Category Archives: Robotics

Friday 22 May, 2020

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So what day is it, actually?

Seen in a tech company office the other day.

Nearly half of Twitter accounts tweeting about Coronavirus are probably bots

Interesting report from NPR.

Nearly half of the Twitter accounts spreading messages on the social media platform about the coronavirus pandemic are likely bots, researchers at Carnegie Mellon University said Wednesday.

Researchers culled through more than 200 million tweets discussing the virus since January and found that about 45% were sent by accounts that behave more like computerized robots than humans.

It is too early to say conclusively which individuals or groups are behind the bot accounts, but researchers said the tweets appeared aimed at sowing division in America.

This vividly reinforces the message in Phil Howard’s new book — Lie machines: How to Save Democracy from Troll Armies, Deceitful Robots, Junk News Operations and Political Operatives, (Yale, 2020) — which I’m currently reading.

Also it hardly needs saying (does it?) but nobody should think that what happens on Twitter provides a guide to what is actually going on in the real world. It’d be good if more journalists realised that.

Main Street in America: 62 Photos That Show How COVID-19 Changed the Look of Everyday Life

Lovely set of pics from an Esquire magazine project. Still photography reaches parts of the psyche that video can’t touch.

Lots of interesting photographs. Worth a look. But give it time.

Everybody knows…

A reader (to whom much thanks) was struck by my (corrected) reference to Joni Mitchell the other day and sent me a clip from Leonard Cohen’s song, Everybody Knows. This bit in particular strikes home:

Everybody knows that the dice are loaded
Everybody rolls with their fingers crossed
Everybody knows that the war is over
Everybody knows the good guys lost
Everybody knows the fight was fixed
The poor stay poor, the rich get rich
That’s how it goes
Everybody knows
Everybody knows that the boat is leaking
Everybody knows that the captain lied
Everybody got this broken feeling
Like their father or their dog just died

We need power-steering for the mind, not autonomous vehicles

Following on from yesterday’s discussion of humans being treated as ‘moral crumple zones’ for the errors of so-called autonomous systems, there’s an interesting article in today’s New York Times on Ben Schneiderman, a great computer scientist (and an expert on human-computer interaction), who has been campaigning for years to get the more fanatical wing of the AI industry to recognise that what humanity needs is not so much fully-autonomous systems as ones that augment human capabilities.

This is a a debate that goes back at least to the 1960s when the pioneers of networked computing like JCR Licklider and Douglas Engelbart argued that the purpose of computers is to augment human capabilities (provide “power-steering for the mind” is how someone once put it) rather than taking humans out of the loop. What else, for example, is Google search than a memory prosthesis for humanity? In other words an augmentation.

This clash of worldviews comes to a head in many fields now — employment, for example. There’s not much argument, I guess, about building machines to do work that is really dangerous or psychologically damaging. Think of bomb disposal, on the one hand, or mindlessly repetitive tasks that in the end sap the humanity out of workers and are very badly paid. These are areas where, if possible, humans should be taken out of the loop.

But autonomous vehicles — aka self-driving cars — represent a moment where the two mindsets really collide. Lots of corporations (Uber, for instance) can’t wait for the moment when they can dispense with those tiresome human drivers. At the moment, they are frustrated by two categories of obstacle.

  1. The first is a lack (still) of technological competence: the kit still isn’t up to the job of managing the complexity of edge cases — where is where the usefulness of humans as crumple zones comes in, because they act as ‘responsibility sponges’ for corporations.

  2. The second is the colossal infrastructural changes that society would have to make if autonomous vehicles were to become a reality. AI evangelists will say that these changes are orders of magnitude less than the changes that were made in order to accommodate the traditional automobile. But nobody has yet made an estimate of the costs to society of changing the infrastructure of cities to accommodate the technology. And of course these costs will be borne more by taxpayers rather than the corporations who profit from the cost-reductions implicit in not employing drivers. It’ll be the usual scenario: the privatisation of profits, and the socialisation of costs.

Into this debate steps Ben Schneiderman., a University of Maryland computer scientist who has for decades warned against blindly automating tasks with computers. He thinks that the tech industry’s vision of fully-automated cars is misguided and dangerous. Robots should collaborate with humans, he believes, rather than replace them.

Late last year, Dr. Shneiderman embarked on a crusade to convince the artificial intelligence world that it is heading in the wrong direction. In February, he confronted organizers of an industry conference on “Assured Autonomy” in Phoenix, telling them that even the title of their conference was wrong. Instead of trying to create autonomous robots, he said, designers should focus on a new mantra, designing computerized machines that are “reliable, safe and trustworthy.”

There should be the equivalent of a flight data recorder for every robot, Dr. Shneiderman argued.

I can see why the tech industry would like to get rid of human drivers. On balance, roads would be a lot safer. But there is an intermediate stage that is achievable and would greatly improve safety without imposing a lot of the social costs of accommodating fully autonomous vehicles. It’s an evolutionary path involving the steady accumulation of the driver-assist technologies that already exist.

