Jonathan Shaw in Harvard Magazine:

IN MARCH 18, 2018, at around 10 P.M., Elaine Herzberg was wheeling her bicycle across a street in Tempe, Arizona, when she was struck and killed by a self-driving car. Although there was a human operator behind the wheel, an autonomous system—artificial intelligence—was in full control. This incident, like others involving interactions between people and AI technologies, raises a host of ethical and proto-legal questions. What moral obligations did the system’s programmers have to prevent their creation from taking a human life? And who was responsible for Herzberg’s death? The person in the driver’s seat? The company testing the car’s capabilities? The designers of the AI system, or even the manufacturers of its onboard sensory equipment?

“Artificial intelligence” refers to systems that can be designed to take cues from their environment and, based on those inputs, proceed to solve problems, assess risks, make predictions, and take actions. In the era predating powerful computers and big data, such systems were programmed by humans and followed rules of human invention, but advances in technology have led to the development of new approaches. One of these is machine learning, now the most active area of AI, in which statistical methods allow a system to “learn” from data, and make decisions, without being explicitly programmed. Such systems pair an algorithm, or series of steps for solving a problem, with a knowledge base or stream—the information that the algorithm uses to construct a model of the world.

Ethical concerns about these advances focus at one extreme on the use of AI in deadly military drones, or on the risk that AI could take down global financial systems. Closer to home, AI has spurred anxiety about unemployment, as autonomous systems threaten to replace millions of truck drivers, and make Lyft and Uber obsolete. And beyond these larger social and economic considerations, data scientists have real concerns about bias, about ethical implementations of the technology, and about the nature of interactions between AI systems and humans if these systems are to be deployed properly and fairly in even the most mundane applications.

More here.

Paul Dolan in The Guardian:

According to the UK’s Office for National Statistics (ONS), which has been studying the happiness levels of a sample of 200,000 people each year from 2011, about 1% of us are miserable. This would scale up to about half a million Britons. Earning less than £400 per week (or about £20,000 a year) is one of the factors that increases the chances of being in the most miserable 1%. Above £400 per week, the law of diminishing marginal returns kicks in. Once your basic needs are satisfied, your desire for ever-increasing amounts of money generates ever-decreasing returns of happiness. Likewise, the most recent American Time Use Survey (ATUS), which allows analysts to estimate levels of happiness associated with a range of daily activities, showed that happiness goes up with increases in income at the lower end of the scale, but then it falls with higher incomes. Contrary to what most of us might predict, those earning over $100K are no happier than those with incomes of less than $25K. Those with the highest incomes report the least sense of purpose in their experiences. Perhaps “having it all” makes what we do feel less meaningful.

Data suggest that being rich can lead to time and attention being directed towards activities that fuel the attainment of more wealth, such as longer working hours and longer commutes, and away from activities that generate more happiness, such as time outside and time with family and friends. This discrepancy between the big effect on happiness that we imagine increased wealth should bring and the small effect we experience goes a long way towards explaining the narrative trap of reaching for wealth. But most people, including those on incomes above £50,000, truly believe misery would continue to fall with higher income above this point. And most people, irrespective of income, would continue to reach for more long after they have earned their 50 grand. This is the addiction problem.

If you are not struggling to make ends meet, I propose that you rein in the social narrative that encourages you to endlessly pursue more money. Invest your time and effort into doing all you can to ensure that those who are struggling are provided with the living conditions, wages and financial support that will help them to cover the costs of their living expenses. (Helping other people is great for our own happiness.)

More here.

Nathan Heller in The New Yorker:

American stories trace the sweep of history, but their details are definingly particular. In the summer of 1979, Elizabeth Anderson, then a rising junior at Swarthmore College, got a job as a bookkeeper at a bank in Harvard Square. Every morning, she and the other bookkeepers would process a large stack of bounced checks. Businesses usually had two accounts, one for payroll and the other for costs and supplies. When companies were short of funds, Anderson noticed, they would always bounce their payroll checks. It made a cynical kind of sense: a worker who was owed money wouldn’t go anywhere, or could be replaced, while an unpaid supplier would stop supplying. Still, Anderson found it disturbing that businesses would write employees phony checks, burdening them with bounce fees. It appeared to happen all the time.

