Sunday 22 March, 2020

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Smartphones could help us track the coronavirus – but at what cost?

This morning’s Observer column

A key principle of control engineering is that you have to be able to measure the variable you’re trying to control. In the case of Covid-19, we currently have no way of accurately measuring how we’re doing, because we’re not able to do enough testing of the population. Dammit, we’re still not even testing frontline medical staff.

I know, I know: this is hard; this thing came out of the blue; we can’t just magic up the resources needed to do extensive public testing out of thin air; etc. But at the same time, every sentient being in the government must know by now that we must find some way of measuring the thing we’re trying to control. How else will we know – other than by counting the number of desperate cases who show up needing intensive care – whether that curve is being flattened or not?

We need a magic bullet. And, miraculously, we seem to have one. It’s called a smartphone…

Yeah, but there’s a downside that we might be living with for the rest of our lives…

Read on

Interestingly, Yuval Noah Harari had an interesting essay on the same lines — “The world after coronavirus” — in the weekend edition of the Financial Times. “Many short-term emergency measures will become a fixture of life”, he writes.

That is the nature of emergencies. They fast-forward historical processes. Decisions that in normal times could take years of deliberation are passed in a matter of hours. Immature and even dangerous technologies are pressed into service because the risks of doing nothing are bigger. Entire countries serve as guinea-pigs in large-scale social experiments. What happens when everybody works from home and communicates only at a distance? What happens when entire schools and universities go online? In normal times, governments, businesses and educational boards would never agree to conduct such experiment. But these aren’t normal times.

In this time of crisis, we face two particularly important choices. The first is between totalitarian surveillance and citizen empowerment. The second is between nationalist isolation and global solidarity.

Yep.


What the Coronavirus crisis is revealing

Extraordinary essay in the New York Times by Mark O’Connell.

In the original Greek, the word apocalypse means simply a revelation, an uncovering. And so there is one sense in which these days are truly, literally, apocalyptic. The world itself is being revealed with a startling and surreal clarity. Much of what is being revealed is ugly: the rot of inequality in the bones of our societies, the lethal inefficiency of free-market capitalism, the bewildering cruelty and stupidity of many of the people in positions of apparent leadership. But there are beautiful things, too, being revealed with great clarity and force. Of these, the one that gives me the most hope in this sad and frightening time is that despite the damage done by the presiding ideology of individualism, there remains a determination to act out of a sense of shared purpose.

On checking, this is probably drawn from his forthcoming book – Notes from an Apocalypse: A Personal Journey to the End of the World and Back.


Quarantine Diary

Given that those of us confined to barracks should have more time on our hands, I’ve decided to keep an audio diary of thoughts and reflections on what we are about to go through. It starts today.


Saturday 22 March, 2020

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The American Cemetery, Madingley this morning. Click on the image for a larger size.


Solitude vs loneliness

As the world struggles to adjust to lockdown, quarantine and social-distancing there’s an interesting and timely book on the horizon. It’s A History of Solitude by my friend and colleague David Vincent, who is one of Britain’s most distinguished social historians. It comes out on April 24. The timing is fortuitous but accidental: David has been working on the book for several years, starting on it after he had finished his previous book, Privacy: A Short History. I haven’t seen it yet, but Terry Eagleton, the literary critic, has and he’s written an interesting review for the Guardian. Snippet:

Solitude is not the same as loneliness. Lonely people feel the need for company, while solitary types seek to escape it. The neatest definition of loneliness, David Vincent writes in his superb new study, is “failed solitude”. Another difference between the two groups is that hermits, anglers, Trappist monks and Romantic poets choose to be alone, whereas nobody chooses to feel abandoned and bereft. Calling yourself “self-partnering”, meaning that you sit in the cinema (should they be open) holding your own hand, may be either a genuine desire for solitude or a way of rationalising the stigma of isolation. The greatest difference of all, however, is that solitude has rarely killed anyone, whereas loneliness can drive you to the grave. As the coronavirus rampages, some of us might now face a choice between physical infection and mental breakdown…


Thank God for experts

Link


Producing vaccines under intense political pressure poses serious risks

How anti-vaxxers win — If any eventual vaccine harms even a tiny percentage of those who get it, “the anti-vaxxers can set back not only this vaccine but all vaccines,” said Barry Bloom, a professor at the Harvard School of Public Health. The anti-vaccine movement has been growing in the United States, and contributed to the country’s worst measles epidemic in 27 years in 2019. (From Politico’s nightly summary.)

This is yet one more reason why Trump is a menace. He keeps talking nonsense and stoking unrealistic expectations. This makes him the second biggest public health risk to the American public. And while we’re on that topic, here’s Larry Lessig:

If in January, Trump had “declared war” on this virus with the resolve of FDR, or Churchill, or even President Thomas J. Whitmore (Independence Day), he would have united the world against this common foe, and for once, the world could wage a war as one, without hesitation, and without regret.

