Wednesday 19 August, 2020

Quote of the Day

“He is the man who sits in the outer office of the White House hoping to hear the President sneeze”.

  • H.L. Mencken, writing about the Vice President, 29 January 1956.

Musical alternative to the morning’s radio news

Anne-Sophie Mutter, Daniel Barenboim, Yo-Yo Ma:
Beethoven: Triple Concerto in C Major, Op. 56 No. 2

5 minutes and 22 seconds of pure bliss.

Link

Note: I’ve decided that the embedded links that I’ve been providing up to now create more problems for some readers than they’re worth. So henceforth each musical interlude will just have a simple URL link. Often, simplest is best.


A European at Stanford

Terrific New Yorker profile of the Dutch politician (and former MEP) Marietje Schaake and what she found when she entered the belly of the Silicon Valley beast.

In conversation and lectures, Schaake often describes herself as an alien, as if she were an anthropologist from a distant world studying the local rites of Silicon Valley. Last fall, not long after she’d settled in, she noticed one particularly strange custom: at parties and campus lectures, she would be introduced to people and told their net worth. “It would be, like, ‘Oh, this is John. He’s worth x millions of dollars. He started this company,’ ” she said. “Money is presented as a qualification of success, which seems to be measured in dollars.” Sometimes people would meet her and launch directly into pitching her their companies. “I think people figure, if you’re connected with Stanford, you must have some interest in venture capital and startups. They don’t bother to find out who you are before starting the sales pitch.”

These experiences spoke to a pervasive blurring between the corporate and the academic, which she saw almost everywhere at Stanford. The university is deeply embedded in the corporate life of Silicon Valley and has been directly enriched by many of the companies that Schaake would like to see regulated more heavily and broken apart; H.A.I., according to one of its directors, receives roughly thirteen per cent of its pledged gifts from tech firms, and a majority of its funding from individuals and companies. The names of wealthy donors on buildings and institutes,the department chairs endowed by corporations, the enormous profits from high tuition prices—none of this happened at her alma mater, the University of Amsterdam, where tuition is highly subsidized and public funding supports the operating expenses of the university. (The University of Amsterdam, of course, is not internationally known as an incubator of startups and a hotbed of innovation.) Beyond Stanford, the contrasts seemed just as stark. Roughly sixty per cent of housing in Amsterdam is publicly subsidized. The main street running through Palo Alto, by contrast, is lined with dozens of old R.V.s, vans, and trailers, in which many semi-homeless service workers live. The public middle school in Menlo Park, where Schaake now resides, has students who are homeless, although the area’s average home value is almost $2.5 million.

When I first heard that she was going to Stanford, I feared for her sanity. Having read this, I think she’ll be ok. Her bullshit detector is still in good working order.


Scream if you want to go faster: Johnson in Cummingsland

This is my long read of the day. Terrific essay by Rachel Coldicutt

The emergence of a patchwork of UK innovation initiatives over the last few months is notable. Rather than fiddling with increments of investment, there is a commitment to large-scale, world-leading innovation and enthusiasm for the potential of data.

But there is also a culture of opacity and bluster, a repeated lack of effectiveness, and a tendency to do secret deals with preferred suppliers. Taken together with the lack of a public strategy, this has led to a lot of speculation, a fair few conspiracy theories, and a great deal of concern about the social impact of collecting, keeping, and centralising data.

But it seems very possible that there is actually no big plan — conspiratorial or otherwise. In going through speeches and policy documents, I have found no vision for society —save the occasional murmur of “Levelling Up” — and plenty of evidence of a fixation with the mechanics of government.

This is a technocractic revolution, not a political one, driven by a desire to obliterate bureaucracy, centralise power, and increase improvisation.

And this obsession with process has led to a complete disregard for outcomes.

The thing about Cummings — and the data-analytics crowd generally — is that they know nothing of how society actually works, and subscribe to a crippled epistemology which leads them to think that the more data you have, the more perfect your knowledge of the world.

Actually, most of them don’t even realise they have an epistemology.


Furloughed Brits got paid not to work—but two-thirds of them worked anyway

From Quartz:

Economists at the universities of Oxford, Zurich, and Cambridge looked into the UK furlough program, which supports one-third of the country’s workforce, accounting for more than 9 million jobs, furloughed by mid-June 2020. Under the scheme, the UK government pays workers up to 80% of their salary for a limited period of time, allowing companies to retain them without paying them—though companies were allowed to top up the government money.

