Anakana Schofield in The Guardian:

The latest TV series by charming, tidy-up guru Marie Kondo has landed on Netflix and while we are all in love with the vibrant folk featured in her show, last week I accidentally entered the damning territory of disagreeing with Kondo’s philosophy – in a tweet that went viral. For while I’d heed Kondo’s “Konmari method” for habits such as folding T-shirts, she is woefully misguided when she says we should get rid of books that don’t give us “joy”. Present tally among the 25,000-plus tweets replying to mine: 65% agree with me, 20% disagree, 3% think we are fighting over a football team and 5% insist Kondo’s position is way more nuanced than I give credit for. The rest insist I am a joyless frump. But be assured that this joyless frump will not be following Kondo’s advice, to essentially hold my books against my teats and left ventricle to see if they spark joy. If my own novels are anything to go by, I should be slightly concerned if the most recent, Martin John, sparked joy in anyone other than a convicted sex offender or a forensic psychiatrist.

…I read in a variety of ways – ebooks, audiobooks – and never mind donating or sharing books. But I can’t imagine what a blank collection of physical books I’d be left with if they had to spark joy. (Goodbye Jelinek, Bernhard and Kafka, hello books with photos of hippo feet.) When I look at my shelves, I marvel at how random books have ended up beside each other. Some are on my shelf on the strength of just one line or a paragraph. Some are gifts, others I found discarded in the street. But every purchase of a book is a gesture of faith in the writer who wrote it. Writers are nothing without readers. Rather than following Kondo’s rules, I’d like to suggest another: it should be obligatory that all living spaces come with built-in bookshelves. (And a hammock.)

More here.

Keswick, There and Back

The Squire strutting down the drive? – No, a partridge off for a stroll.
stone fence; moss; sharp, stiff holly leaves; soft drape of cedar, a still life.
Triplets: Lady in brown, black, white walks between two collies.

The dropped pound chings against the bar’s brass footrail
“Autumn, Autumn, Autumn, Autumn,” an old drunk murmurs to his pint.
Bored tall blonde on high heels, smoke in one hand, drink in the other.

Eight black cows in a line hurrying towards an forgotten open gate.
Beneath dappled cloud masses – a jet’s double streak.
On all sides, mountains.  They don’t look down.

This was written years ago. The year I live in now has long ago turned and heads
inward towards the solstice, and, later, my 85th birthday. I’ve just begun to understand
the old man in the pub talking to his pint of bitter, “Autumn, Autumn, Autumn, Autumn.”
.

by Nils Peterson
from Wanderlust, a narrative map

Elie Dolgin in Nature:

A deep-learning algorithm is helping doctors and researchers to pinpoint a range of rare genetic disorders by analysing pictures of people’s faces. In a paper¹ published on 7 January in Nature Medicine, researchers describe the technology behind the diagnostic aid, a smartphone app called Face2Gene. It relies on machine-learning algorithms and brain-like neural networks to classify distinctive facial features in photos of people with congenital and neurodevelopmental disorders. Using the patterns that it infers from the pictures, the model homes in on possible diagnoses and provides a list of likely options.

Doctors have been using the technology as an aid, even though it’s not intended to provide definitive diagnoses. But it does raise a number of ethical and legal concerns, say researchers. These include ethnic bias in training data sets and the commercial fragmentation of databases, both of which could limit the reach of the diagnostic tool. Researchers at FDNA, a digital-health company in Boston, Massachusetts, first trained the artificial intelligence (AI) system to distinguish Cornelia de Lange syndrome and Angelman syndrome — two conditions with distinct facial features — from other similar conditions. They also taught the model to classify different genetic forms of a third disorder known as Noonan syndrome. Then the researchers, led by FDNA chief technology officer Yaron Gurovich, fed the algorithm more than 17,000 images of diagnosed cases spanning 216 distinct syndromes. When presented with new images of people’s faces, the app’s best diagnostic guess was correct in about 65% of cases. And when considering multiple predictions, Face2Gene’s top-ten list contained the right diagnosis about 90% of the time.

More here.

Stephen Law in Aeon:

When contemporary atheists criticise religious beliefs, they usually criticise beliefs that only crude religious thinkers embrace. Or so some people claim. The beliefs of the sophisticated religious believer, it’s suggested, are immune to such assaults.

Those making this kind of response often appeal to the later work of Ludwig Wittgenstein (1889-1951) – in particular, to remarks he made in Lectures and Conversations on Aesthetics,Psychology and Religious Belief (1967) and Culture and Value (1970), both published posthumously. Wittgenstein made a number of interesting, if rather cryptic, comments about religious belief in these books, and did seem to suggest that such atheist criticisms miss their mark.

