of a bohemian tycoon.

. . .

WeWork pulled the classic new-economy maneuver of hiring idealistic young people, deploying them to the point of exhaustion and paying them peanuts while telling them that they were part of a revolution — what Neumann called “the ‘We’ decade.” Eventually, WeWork offered stock options, though Neumann would be the one to cash out hundreds of millions in stock in order to fund an escalating lifestyle that had grown to include five children, several houses, a penchant for $200 T-shirts and lots of pot.

. . .

“Billion Dollar Loser” would be absorbing enough were it just about one man’s grandiosity, but Wiedeman has a larger argument to make about what Neumann represents. Neumann finagled funding not only from SoftBank, the Japanese conglomerate led by the billionaire-entrepreneur Masayoshi Son, who liked to say that “feeling is more important than numbers,” but also from the venerable venture capital firm Benchmark. Neumann had passed himself off as a tech visionary, even though he rarely used a computer and WeWork’s IT department was once run by a high school student from Queens.

For the full review, see:

Jennifer Szalai. “Big Dreams, and a Harsh Awakening.” The New York Times (Thursday, October 22, 2020): C4.

(Note: ellipses added.)

(Note: the online version of the review has the date Oct. 21, 2020, and has the title “‘Billion Dollar Loser’ Recounts WeWork’s Big Dreams and Its Harsh Wake-Up Call.”)

The book under review is:

Wiedeman, Reeves. Billion Dollar Loser: The Epic Rise and Spectacular Fall of Adam Neumann and WeWork. New York: Little, Brown and Company, 2020.

“The Often-Unsung Adaptability of Organic Intelligence”

(p. A13) . . ., as the journalist Jonathan Waldman chronicles in “SAM,” the quest for a bricklaying robot has been bumpier than the work of a mason with vertigo.

. . .

Several themes run through the book. First is the often-unsung adaptability of organic intelligence.

. . .

The minute adjustments a human makes when manipulating objects, especially in messy environments like construction sites, result from billions of years of evolution. We make it look easy, until you give instructions to a robot and watch it fumble around or freeze up when it gets a little dirt on its face. Yann LeCun, Facebook’s chief A.I. scientist, once told me, “I would declare victory if in my professional lifetime we could make machines that are as intelligent as a rat.”

Mr. Peters has laudable motivations. “By creating a bricklaying robot,” Mr. Waldman writes, “he aimed to eliminate lifting and bending and repetitive-motion injuries in humans; to improve the quality of walls; to finish jobs faster and safer and cheaper; and to ease project scheduling and estimation. Basically: to modernize the world’s second oldest and most primitive trade.”

. . .

Within this physically and culturally harsh environment, Construction Robotics had to invent and reinvent their business model on the fly. Should they license their innovations? Sell the robots? Rent them? Provide robots and technicians as a service? Create a full-service masonry shop? Pivot from bricks to cement blocks? Take money from venture capitalists, court Google or a Dubai investment fund? Mr. Peters follows the philosophy of the book “The Lean Startup” and aims for an MVP—minimum viable product—to gain exposure and experience, knowing the risks in the construction industry. Word of a robot that builds crummy walls will travel fast, and demolished reputations are hard to rebuild.

The business finally finds its footing in the epilogue, around 2018. Construction Robotics gets SAM to lay more than 3,000 bricks a day (versus 300 to 1,000 for a human mason), and they create another machine that helps workers lift and place concrete blocks, quickly selling dozens. The company now looks to be solvent, though it’s unclear how much the construction landscape is poised to change.

For the full review, see:

Hutson, Matthew. “BOOKSHELF; Building a Better Bricklayer.” The Wall Street Journal (Tuesday, Jan 14, 2020): A13.

(Note: ellipses added.)

(Note: the online version of the review has the date January 13, 2020, and has the title “BOOKSHELF; ‘SAM’ Review: Building a Better Bricklayer.”)

The book under review is:

Waldman, Jonathan. SAM: One Robot, a Dozen Engineers, and the Race to Revolutionize the Way We Build. New York: Simon & Schuster, 2020.