Yet so tiny is the mind of our Idiot King that he could not even glimpse this extraordinary gift. His single focus was on the single indicator that seemed to say that he was, indeed, a genius — the stock market. And so he dissembled and obstructed to the end of faking the market out. Who knows if the man is really stupid enough to have believed that a virus that had brought China to its knees, once discovered to have infected 15 Americans, would “within a couple days go down to close to zero.” It doesn’t matter. The political system had taught Trump that he had the power to distort reality. The economic system has now taught Trump that he can’t distort economic reality. America’s economy — and the worlds’ economy— will now collapse. The election in November will be in midst of a great recession, compounded by unimaginable loss of human life. No President gets re-elected in times like that. Not the good ones. Not even the buffoons.


Remote conferencing with Zoom

Some of my research colleagues and I had a key meeting scheduled for this week and planned some weeks ago. As the University (Cambridge) went into lockdown we obviously couldn’t meet fate-to-face but were reluctant to cancel the discussion. Previously, we would have used conventional phone-conferencing, but I have become so pissed-off with the inadequacies of that medium that I suggested we used Zoom instead.

It was MUCH better. Two things in particular made all the difference: firstly one could see all the participants (as live images in small frames at the top of the screen); and secondly, whenever anyone started to speak, the software foregrounded them. This latter feature wasn’t perfect, but it was generally very effective. And the audio quality was sometimes a bit harsh, but still perfectly comprehensible.

My conclusion: the tech isn’t perfect, but I never want to go back to phone conferences again.


Why modelling is the rational way to make policy in a complex system

The Economist has an excellent explanation of the Imperial College epidemiological model That persuaded the UK government to change tack (though not quickly enough). The modellers

assigned covid-19 a “basic reproduction number” of 2.4. This means that in a population not taking any precautions, and where no one is immune, each case leads, on average, to 2.4 secondary cases.

Under those conditions the model showed the disease infecting 80% of the British population in three to four months. If 4.4% of the people infected became ill enough to be hospitalised and 30% of those deteriorated to the point of needing intensive care, then by mid-April demand for beds in intensive-care units (icus) would outstrip the health service’s “surge” capacity. In May the number of critical patients would be more than 30 times the number of icu beds available. Estimates of the fatality rate in China range from 0.5% to 1.5% of infections. Using a conservative 0.9% for Britain, the model put the death toll by the end of the summer at over half a million.


The Italian tragedy

One of the tragedies of this pandemic is the way it shows how social structures that we generally think of as embodying sociality and stability — extended families with several generations living closely together, for example — can be especially vulnerable. It turns out that Italy has a higher percentage of elderly people than most European countries, and about two-thirds of adults aged 18-35 live with their parents, with many houses containing three generations — which meant they were sitting ducks for Covid-19.


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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Serial Killers: Moore’s Law and the parallelisation bubble

Cory Doctorow had a thoughtful reaction to Sunday’s Observer column, where I cited Nathan Myhrvold’s Four Laws of Software. “Reading it”, he writes,

made me realize that we were living through a parallel computation bubble. The period in which Moore’s Law had declined also overlapped with the period in which computing came to be dominated by a handful of applications that are famously parallel — applications that have seemed overhyped even by the standards of the tech industry: VR, cryptocurrency mining, and machine learning.

Now, all of these have other reasons to be frothy: machine learning is the ideal tool for empiricism-washing, through which unfair policies are presented as “evidence-based”; cryptocurrencies are just the thing if you’re a grifty oligarch looking to launder your money; and VR is a new frontier for the moribund, hyper-concentrated entertainment industry to conquer.

“Parallelizable problems become hammers in search of nails,” Cory continued in an email:

“If your problem can be decomposed into steps that can be computed independent of one another, we’ve got JUST the thing for you — so, please, tell me about all the problems you have that fit the bill?”

This is arguably part of why we’re living through a cryptocurrency and ML bubble: even though these aren’t solving our most pressing problems, they are solving our most TRACTABLE ones. We’re looking for our keys under the readily computable lamppost, IOW.

Which leads Cory (@doctorow) to this “half-formed thought”: the bubbles in VR, machine learning and cryptocurrency are partly explained by the decline in returns to Moore’s Law, which means that parallelizable problems are cheaper/easier to solve than linear ones.

And wondering what the counterfactual would have been like: if we had found a way of extending Moore’s Law indefinitely.

As Moore’s Law runs out of steam, it’ll be back to the future

This morning’s Observer column:

In a lecture in 1997, Nathan Myhrvold, who was once Bill Gates’s chief technology officer, set out his Four Laws of Software. 1: software is like a gas – it expands to fill its container. 2: software grows until it is limited by Moore’s law. 3: software growth makes Moore’s law possible – people buy new hardware because the software requires it. And, finally, 4: software is only limited by human ambition and expectation.

As Moore’s law reaches the end of its dominion, Myhrvold’s laws suggest that we basically have only two options. Either we moderate our ambitions or we go back to writing leaner, more efficient code. In other words, back to the future.