What follows is a brief guide to the leading ‘Wittgensteinian’ defences of religious belief, rooted in Wittgenstein’s later work. Note that it’s contentious what Wittgenstein’s later views about religious belief are. The views I discuss are not necessarily Wittgenstein’s own, but attributed to him. Examine these different positions more closely, and we find little to reassure most religious believers that their beliefs are ‘off limits’ so far as atheist criticism is concerned. This is not to say that contemporary atheist criticisms of faith are good – they might not be. It’s just that going Wittgensteinian provides little immunity to such attacks.

More here.

Edith Zimmerman in The Cut:

Recently I’ve been experimenting with mood-modification through temperature extremes (like hot and cold bathing). The heat of a sauna, for instance, supposedly triggers a rush of pleasurable hormones — and so, apparently, does the heat of a chili pepper. I like hot sauce, and this seemed like a good enough excuse to experiment.

For a beginner’s lesson on the mood-altering properties of capsaicin (which is sometimes used in pain relief), I got in touch with Matt Gross, a travel writer and hot pepper expert who’s currently at work on a hot pepper documentary called Hot Pursuit. We met up one recent evening at his Brooklyn apartment to taste increasingly hot peppers while he fielded my questions about what it is that people like about pain.

One rationale is that it’s a form of “controlled risk,” or a way of enjoying the thrill of pain and fear without actually feeling threatened (roller coasters and scary movies do the same thing). Eating spicy peppers also triggers the release of dopamine and endorphins, which are two of the brain’s natural painkillers, and which can result in a kind of stressor-induced “high” (akin to “runner’s high”).

More here.

Akeel Bilgrami in Outlook:

The state in polities broadly described as ‘liberal democracies’ with political economies broadly described as ‘capitalist’ are characterised by a feature that Gramsci called ‘hegemony’. This is a technical term, not to be confused with the loose use of that term to connote ‘power and domination over another’. In Gramsci’s special sense, hegemony means that a class gets to be the ruling class by convincing all other classes that its interests are the interests of all other classes. It is because of this feature that such states avoid being authoritarian. Authoritarian states need to be authoritarian precisely because they lack Gramscian hegemony. It would follow from this that if a state that does possess hegemony in this sense is authoritarian, there is something compulsive about its authoritarianism. Now, what is interesting is that the present government in India keeps boastfully proclaiming that it possesses hegemony in this sense, that it has all the classes convinced that its policies are to their benefit. If so, one can only conclude that its widely rec­orded authoritarianism, therefore, is pathological.

There have been spectacular cases of this authoritarianism such as the recent arrest of five journalists and professors on charges that are virtually nonsensical. The liberal middle class has expressed some anger about these and, given how authoritarian the government has become, that took some courage. But Muslims and Dalits and, quite generally, the unprotected poor suffer from brutality and arbitrary arrest each day and this goes unreported even in the regional media. It is so pervasive that it is not news and it invokes nothing but indifference from the liberal middle class.

More here.

From 52 Insights:

So it’s 2018, and we’re at a pivotal point in the world of cancer. A breakthrough has been made, is this the revolution we’ve all been waiting for. Is the cut and burn era over?

You have to be so careful with this question because the idea of raising false hope is cruel. We’ve seen this time and time again, where there have been breakthroughs but it becomes one of the most shopworn headlines out there. The short answer is yes, this is the breakthrough.  This is a penicillin moment for this disease, which is to say we have fundamentally changed our understanding of the disease and of ourselves and how our immune system interacts or has forever failed to interact with cancer.

We understand that cancer takes advantage of the safety mechanism built into our immune system. Cancer uses a secret handshake to shut down the immune system and to say “I’m cool, I’m a normal body cell don’t attack me.” We count on these secret handshakes or checkpoints for the body not to be attacking ourselves all the time, to not be in a constant state of autoimmunity. The most dangerous thing in our bodies usually is our defences, and that has evolved over 500 million years, and they’re really good. And when they go wrong, it’s terrible.

The safety built into them are necessary. We now know cancer takes advantage of those safety checks and now we know we can block that. That understanding has been sought after for well over one hundred and fifty years. It’s something that puzzled humanity forever. And it was only understood recently.

More here.

Olive Oatman

It was the charcoal they couldn’t stand.
Sister Maddy tried and tried
to get it out—bleach and scrub
till my skin peeled—
but the marks stayed,
black as the stripes
on a hawk’s wing.

Maddy took my mirror away —
each day I saw those marks
took me back,
away from the silk bustled dresses,
the shoes like vises,
the bobs and nods and mouthy words.

Back to his camp by the river.
Smoke blue as morning,
children so quiet
I was afraid at first.
He brought me tied on the back of a horse.
They took my dress,
burned it and laughed,
put me in deerskin—so soft—
laid me on a bed of pine
with the skins circled ‘round,
a smell of earth and sweat and hide.

I choked on the smell,
couldn’t get used to the work.
Water from the river in bark buckets,
firewood in a clump on my back,
scraping the dead things he brought me —
blood, skin, and sinew
torn from the hide
like all I’d left behind.

Read more »

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.