A.I. Lacks Common Sense: “A Broad and Often Unspoken Understanding of How the World Works”

(p. A15) Journalists like to punctuate stories about the risks of artificial intelligence—particularly long-term, humanity-threatening risks—with images of the Terminator. The idea is that unchecked robots will rise up and kill us all.

. . .

Melanie Mitchell, a computer scientist at Portland State University, is in the too-soon-to-worry camp. “My own opinion is that too much attention has been given to the risks from superintelligent AI,” she writes in “Artificial Intelligence,” “and far too little to deep learning’s lack of reliability and transparency and its vulnerability to attacks.”

. . .

Object-recognition software, for instance, can track pedestrians, detect tumors and sort photo libraries. But it doesn’t understand the content the way we do. Its obtuseness becomes sharply apparent in so-called adversarial attacks, in which only minimal changes to an image (or a sound or text file) can fool an AI into misidentifying it. Such attacks even transfer to the real world. A stop sign with a few innocuous stickers becomes a speed-limit sign.

The researchers first elucidating such vulnerabilities in neural networks—machine-learning programs inspired by the brain’s wiring—called them an “intriguing property.” Ms. Mitchell writes, “Calling this an ‘intriguing property’ of neural networks is a little like calling a hole in the hull of a fancy cruise liner a ‘thought-provoking facet’ of the ship.”

Ultimately, these systems lack common sense, a broad and often unspoken understanding of how the world works. Common sense, in turn, might require embodied experience in the world, plus the ability to abstract from it and form analogies. Much of Ms. Mitchell’s academic work concerns helping AI form analogies. It hasn’t progressed far. (No fault of hers.)

For the full review, see:

Matthew Hutson. “BOOKSHELF; Learn Like a Machine.” The Wall Street Journal (Wednesday, November 20, 2019): A15.

(Note: ellipses added.)

(Note: the online version of the review has the date November 19, 2019, and has the title “BOOKSHELF; ‘Human Compatible’ and ‘Artificial Intelligence’ Review: Learn Like a Machine.”)

The book under review is:

Mitchell, Melanie. Artificial Intelligence: A Guide for Thinking Humans. New York: Farrar, Straus, and Giroux, 2019.

Workers with Criminal Records Pay for Their Second Chance with Greater Loyalty and Harder Work

(p. B1) CINCINNATI—While some companies try to attract and keep employees with yoga classes and lavish cafeterias, Nehemiah Manufacturing Co.’s perks include a social-service team and an attorney.

When two consumer-product veterans started Nehemiah a decade ago, their idea was to create more opportunities in a struggling part of Cincinnati. Increasingly, that meant hiring people who had a particularly hard time finding jobs: those with criminal backgrounds.

Now, workers with criminal records make up around 80% of the company’s about 180 employees—and Nehemiah has learned that offering a job to people trying to turn their lives around is just half the battle.

“We are investing in our employees in order to retain them,” said Richard Palmer, president of Nehemiah, whose brands include Boogie Wipes, Saline Soothers and other consumer products. “It’s no different than tech companies bringing in lunch and a foosball table.”

In one of the tightest labor markets in decades, more employers are willing to give ex-convicts a chance, trying to marry business needs and good intentions. Even large American companies are rethinking whether their responsibilities extend beyond their shareholders. JPMorgan Chase & Co. Chief Executive James Dimon said in October [1999] that the bank would step up efforts to recruit people with criminal backgrounds.

Hiring people with a criminal past can pay big dividends for companies, such as closer community ties and a loyal workforce. But keeping them on the job can be a struggle.

. . .

(p. B6) Since its first days, Nehemiah has become more deliberate about identifying candidates who are likely to be good, reliable employees and has developed a more formal system for providing them with support.

Today, Nehemiah’s annual turnover stands at roughly 15%, well below the 38.5% average for consumer-products companies, as reported by Mercer’s 2019 U.S. Turnover Survey. Nehemiah says it had operating income of $5.7 million on sales of $59.4 million in 2018.

. . .

“We found that the population we were hiring who had criminal backgrounds were our most loyal people,” said Mr. Palmer. “When we were looking for people to work overtime, come in on Saturday or go that extra mile, it was the second-chance population that was saying, ‘I’m in.’”