Read on

Raspberry Pi: a great British success story

This morning’s Observer column:

I bought my Pi from the Raspberry Pi store in Cambridge. Across the street (and one floor below) is the Apple store where I had earlier gone to buy a new keyboard for one of my Macs. The cost: £99. So for £15 more, I had a desktop computer perfectly adequate for most of the things I need to do for my work.

The Pi is one of the (few) great British technology success stories of the last decade: sales recently passed the 30m mark. But if you got your news from mainstream media you’d never know…

Read on

Podcasting: will it succumb to the Wu cycle?

This morning’s Observer column:

I’ve just been listening to what I think of as the first real podcast. The speaker is Dave Winer, the software genius whom I wrote about in October. He pioneered blogging and played a key role in the evolution of the RSS site-syndication technology that enabled users and applications to access updates to websites in a standardised, computer-readable format.

And the date of this podcast? 11 June, 2004 – 15 years ago; which rather puts into context the contemporary excitement about this supposedly new medium that is now – if you believe the hype – taking the world by storm. With digital technology it always pays to remember that it’s older than you think.

When he started doing it, Winer called it “audioblogging” and if you listen to his early experiments you can see why. They’re relaxed, friendly, digressive, unpretentious and insightful – in other words an accurate reflection of the man himself and of his blog. He thought of them as “morning coffee notes” – audio meditations about what was on his mind first thing in the morning…

Read on

Kranzberg’s Law

As a critic of many of the ways that digital technology is currently being exploited by both corporations and governments, while also being a fervent believer in the positive affordances of the technology, I often find myself stuck in unproductive discussions in which I’m accused of being an incurable “pessimist”. I’m not: better descriptions of me are that I’m a recovering Utopian or a “worried optimist”.

Part of the problem is that the public discourse about this stuff tends to be Manichean: it lurches between evangelical enthusiasm and dystopian gloom. And eventually the discussion winds up with a consensus that “it all depends on how the technology is used” — which often leads to Melvin Kranzberg’s Six Laws of Technology — and particularly his First Law, which says that “Technology is neither good nor bad; nor is it neutral.” By which he meant that,

“technology’s interaction with the social ecology is such that technical developments frequently have environmental, social, and human consequences that go far beyond the immediate purposes of the technical devices and practices themselves, and the same technology can have quite different results when introduced into different contexts or under different circumstances.”

Many of the current discussions revolve around various manifestations of AI, which means machine learning plus Big Data. At the moment image recognition is the topic du jour. The enthusiastic refrain usually involves citing dramatic instances of the technology’s potential for social good. A paradigmatic example is the collaboration between Google’s DeepMind subsidiary and Moorfields Eye Hospital to use machine learning to greatly improve the speed of analysis of anonymized retinal scans and automatically flag ones which warrant specialist investigation. This is a good example of how to use the technology to improve the quality and speed of an important healthcare service. For tech evangelists it is an irrefutable argument for the beneficence of the technology.

On the other hand, critics will often point to facial recognition as a powerful example for the perniciousness of machine-learning technology. One researcher has even likened it to plutonium. Criticisms tend to focus on its well-known weaknesses (false positives, racial or gender bias, for example), its hasty and ill-considered use by police forces and proprietors of shopping malls, the lack of effective legal regulation, and on its use by authoritarian or totalitarian regimes, particularly China.

Yet it is likely that even facial recognition has socially beneficial applications. One dramatic illustration is a project by an Indian child labour activist, Bhuwan Ribhu, who works for the Indian NGO Bachpan Bachao Andolan. He launched a pilot program 15 months prior to match a police database containing photos of all of India’s missing children with another one comprising shots of all the minors living in the country’s child care institutions.

The results were remarkable. “We were able to match 10,561 missing children with those living in institutions,” he told CNN. “They are currently in the process of being reunited with their families.” Most of them were victims of trafficking, forced to work in the fields, in garment factories or in brothels, according to Ribhu.

This was made possible by facial recognition technology provided by New Delhi’s police. “There are over 300,000 missing children in India and over 100,000 living in institutions,” he explained. “We couldn’t possibly have matched them all manually.”

This is clearly a good thing. But does it provide an overwhelming argument for India’s plan to construct one of the world’s largest facial-recognition systems with a unitary database accessible to police forces in 29 states and seven union territories?

I don’t think so. If one takes Kranzberg’s First Law seriously, then each proposed use of a powerful technology like this has to face serious scrutiny. The more important question to ask is the old Latin one: Cui Bono?. Who benefits? And who benefits the most? And who loses? What possible unintended consequences could the deployment have? (Recognising that some will, by definition, be unforseeable.) What’s the business model(s) of the corporations proposing to deploy it? And so on.

At the moment, however, all we mostly have is unasked questions, glib assurances and rash deployments.

What if AI could write like Hemingway?

This morning’s Observer column:

Last February, OpenAI, an artificial intelligence research group based in San Francisco, announced that it has been training an AI language model called GPT-2, and that it now “generates coherent paragraphs of text, achieves state-of-the-art performance on many language-modelling benchmarks, and performs rudimentary reading comprehension, machine translation, question answering, and summarisation – all without task-specific training”.

If true, this would be a big deal…

Read on