Midway through summer, the bank changed its office plan. When Anderson had started, the bookkeepers worked in rows of desks. Coördination was easy—a check that fell under someone else’s purview could be handed down the line—and there was conversation throughout the day. Then cubicles were added. That transformation interrupted the workflow, the conversational flow, and most other things about the bookkeepers’ days. Their capacities as workers were affected, yet the change had come down from on high.

These problems nagged at Anderson that summer and beyond. She had arrived at college as a libertarian who wanted to study economics. In the spirit of liberal-arts exploration, though, she enrolled in an introductory philosophy course whose reading list included Karl Marx’s 1844 manuscripts concerning worker alienation. Anderson thought that Marx’s economic arguments about the declining rate of profit and the labor theory of value fell apart under scrutiny. But she was stirred by his observational writings about the experience of work. Her summer at the bank drove home the fact that systemic behavior inside the workplace was part of the socioeconomic fabric, too: it mattered whether you were the person who got a clear check or a bounced check, whether a hierarchy made it easier or harder for you to excel and advance.

More here.

Stephen Camarata in Psychology Today:

This past week, Dr. Mark Green, M.D., who was recently elected to the U.S. House of Representatives from the state of Tennessee declared: “Let me say this about autism, I have committed to people in my community, up in Montgomery County [Tennessee], to stand on the CDC’s desk and get the real data on vaccines. Because there is some concern that the rise in autism is the result of the preservatives that are in our vaccines. As a physician, I can make that argument and I can look at it academically and make the argument against the CDC, if they really want to engage me on it,”[1]

As a clinician dedicated to serving people with autism and their families, I am both appalled and disheartened that a physician — and future member of Congress — has once again promulgated the “vaccines cause autism” narrative that has led to so much misinformation and fear regarding vaccinating toddlers and preschoolers against deadly diseases. Moreover, these shameful comments demonstrate why this lie has proven extremely difficult to overcome.

A crucial and indisputable fact about the “vaccines cause autism” narrative is that it is founded on fraudulent research. This is not simply an opinion.

More here.

Jamil Jivani in Quillette:

The demand that we transcend tribalism in public debate sits on the schism line of today’s culture wars over speech, scholarship and art. On one side (loosely, if inexactly, called “the left”), there exists a deep conviction that the social justice sins of the past (and present) make an escape from tribalism impossible—and so the only solution is to carve out well-guarded silos of speech and cultural representation for disadvantaged groups. On the other side (loosely, if inexactly, called “the right”) are those who view those silos as a tool of censorship, as well as an affront to the idea that we all can speak for ourselves as individuals, regardless of skin color, sexual orientation, gender and faith.

This conflict took center stage during a recent high-profile Munk Debate in Toronto, which had been billed as a debate about the dangers of political correctness. Two of the biggest reactions from the 3,000-strong audience came in response to Georgetown University’s Michael Eric Dyson (representing “the left”) referring to psychologist Jordan Peterson as a “mean, mad white man,” and then Peterson subsequent pointing to Dyson’s comment as an “example of what’s wrong with the politically correct left.” A primary source of conflict between the two best-selling authors was the extent of white privilege, and the question of how it should be accounted for in public debate, if at all.

On that Munk Debate stage in Toronto, Peterson wanted to have a debate among individuals sharing ideas as individuals, not as representatives of their race. Dyson disagreed again and again. The other participants—journalist Michelle Goldberg and performer Stephen Fry—watched on as this increasingly toxic exchange dominated the night.

More here.

Maryanne Wolf in The Guardian:

Look around on your next plane trip. The iPad is the new pacifier for babies and toddlers. Younger school-aged children read stories on smartphones; older boys don’t read at all, but hunch over video games. Parents and other passengers read on Kindles or skim a flotilla of email and news feeds. Unbeknownst to most of us, an invisible, game-changing transformation links everyone in this picture: the neuronal circuit that underlies the brain’s ability to read is subtly, rapidly changing – a change with implications for everyone from the pre-reading toddler to the expert adult.

As work in neurosciences indicates, the acquisition of literacy necessitated a new circuit in our species’ brain more than 6,000 years ago. That circuit evolved from a very simple mechanism for decoding basic information, like the number of goats in one’s herd, to the present, highly elaborated reading brain. My research depicts how the present reading brain enables the development of some of our most important intellectual and affective processes: internalized knowledge, analogical reasoning, and inference; perspective-taking and empathy; critical analysis and the generation of insight. Research surfacing in many parts of the world now cautions that each of these essential “deep reading” processes may be under threat as we move into digital-based modes of reading.