. . .

At Nehemiah, having a criminal past carries less of a stigma because so many workers have been incarcerated.

. . .

. . ., Nehemiah’s approach . . . means it can spot potential other employers might overlook. When Rayshun Holt came to Nehemiah roughly two years ago, Ms. Merida said he immediately stood out as someone the company wanted.

Mr. Holt, 40, spent two decades in prison after fatally shooting a friend when he was 15 during what he describes as a scuffle over a gun. While in prison, Mr. Holt reconnected to his faith, started taking classes and began coaching other prisoners on how to turn their lives around.

Released in 2016 with $96 in his pocket, he said, “I was filled with hope and overwhelmed by fear.” His first job was in a fast-food restaurant specializing in chicken fingers. “I was the oldest person there and the most enthusiastic. It was the first time in my life I was earning an honest check,” he said.

But he struggled to find steady work with decent pay. Nehemiah hired him as a second-shift supervisor at $19 an hour.

Ms. Merida said she was impressed by Mr. Holt’s passion, humility and sincerity when he told his life story, how he knew the streets but had already taken steps to turn his life around. “I knew this was a born leader who could really have a profound impact on our employees,” said Ms. Merida. “He could show them that no matter how bad it is, your life isn’t over.”

Mr. Holt now works as the company’s commercialization coordinator, responsible for taking new products and product improvements from concept to market.

For the full story, see:

Ruth Simon. “The Company of Second Chances.” The Wall Street Journal (Saturday, January 25, 2020): B1 & B6.

(Note: ellipses, and bracketed year, added.)

(Note: the online version of the story has the same date and title as the print version.)

Young Doctor “Taken Aback” by Deaths Under Nationalized Medicine

(p. 26) Westaby’s book will be a balm to the hearts of curmudgeons everywhere. Sidestepping the contemporary hand-wringing about the lack of empathy in medicine, Westaby, a British surgeon, positions empathy as a threat to the surgical career: “Heart surgery,” he writes, “needs to be an impersonal, technical exercise.”

. . .

The deaths that truly madden him are those that could have been prevented by available technologies not then funded by the British National Health Service (N.H.S.), his employer.

. . .

As a young doctor who imagines nationalized medicine as a way toward comprehensive care for all my patients, I was taken aback.

For the full review, see:

Rachel Pearson. “SHORTLIST; Medical Memoirs.” The New York Times Book Review (Sunday, July 2, 2017): 26.

(Note: the online version of the review has the date June 27, 2017, and has the title “SHORTLIST; Four Timely Memoirs from the Halls of Medicine.”)

The book under review is:

Westaby, Stephen. Open Heart: A Cardiac Surgeon’s Stories of Life and Death on the Operating Table. New York: Basic Books, 2017.

Bayesian Updating, Not Clinical Trials, Is Key to Advancing Medical Knowledge

(p. D8) In the early pandemic era, for instance, airborne transmission of Covid-19 was not considered likely, but in early July the World Health Organization, with mounting scientific evidence, conceded that it is a factor, especially indoors. The W.H.O. updated its priors, and changed its advice.

This is the heart of Bayesian analysis, named after Thomas Bayes, an 18th-century Presbyterian minister who did math on the side. It captures uncertainty in terms of probability: Bayes’s theorem, or rule, is a device for rationally updating your prior beliefs and uncertainties based on observed evidence.

. . .

As Marc Lipsitch, an infectious disease epidemiologist at Harvard, noted on Twitter, Bayesian reasoning comes awfully close to his working definition of rationality. “As we learn more, our beliefs should change,” Dr. Lipsitch said in an interview.

. . .

But there is little point in trying to establish fixed numbers, said Natalie Dean, an assistant professor of biostatistics at the University of Florida.

“We should be less focused on finding the single ‘truth’ and more focused on establishing a reasonable range, recognizing that the true value may vary across populations,” Dr. Dean said. “Bayesian analyses allow us to include this variability in a clear way, and then propagate this uncertainty through the model.”

. . .