I happen to like driving — at least some kinds of driving, anyway. I’ve been driving since 1971 and have — mercifully — never had a serious accident. But on the other hand, I’ve had a few near-misses where lack of attention on my part, or on the part of another driver, could have had serious consequences.

So what I’d like is far more technology-driven assistance. I’ve found cruise-control very helpful — especially for ensuring that I obey speed-limits. And sensors that ensure that when parking I don’t back into other vehicles. But I’d also like forward-facing radar that, in slow-moving traffic, would detect when I’m too close to a car in front and apply the brakes if necessary — and spot a fox running across the road on a dark rainy night. I’d like lane-assist tech that would spot when I’m wandering on a motorway, and all-round video cameras that would overcome the blind-spots in mirrors and a self-parking system. And so on. All of this kit already exists, and if widely deployed would make driving much safer and more enjoyable. None of it requires the massive breakthroughs that current autonomous systems require. No rocket science required. Just common sense.

The important thing to remember is that this isn’t just about cars, but about AI-powered automation generally. As the NYT piece points out, the choice between elimination or augmentation is going to become even more important when the world’s economies eventually emerge from the devastation of the pandemic and millions who have lost their jobs try to return to work. A growing number of them will find they are competing with or working side by side with machines. And under the combination of neoliberal obsessions about eliminating as much labour as possible, and punch-drunk acceptance of tech visionary narratives, the danger is that societies will plump for elimination, with all the dangers for democracy that that could imply.

A note from your University about its plans for the next semester

Dear Students, Faculty, and Staff —

After careful deliberation, we are pleased to report we can finally announce that we plan to re-open campus this fall. But with limitations. Unless we do not. Depending on guidance, which we have not yet received.

Please know that we eventually will all come together as a school community again. Possibly virtually. Probably on land. Maybe some students will be here? Perhaps the RAs can be let in to feed the lab rats?

We plan to follow the strictest recommended guidance from public health officials, except in any case where it might possibly limit our major athletic programs, which will proceed as usual…

From McSweeney’s

Quarantine diary — Day 62

Link

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Think that self-driving cars will eliminate traffic? Think again

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Fascinating paper, “The autonomous vehicle parking problem” by Adam Millard-Ball. In it he: identifies and analyzes parking behavior of autonomous vehicles; uses a traffic simulation model to demonstrate how autonomous vehicles can implicitly coordinate to reduce the cost of cruising for parking, through self-generated congestion; discusses policy responses, including congestion pricing; and argues that congestion pricing should include both a time-based charge for occupying the public right-of-way, and a distance- or energy-based charge to internalizes other externalities.

The Abstract reads:

Autonomous vehicles (AVs) have no need to park close to their destination, or even to park at all. Instead, AVs can seek out free on-street parking, return home, or cruise (circle around). Because cruising is less costly at lower speeds, a game theoretic framework shows that AVs also have the incentive to implicitly coordinate with each other in order to generate congestion. Using a traffic microsimulation model and data from downtown San Francisco, this paper suggests that AVs could more than double vehicle travel to, from and within dense, urban cores. New vehicle trips are generated by a 90% reduction in effective parking costs, while existing trips become longer because of driving to more distant parking spaces and cruising. One potential policy response—subsidized peripheral parking—would likely exacerbate congestion through further reducing the cost of driving. Instead, this paper argues that the rise of AVs provides the opportunity and the imperative to implement congestion pricing in urban centers. Because the ability of AVs to cruise blurs the boundary between parking and travel, congestion pricing programs should include two complementary prices—a time-based charge for occupying the public right-of-way, whether parked or in motion, and a distance- or energy-based charge that internalizes other externalities from driving.

What this suggests is that society — in this case city authorities — should think of urban streets as analogous to radio spectrum. We auction rights to communications companies to operate on specific chinks of the radio spectrum. When autonomous vehicles arrive then those who operate them ought to be treated like radio spectrum users. The one tweak we’d need is that AV operators would be charged not only for the right to use a particular slice of the road ‘spectrum’ but also for the amount of use they make of it.

Quote of the Day

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“Services like Uber and online freelance markets like TaskRabbit were created to take advantage of an already independent work force; they are not creating it. Their technology is solving the business and consumer problems of an already insecure work world. Uber is a symptom, not a cause.”

Louis Hyman, an economic historian, writing in the New York Times

He has a new book coming out soon – Temp: How American Work, American Business, and the American Dream Became Temporary.

So is the spreadsheet an example of job-destroying automation?

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Interesting thought from Tim Harford in his FT column:

Consider an idea dreamt up in 1978, released in October 1979, and so revolutionary that the journalist Steven Levy could write just five years later: “There are corporate executives, wholesalers, retailers, and small business owners who talk about their business lives in two time periods: before and after the electronic spreadsheet.”