More here.

Read more »

Nicky Woolf in New Statesman:

Sean Wilentz in The New York Times:

The Civil War began over one basic issue: Was slavery, the ownership of human beings, a legitimate national institution, fixed in national law by the United States Constitution? One half of the country said it was, the other said it was not. The ensuing conflict was the chief instigator of Southern secession, as the secessionists themselves proclaimed. It was thus the chief source of the war that led to slavery’s abolition in the United States. The struggle over property in slaves focused largely on the fate of the Western territories, but it also inflamed conflicts over the status of fugitive slaves. Pro-slavery Southerners insisted that the federal government was obliged to capture slaves who had escaped to free states and return them to their masters, and thus vindicate the masters’ absolute property rights in humans. Antislavery Northerners, denying that obligation and those supposed rights, saw the fugitives as heroic refugees from bondage, and resisted federal interference fiercely and sometimes violently. Even more than the fights over the territories, Andrew Delbanco asserts in “The War Before the War,” the “dispute over fugitive slaves … launched the final acceleration of sectional estrangement.”

Delbanco, an eminent and prolific scholar of American literature, is well suited to recounting this history, and not just because fugitive slaves have been a subject of American fiction from Harriet Beecher Stowe to Toni Morrison and beyond. A traditional critic in the historicist mode, Delbanco has always thoughtfully rendered the contexts in which his writers wrote. He has offered fresh interpretations not only of how national politics shaped the writing of, say, “Moby-Dick,” but also of what Melville’s tragic awareness and moral ambiguities tell us about the temper of a nation hurtling toward civil war. Whitman, Emerson, Thoreau and Hawthorne, as well as Melville, Stowe and numerous lesser artists and thinkers of the time, all had pertinent if sometimes cursory and not always pleasing things to say about fugitive slaves. Delbanco’s incisive analyses of their observations — and, just as important, of their failure to observe — form one of his book’s running themes.

More here.

Costica Bradatan in the Los Angeles Review of Books:

WHAT IF KNOWLEDGE — the real, redeeming variety — is not power, but the opposite of it? If, for instance, to become properly human we need to run away from power as much as we can? Indeed, what if our highest accomplishment in this world came from radical self-effacement, the lowest existential station we could possibly reach?

If there is one trait that all forms of life share, it must be self-assertion. From the simplest to the most complex, all living entities seek to persist in their state and reproduce. And doing so requires pushing relentlessly against other entities, often to the point of annihilating them. That makes life a scene of cruelty of cosmic proportions. But “cruel” may be the wrong word, for it applies human judgment to something that, by definition, is anything but human. The process of life unfolds beyond any human concerns — spontaneously, blindly, tyrannically. Humans are caught up in it just like any other species. Far from having a say in the process, we are used and abused by it — brought into being, instrumentalized, and discarded. We think we fall in love, but that’s just one of the tricks life uses to reproduce itself; we devise some better tool and think ourselves smart, blissfully ignorant that we are just playing life’s game of self-assertion. We live in a comic farce and call it happiness.

When it reaches Homo sapiens self-assertion takes a specific form: power.

More here.

George Dyson at Edge:

All revolutions come to an end, whether they succeed or fail.

The digital revolution began when stored-program computers broke the distinction between numbers that mean things and numbers that do things. Numbers that do things now rule the world. But who rules over the machines?

Once it was simple: programmers wrote the instructions that were supplied to the machines. Since the machines were controlled by these instructions, those who wrote the instructions controlled the machines.

Two things then happened. As computers proliferated, the humans providing instructions could no longer keep up with the insatiable appetite of the machines. Codes became self-replicating, and machines began supplying instructions to other machines. Vast fortunes were made by those who had a hand in this. A small number of people and companies who helped spawn self-replicating codes became some of the richest and most powerful individuals and organizations in the world.

Then something changed. There is now more code than ever, but it is increasingly difficult to find anyone who has their hands on the wheel. Individual agency is on the wane. Most of us, most of the time, are following instructions delivered to us by computers rather than the other way around. The digital revolution has come full circle and the next revolution, an analog revolution, has begun. None dare speak its name.

More here.