Until July 1st, the plan also specifically prohibited workers from working for their employers when on the scheme. But the researchers, who surveyed over 4,000 people in two waves in April and May 2020, discovered a striking fact: Only 37% of furloughed workers reported doing no work at all for their employers during that time.

In some sectors, the imperative to work definitely came from employers. In the the sector termed “computer and mathematical,” 44% of those surveyed said they had been asked to work despite being furloughed.

But it also seems that many employees chose to work because they wanted to. Two-thirds of all workers said they had done some work despite being on furlough, even though only 20% were actually asked to. Perhaps unsurprisingly, those on higher salaries, those able to work from home, and those with the most flexible contracts were most likely to do some work.


One in five college students don’t plan to go back this fall

As the coronavirus pandemic pushes more and more universities to switch to remote learning — at least to start — 22% of college students across all four years are planning not to enroll this fall, according to a new College Reaction/Axios poll.

Among other things, the report claims that 20% of Harvard undergraduates have decided to defer for a year. Harvard (a hedge fund with a nice university attached) can ride out that kind of dropout, but many poorer institutions will struggle.

Source: Axios


Summer books #8

Puligny-Montrachet: Journal of a Village in Burgundy by Simon Loftus, Daunt Books, 2019.

If you like France, or wine, or (like me) both then you’ll enjoy this eccentric but utterly charming social history of the village (well, pair of villages) from which some of the country’s finest dry white wine comes. Loftus is a very good social historian, and his account of what are, in most respects, unglamorous villages is both affectionate and unsentimental. Some good friends of mine, when driving home to Holland from Provence, always used to have an overnight stop in Puligny, from which they would depart the following morning with a car boot full of the most wonderful wine. My fond hope is that, when the plague recedes a bit, we might one day do the same.


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Tuesday 18 August, 2020

Dusk

That magical moment between daylight and darkness.

Click on the image for a bigger version.


Quote of the Day

“The convent taught me only that if you spit on a pencil eraser it will erase ink.”


Musical alternative to the morning’s radio news

Paul Brady sings ‘Arthur McBride’, an Irish folk song variously categorised as an “anti-recruiting” song, a specific form of anti-war song, or more broadly as a protest song. Planxty also has a lovely version of it.

Link


Thinking about tech regulation

This diagram comes from an interesting article, “Law and Technology Realism” by Thibault Schrepel.

While it is commonly accepted that technology is deterministic, I am under the impression that a majority of “Law and Technology” scholars also believe that technology is non-neutral. It follows that, according to this dominant view, (1) technology drives society in good or bad directions (determinism), and that (2) certain uses of technology may lead to the reduction or enhancement of the common good (non-neutrality). Consequently, this leads to top-down tech policies where the regulator has the impossible burden of helping society control and orient technology to the best possible extent.

This article is deterministic and non-neutral.

But, here’s the catch. Most of today’s doctrine focuses almost exclusively on the negativity brought by technology (read Nick Bostrom, Frank Pasquale, Evgeny Morozov). Sure, these authors mention a few positive aspects, but still end up focusing on the negative ones. They’re asking to constrain technology on that sole basis. With this article, I want to raise another point: technology determinism can also drive society by providing solutions to centuries-old problems. In and of itself. This is not technological solutionism, as I am not arguing that technology can solve all of mankind’s problems, but it is not anti-solutionism either. I fear the extremes, anyway.

Not sure I agree with his methodological recommendations at the end, but this is an interesting way of thinking about the regulation problem.


Challenging the epistemological imperialism of ‘Computer Science’

Randy Connolly has written an extraordinary article in the August issue of Communications of the ACM on “Why Computing Belongs Within the Social Sciences”. It’s a really interesting and important essay, about which I will be writing more. But for now, here’s the trailer.

Link


Jack Shafer: stop fretting about Trump’s bluffing on postal voting and get your vote in early

Typically robust Shafer column:

If you’re still worried about the disenfranchisement of the 76 percent of eligible voters who have the right to cast their ballot by mail, there are practical things you can do as an individual besides tweeting anxiously about Trump. The progressives at Democracy Docket recommend that in addition to using special drop boxes, you avoid the Election Day crowds by taking part in the early, in-person voting offered in 41 states. Some states even offer weekend voting. They also suggest you participate in the organized collection of ballots, which some states allow. (Trump assails organized collection as “ballot harvesting.”)