Joseph Blitzstein, a statistician at Harvard, delves into the utility of Bayesian analysis in his popular course “Statistics 110: Probability.” For a primer, in lecture one, he says: “Math is the logic of certainty, and statistics is the logic of uncertainty. Everyone has uncertainty. If you have 100 percent certainty about everything, there is something wrong with you.”

By the end of lecture four, he arrives at Bayes’s theorem — his favorite theorem because it is mathematically simple yet conceptually powerful.

“Literally, the proof is just one line of algebra,” Dr. Blitzstein said. The theorem essentially reduces to a fraction; it expresses the probability P of some event A happening given the occurrence of another event B.

“Naïvely, you would think, How much could you get from that?” Dr. Blitzstein said. “It turns out to have incredibly deep consequences and to be applicable to just about every field of inquiry” — from finance and genetics to political science and historical studies. The Bayesian approach is applied in analyzing racial disparities in policing (in the assessment of officer decisions to search drivers during a traffic stop) and search-and-rescue operations (the search area narrows as new data is added). Cognitive scientists ask, ‘Is the brain Bayesian?’ Philosophers of science posit that science as a whole is a Bayesian process — as is common sense.

. . .

Even with evidence, revising beliefs isn’t easy. The scientific community struggled to update its priors about the asymptomatic transmission of Covid-19, even when evidence emerged that it is a factor and that masks are a helpful preventive measure. This arguably contributed to the world’s sluggish response to the virus.

. . .

In 1650, Oliver Cromwell, Lord Protector of the Commonwealth of England, wrote in a letter to the Church of Scotland: “I beseech you, in the bowels of Christ, think it possible you may be mistaken.”

In the Bayesian world, Cromwell’s law means you should always “keep a bit back — with a little bit of probability, a little tiny bit — for the fact that you may be wrong,” Dr. Spiegelhalter said. “Then if new evidence comes along that totally contradicts your main prior belief, you can quickly ditch what you thought before and lurch over to that new way of thinking.”

“In other words, keep an open mind,” said Dr. Spiegelhalter. “That’s a very powerful idea. And it doesn’t necessarily have to be done technically or formally; it can just be in the back of your mind as an idea. Call it ‘modeling humility.’ You may be wrong.”

For the full story, see:

Siobhan Roberts. “Thinking Like an Epidemiologist.” The New York Times (Tuesday, August 4, 2020): D8.

(Note: ellipses added.)

(Note: the online version of the story has the same date as the print version, and has the title “How to Think Like an Epidemiologist.”)

“The Concept of Microaggressions” Is “Subjective by Nature”

(p. 25) Scott Lilienfeld, an expert in personality disorders who repeatedly disturbed the order in his own field, questioning the science behind many of psychology’s conceits, popular therapies and prized tools, died on Sept. 30 [2020] at his home in Atlanta.

. . .

He . . . received blowback when he touched a nerve. In 2017, he published a critique of the scientific basis for microaggressions, described as subtle and often unwitting snubs of marginalized groups. (For instance, a white teacher might say to a student of color, “My, this essay is so articulate!”) Dr. Lilienfeld argued that the concept of microaggressions was subjective by nature, difficult to define precisely, and did not take into account the motives of the presumed offender, or the perceptions of the purported victim. What one recipient of the feedback might consider injustice, another might regard as a compliment.

The nasty mail rolled in, from many corners of academia, Dr. Lilienfeld told colleagues.

“There was no one like him in this field,” said Steven Jay Lynn, a psychology professor at Binghamton and a longtime collaborator. “He just had this abiding faith that science could better us, better humankind; he saw his championing as an opportunity to make a difference in the world. He enjoyed stepping into controversial areas, it’s true, but the motives were positive.”

For the full obituary, see:

Benedict Carey. “Scott Lilienfeld, 59, Psychologist Who Questioned Science of Psychology, Dies.” The New York Times, First Section (Sunday, October 18, 2020): 25.

(Note: ellipses, and bracketed year, added.)

(Note: the online version of the obituary has the date Oct. 16, 2018, and has the title “Scott Lilienfeld, Psychologist Who Questioned Psychology, Dies at 59.”)