Avni Sejpal in the Boston Review:

Avni Sejpal: In your book, An Ordinary Person’s Guide to Empire (2004), you identify a few different pillars of empire: globalization and neoliberalism, militarism, and the corporate media. You write, “The project of corporate globalization has cracked the code of democracy. Free elections, a free press and an independent judiciary mean little when the free market has reduced them to commodities on sale to the highest bidder.” How would you update this today?

Arundhati Roy: That was fourteen years ago! The updates now would include the ways in which big capital uses racism, caste-ism (the Hindu version of racism, more elaborate, and sanctioned by the holy books), and sexism and gender bigotry (sanctioned in almost every holy book) in intricate and extremely imaginative ways to reinforce itself, protect itself, to undermine democracy, and to splinter resistance. It doesn’t help that there has been a failure on the part of the left in general to properly address these issues. In India, caste—that most brutal system of social hierarchy—and capitalism have fused into a dangerous new alloy. It is the engine that runs modern India. Understanding one element of the alloy and not the other doesn’t help. Caste is not color-coded. If it were, if it were visible to the untrained eye, India would look very much like a country that practices apartheid.

Another “update” that we ought to think about is that new technology could ensure that the world no longer needs a vast working class.

More here.

Technology is as inevitable as death.
………………………….. —Roshi Bob

Figure Study: Trinity

—Los Alamos National Laboratory, 1945

They taught them to care & not to care.
The trick of battle lines & national sacrifice.
They are building a bomb in what was a boys’ school
where students are only echoes among the yucca.
The fields grow chainlink & checkpoints.
The only music now comes from concertina wire
humming with caught garbage. Little Boy
is sleeping nannied by armed men & dogs.
Surrounded, coaxed by work lamps to grow
fatter, yielding its inner casing to hands rough
with patriotic fervor. To fill with ghosts yet to be,
apprehensive to birth. Men sleep with rifles on boys’ old cots.
It’s midnight in the Mess & three men huddle
over a children’s game. Drop a ball & swipe the jacks.
A game because, for now, they can take it all back.

by C. Samuel Rees
from EchoTheo Review

Jonathan Liebson in The Atlantic:

On December 21, 1968, writing in the Winnipeg Free Press, the reviewer William Morgan starts out admiring of Alice Munro’s debut story collection. He says that the author, in her fictitious small towns, creates a “strange mixture of physical freedom and emotional claustrophobia.” By the end of that review, however, those same features will come to annoy him. Morgan laments that the “characters and situations are real enough, and yet [they’re] enough the same that an unwanted familiarity seems to develop; they were closing in, making one want to escape.”

What Morgan takes issue with in the collection, others may see as a virtue. Fifty years ago, Dance of the Happy Shades won the Governor General’s Award for Fiction, one of Canada’s most important literary awards (an honor that Munro received twice more on her way to winning a Nobel Prize, in 2013). Compared with the long, stand-alone stories that later became Munro’s trademark, the stories from Shades are leaner in page count, more plot-driven, and more conventional in narrative structure; they also have an essential co-dependency. Like James Joyce’s Dubliners or Sherwood Anderson’s Winesburg, Ohio, the book coalesces around a sense of place—rural southwestern Ontario—as much as it does around overlapping themes. In a setting where many homes lack electricity or running water, many men still make a living off the land, and many housewives must jar their own preserves, Munro’s female protagonists often confront expectations that seem as old, and firmly rooted, as the landscape itself.

More here.

Jocelyn Kaiser and Ann Gibbon in Science:

In early 2017, epidemiologist Rory Collins at the University of Oxford in the United Kingdom and his team faced a test of their principles. They run the UK Biobank (UKB), a huge research project probing the health and genetics of 500,000 British people. They were planning their most sought-after data release yet: genetic profiles for all half-million participants. Three hundred research groups had signed up to download 8 terabytes of data—the equivalent of more than 5000 streamed movies. That’s enough to tie up a home computer for weeks, threatening a key goal of the UKB: to give equal access to any qualified researcher in the world. “We wanted to create a level playing field” so that someone at a big center with a supercomputer was at no more of an advantage than a postdoc in Scotland with a smaller computer and slower internet link, says Oxford’s Naomi Allen, the project’s chief epidemiologist. They came up with a plan: They gave researchers 3 weeks to download the encrypted files. Then, on 19 July 2017, they released a final encryption key, firing the starting gun for a scientific race.