Other things you can do to increase the tabulated vote: Request your absentee ballot at the earliest date possible and return it in person, by mail or secure dropoff as soon as you can. If you live in a state that sends ballots to all registered voters, complete yours and return it promptly. Also, use the USPS sparingly in the three weeks before the election to liberate capacity. Pay your bills via the web. Don’t send postcards. Place phone calls instead of sending birthday cards. Send packages through FedEx or UPS.

Do what you can—if only to call Trump’s postal bluff.

I like Shafer’s brusque, no-nonsense style. Which is why I always read him.


Summer books #7

Magic Mobile by Michael Frayn.

This is lovely. I bought it at the beginning of lockdown. It’s a “no-fuss, non-digital entertainment system”, complete with 35 “pre-loaded new text files” by one of Britain’s greatest playwrights and humourists. No batteries required. Makes a lovely gift for non-techies, I’ve discovered.


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Sunday 26 January, 2020

What the Clearview AI story means

This morning’s Observer column:

Ultimately, the lesson of Clearview is that when a digital technology is developed, it rapidly becomes commodified. Once upon a time, this stuff was the province of big corporations. Now it can be exploited by small fry. And on a shoestring budget. One of the co-founders paid for server costs and basic expenses. Mr Ton-That lived on credit-card debt. And everyone worked from home. “Democracy dies in darkness” goes the motto of the Washington Post. “Privacy dies in a hacker’s bedroom” might now be more appropriate.

Read on

UPDATE A lawsuit — seeking class-action status — was filed this week in Illinois against Clearview AI, a New York-based startup that has scraped social media networks for people’s photos and created one of the biggest facial recognition databases in the world.


Privacy is a public good

Shoshana Zuboff in full voice:

”The belief that privacy is private has left us careening toward a future that we did not choose, because it failed to reckon with the profound distinction between a society that insists upon sovereign individual rights and one that lives by the social relations of the one-way mirror. The lesson is that privacy is public — it is a collective good that is logically and morally inseparable from the values of human autonomy and self-determination upon which privacy depends and without which a democratic society is unimaginable.”

Great OpEd piece.


The winding path


Why the media shouldn’t underestimate Joe Biden

Simple: Trump’s crowd don’t. They think he’s the real threat. (Which explains the behaviour that’s led to Trump’s Impeachment.) David Brooks has some sharp insights into why the chattering classes are off target About this.

It’s the 947th consecutive sign that we in the coastal chattering classes have not cured our insularity problem. It’s the 947th case in which we see that every second you spend on Twitter detracts from your knowledge of American politics, and that the only cure to this insularity disease is constant travel and interviewing, close attention to state and local data and raw abject humility about the fact that the attitudes and academic degrees that you think make you clever are actually the attitudes and academic degrees that separate you from the real texture of American life.

Also, the long and wide-ranging [NYT interview)(https://www.nytimes.com/interactive/2020/01/17/opinion/joe-biden-nytimes-interview.html) with him is full of interesting stuff — like that he thinks that Section 230 of the Communications Decency Act (that’s the get-out-of-gaol card for the tech companies) should be revoked. I particularly enjoyed this observation by Brooks: “ Jeremy Corbyn in Britain and Bernie Sanders here are a doctoral student’s idea of a working-class candidate, not an actual working person’s idea of one.”


Linkblog

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We shape our tools, and afterwards…

In his provocative LARB piece on the intrinsic conservatism of machine learning, Cory Doctorow pointed me to “Instant Recall”, Molly Sauter’s lovely essay, about how the Web has given us “a suite of products and services to programmatically induce reminiscence.”

Apps like Timehop, which presents time-traveled posts from across your social media profiles, or Facebook’s “On This Day” Memories, are attempts to automate and algorithmically define reminiscence, turning the act of remembering into a salable, scalable, consumable, trackable product suite. As the work of memory keeping is offshored, Instagram by Instagram, to social media companies and cloud storage, we are giving up the work of remembering ourselves for the convenience of being reminded.

What’s going on, Sauter says, is that we are being algorithmically fed virtual ‘madelaines’ (those buttery cakes that when when dipped in hot tea were the catalyst for the memories that make up Proust’s À la recherche du temps perdu.) She contrasts this with psychologist Dan McAdams’s contention that remembering is a generative, creative process that is essential for a happy life. What’s important, McAdams argues, is

the creation and maintenance of life narratives, dynamically evolving situated performances that integrate lives in time, providing “an understandable frame for disparate ideas, character, happenings, and other events that were previously set apart.” These stories are subject to constant additive revision, as through living we continually add more material and revise the material available to us, rethinking and rewriting memories as we age. The process of remembering memories rewrites them, revises them, and this ability to re-envision ourselves is a central part of the creation of seemingly stable life narratives that allow for growth and change.