Monty Python’s John Cleese on Creativity and Open Offices

(p. D10) Creativity is almost always: unlearned. Ask young children, “Are you creative?” They’ll all raise a hand. By age 16, none of them will because they’ve had their creativity gently squeezed out of them by those who think conventionally.

. . .

One of the great mistakes is: the open-plan office. If I were starting a business—and this is a great time to reinvent the workplace—I’d give everybody an office. It’s essential you’re not interrupted when you’re working. And you must have lots of rooms for people to meet and play.

For the full interview, see:

Jeff Slate, interviewer. “20 ODD QUESTIONS; John Cleese.” The Wall Street Journal (Saturday, Oct 31, 2020): D10.

(Note: ellipsis added. The questions from the interviewer, before each colon, were bolded in the original.)

(Note: the online version of the interview has the date October 28, 2020, and has the title “20 ODD QUESTIONS; John Cleese on Why Open Offices Are Among History’s Greatest Mistakes.”)

Arthur Ashton’s Serendipitous Invention of Optical Tweezers

(p. B11) Arthur Ashkin, a physicist who was awarded a 2018 Nobel Prize for figuring out how to harness the power of light to trap microscopic objects for closer study, calling his invention optical tweezers, died on Sept. 21 [2020] at his home in Rumson, N.J.

. . .

Dr. Ashkin’s discovery was serendipitous.

In 1966, he was head of the laser research department at Bell Labs, the storied New Jersey laboratory founded by the Bell Telephone Company in 1925, when he went to a scientific conference in Phoenix. There, in a lecture, he heard two researchers discuss something odd that they had found while studying lasers, which had been invented six years earlier: They had noticed that dust particles within the laser beams careened back and forth. They theorized that light pressure might be the cause.

Dr. Ashkin did some calculations and concluded that this was not the cause — it was most likely thermal radiation. But his work reignited a childhood interest in the subject of light pressure.

Light pushes against everything, including people, because it comprises tiny particles called photons. Most of the time the pressure is utterly insignificant; people, for one, feel nothing. But Dr. Ashkin thought that if objects were small enough, a laser might be used to push them around.

. . .

Then, in 1986, he and several colleagues, notably Steven Chu, achieved the first practical application of optical tweezers when they sent a laser through a lens to manipulate microscopic objects. Their results were published in another paper in Physical Review Letters. Dr. Chu began using the tweezers to cool and trap atoms, a breakthrough for which he was awarded a one-third share of the Nobel Prize in Physics in 1997.

Dr. Ashkin, it was clear, was irked that the Nobel committee had not recognized his foundational work in awarding the prize. But he had already begun to use the tweezers for a different purpose: trapping live organisms and biological material.

Other scientists thought this application would not work, as he explained in an interview with the Nobel Institute after he was awarded the prize in 2018.

“They used light to heal wounds, and it was considered to be deadly,” he said. “When I described catching living things with light, people said, ‘Don’t exaggerate, Ashkin.’”

. . .

Dr. Ashkin was awarded one-half the 2018 physics prize, . . . . In so doing he became, at 96, the oldest recipient of a Nobel Prize at the time.

. . .

Dr. Ashkin’s retirement from Bell Labs did not stop him from continuing his research. When he received word of his Nobel Prize, he was working on a project in his basement to improve solar energy collection. Asked if he was going to celebrate, he said: “I am writing a paper right now. I am not about celebrating old stuff.”

For the full obituary, see:

Dylan Loeb McClain. “Arthur Ashkin, 98, Dies; Nobel-Winning Physicist.” The New York Times (Tuesday, September 29, 2020): B11.

(Note: ellipses, and bracketed year, added.)

(Note: the online version of the obituary was updated Oct. 5, 2020, and has the title “Arthur Ashkin, 98, Dies; Nobel Laureate Invented a ‘Tractor Beam’.”)

The essay about Aoyagi mentioned above is:

Severinghaus, John W. “Takuo Aoyagi: Discovery of Pulse Oximetry.” Anesthesia & Analgesia 105, no. 6 (Dec. 2007): S1-S6.