Within a couple of days, one U.S. group had done quick analyses linking more than 120,000 genetic markers to more than 2000 diseases and traits, data it eventually put up on a blog. Only 60,000 markers had previously been tied to disease, says human geneticist Eric Lander, president and director of the Broad Institute in Cambridge, Massachusetts. “[They] doubled that in a week.” Within 2 weeks, others had begun to post draft manuscripts on the bioRxiv preprint site. By now, those data have spawned dozens of papers in journals or on bioRxiv, firming up how particular genes contribute to heart disease, diabetes, Alzheimer’s, and other conditions, as well as genes’ role in shaping personality, depression, birth weight, insomnia, and other traits. More controversially, data from the trove also pointed to DNA markers linked to education level and sexual orientation, stoking long-running controversies about the application of genetics to behavior in people.

More  here.

Amitava Kumar in Powell’s:

In the summer of 1904, Ota Benga was bought in the Congo from slave traders for a pound of salt and a bolt of cloth. The man who purchased him was an American entrepreneur and explorer named Samuel Phillips Verner. Verner was under contract to bring pygmies for display at the St. Louis World Fair. Later, Verner was awarded a gold medal for his services to the young discipline of anthropology.

In 1906, two years after being exhibited at the World Fair, Ota Benga was brought to the Bronx Zoo and locked in a monkey cage to be displayed under a sign saying “African Pygmy.” His teeth had been filed into sharp points, and this was seen as a sign of cannibalism. Ota Benga was a member of the tribe of Mbuti pygmies; he stood less than five feet tall and weighed only 100 pounds. He spoke no English. He arrived at the Bronx Zoo wearing a white linen suit, in the company of Verner, who was broke. Benga had with him a wooden box, a set of arrows, and his pet chimpanzee. Verner had contacted the zoo’s director in the hopes of securing an apartment for Benga on the zoo’s premises. The director of the Bronx Zoo decided it was better to display Benga in the orangutan’s cage. I read somewhere that bones were scattered about the cage to add a whiff of cannibalism. The zoo attracted as many as 40,000 visitors a day.

More here.

Yaneer Bar-Yam in Student Voices:

One of the hardest things to explain is why complex systems are actually different from simple systems. The problem is rooted in a set of ideas that work together and reinforce each other so that they appear seamless: Given a set of properties that a system has, we can study those properties with experiments and model what those properties do over time. Everything that is needed should be found in the data and the model we write down. The flaw in this seemingly obvious statement is that what is missing is realizing that one may be starting from the wrong properties. One might have missed one of the key properties that we need to include, or the set of properties that one has to describe might change over time. Then why don’t we add more properties until we include enough? The problem is that we will be overwhelmed by too many of them, the process never ends. The key, it turns out, is figuring out how to identify which properties are important, which itself is a dynamic property of the system.

To explain this idea we can start from a review of the way this problem came up in physics and how it was solved for that case. The ideas are rooted in an approximation called “separation of scales.”

More here.  [Thanks to Ali Minai. And, yes, I know this article is from 2017.]

Scott Alexander in Slate Star Codex:

In my endorsement of anyone except Trump, I told progressives not to vote Trump because they opposed his policy, and conservatives not to vote Trump because he would cause a backlash that was worse than anything they might get from him. I said that the left thrives by imagining themselves as brave rebels fighting an ignorant, regressive, hateful authority, and that “bringing their straw man to life and putting him in the Oval Office” would be “the biggest gift” they could give the Democrats, and would end up pushing an entire generation further to the left.

I think this is a good broad theory of what’s happening, but it might be worth digging deeper to try to distinguish possible mechanisms.

First, maybe Trump is just such an offensive and aversive figure that people switch sides in disgust. This is a little weird; if you were anti-immigration before Trump, can’t you just say “I hate Trump, but I’m still against immigration”? But maybe people’s minds don’t work that way.

Second, maybe Trump made causes like protectionism and nativism so central to the Republican narrative that they became untenable for Democrats. That is, in 2010, it might have been possible to be an anti-illegal-immigration Democrat (remember, in the early 2000s Hillary supported a border fence), but in 2018, that would signal being a Republican, or at least someone of questionable loyalty to the Democratic Party.

More here.