Sauter argues that if we were, somehow, to lose this ability “to both serendipitously and intentionally encounter and creatively engage with our memories, perhaps we would then also lose that re-visionary ability, leaving us narratively stranded amidst our unchanging, unconnected memories”.

It’s a great essay, well worth reading in full. What I like most about it is the way it reminds one of the deeper ways in which digital technology is changing us. “We shape our tools”, as one of Marshall McLuhan’s buddies put it, “and afterwards they shape us“.

In a way, Mark Twain was right when he said that “the older I get, the more clearly I remember things that never happened”.

US immigration uses Google Translate to scan people’s social media for ‘bad’ posts

This is not a good idea. And in contravenes Google’s own advice — which is that anyone using its translation technology add a disclaimer that translated text may not be accurate.

According to a report from ProPublica, USCIS uses these tools to help evaluate whether refugees should be allowed into the US. In so doing, agency personnel are putting their trust in an untrustworthy algorithm to make entry decisions that may have profound consequences for the health and welfare of those seeking admission to the country.

“The translation of these social media posts can mean life or death for refugees seeking to reunite with their family members,” said Betsy Fisher, director of strategy for the International Refugee Assistance Project (IRAP),” in an email to The Register. “It is dangerous to rely on inadequate technology to inform these unreasonable procedures ostensibly used to vet refugees.”

To demonstrate the inaccuracy of Google Translate, ProPublica asked Mustafa Menai, who teaches Urdu at the University of Pennsylvania, to translate a Twitter post written in Urdu. By Menai’s estimation, an accurate English translation would be, “I have been spanked a lot and have also gathered a lot of love (from my parents).”

Google Translate’s rendering of the post is, “The beating is too big and the love is too windy.”

The moral: Translate is wonderful; but don’t bet your life on it.

Source: The Register

Excavating AI

Fabulous essay by Kate Crawford and Trevor Paglen, uncovering the politics and biases embedded in the guge image databases that have been used for training machine learning software. Here’s how it begins:

You open up a database of pictures used to train artificial intelligence systems. At first, things seem straightforward. You’re met with thousands of images: apples and oranges, birds, dogs, horses, mountains, clouds, houses, and street signs. But as you probe further into the dataset, people begin to appear: cheerleaders, scuba divers, welders, Boy Scouts, fire walkers, and flower girls. Things get strange: A photograph of a woman smiling in a bikini is labeled a “slattern, slut, slovenly woman, trollop.” A young man drinking beer is categorized as an “alcoholic, alky, dipsomaniac, boozer, lush, soaker, souse.” A child wearing sunglasses is classified as a “failure, loser, non-starter, unsuccessful person.” You’re looking at the “person” category in a dataset called ImageNet, one of the most widely used training sets for machine learning.

Something is wrong with this picture.

Where did these images come from? Why were the people in the photos labeled this way? What sorts of politics are at work when pictures are paired with labels, and what are the implications when they are used to train technical systems?

In short, how did we get here?

The authors begin with a deceptively simple question: What work do images do in AI systems? What are computers meant to recognize in an image and what is misrecognised or even completely invisible? They examine the methods used for introducing images into computer systems and look at “how taxonomies order the foundational concepts that will become intelligible to a computer system”. Then they turn to the question of labeling: “how do humans tell computers which words will relate to a given image? And what is at stake in the way AI systems use these labels to classify humans, including by race, gender, emotions, ability, sexuality, and personality?” And finally, they turn to examine the purposes that computer vision is meant to serve in our society and interrogate the judgments, choices, and consequences of providing computers with these capacities.

This is a really insightful and sobering essay, based on extensive research.

Some time ago Crawford and Paglen created an experimental website — ImageNet Roulette — which enabled anyone to upload their photograph and then pulled up from the ImageNet database how the person would be classified based on their photograph. The site is now offline, but the Guardian journalist Julia Carrie Wong wrote an interesting article about it recently in the course of which she investigated how it would classify/describe her from her Guardian byline photo. Here’s what she found.

Interesting ne c’est pas? Remember, this is the technology underpinning facial recognition.

Do read the whole thing.