Spreadsheet software redefined what it meant to be an accountant. Spreadsheets were once a literal thing: two-page spreads in a paper ledger. Fill them in, and make sure all the rows and columns add up. The output of several spreadsheets would then be the input for some larger, master spreadsheet. Making an alteration might require hours of work with a pencil, eraser, and desk calculator.

Once a computer programmer named Dan Bricklin came up with the idea of putting the piece of paper inside a computer, it is easy to see why digital spreadsheets caught on almost overnight.

But did the spreadsheet steal jobs? Yes and no. It certainly put a sudden end to a particular kind of task — the task of calculating, filling in, checking and correcting numbers on paper spreadsheets. National Public Radio’s Planet Money programme concluded that in the 35 years after Mr Bricklin’s VisiCalc was launched, the US lost 400,000 jobs for book-keepers and accounting clerks.

Meanwhile, 600,000 jobs appeared for other kinds of accountant. Accountancy had become cheaper and more powerful, so people demanded more of it.

Nice illustration of the complexity of the ‘automation = job-killer’ argument.

Impact of autonomous vehicles on (mostly male) employment

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From a Guardian column by Paul Mason:

these battles between regulators and the rent-seeking monopolists who have hijacked the sharing economy are, in the long term, irrelevant. The attempt to drive down cab drivers’ wages and reduce their employment rights to zero are, in their own way, a last gasp of the 20th-century economic thinking.

Because soon there won’t need to be drivers at all. Given that there are 400,000 HGV drivers in the UK, that at least a quarter of Britain’s 2.5 million van drivers are couriers, and that there are 297,000 licensed taxi drivers – that is a big dent in male employment.

The most important question facing us is not whether Uber drivers should have employment rights (they should), but what to do in a world where automation begins to eradicate work. If we accept – as Oxford researchers Carl Frey and Michael Osborne stated in 2013 – that 47% of jobs are susceptible to automation, the most obvious problem is: how are people going to live?

Come for a drive in a Tesla

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Tesla says that the necessary kit for fully-autonomous driving will be installed on all its new cars from now on. But it won’t be activated until a lot more testing has been done. This video provides a glimpse of this brave new future. Ignore the music.

The Chinese economic miracle, Part 2

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The Chinese economic miracle is built on cheap and dextrous manual labour. But labour costs are rising sharply, so…

China already imports a huge number of industrial robots, but the country lags far behind competitors in the ratio of robots to workers. In South Korea, for instance, there are 478 robots per 10,000 workers; in Japan the figure is 315; in Germany, 292; in the United States it is 164. In China that number is only 36.

The Chinese government is keen to change this.

You bet they are. But what happens to all the folks who no longer have work? Stay tuned.

‘Smart’ homes? Not yet

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My Observer comment piece on what the Internet of Things looks like when it’s at home:

There is a technological juggernaut heading our way. It’s called the Internet of Things (IoT). For the tech industry, it’s the Next Big Thing, alongside big data, though in fact that pair are often just two sides of the same coin. The basic idea is that since computing devices are getting smaller and cheaper, and wireless network technology is becoming ubiquitous, it will soon be feasible to have trillions of tiny, networked computers embedded in everything. They can sense changes, turning things on and off, making decisions about whether to open a door or close a valve or order fresh supplies of milk, you name it, the computers communicating with one another and shipping data to server farms all over the place.

As ever with digital technology, there’s an underlying rationality to lots of this. The IoT could make our lives easier and our societies more efficient. If parking bays could signal to nearby cars that they are empty, then the nightmarish task of finding a parking place in crowded cities would be eased. If every river in the UK could tweet its level every few minutes, then we could have advance warning of downstream floods in time to alert those living in their paths. And so on.

But that kind of networking infrastructure takes time to build, so the IoT boys (and they are mostly boys, still) have set their sights closer to home, which is why we are beginning to hear a lot about “smart” homes. On further examination, this turns out mostly to mean houses stuffed with networked kit…

Read on

Potholes on the road to the self-driving future

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This morning’s Observer column:

Somehow I think it’s going to take quite a while to get to self-driving nirvana. For one thing, autonomous vehicles require digital mapping that is an order of magnitude more detailed than anything in Google Streetview. Secondly, those maps need to be continually updated, because even an unexpected new mini-roundabout might confuse the vehicle and cause an accident.

But the biggest obstacle might come from what supposedly kept Harold Macmillan awake at nights – “events, dear boy, events”. Driving in Devon last weekend, I came on a number of temporary traffic lights at roadworks, and wondered how an autonomous vehicle would cope with them. After all, they would not appear on its digital map; and although it would be programmed to look for a red light in a standard position at a junction, it might not “see” a temporary one.

Devon is a ravishing county, but it has one quirk from the motorist’s point of view: it has lots of extremely narrow lanes, most of which have high hedges growing on either side. There are occasional passing places which allow two vehicles to edge past one another. This is fine until a procession of three or four vehicles meets another procession of several cars stuck behind a truck, at which point the only way to reach a solution involves a good deal of human-to-human negotiation. This is something that even the dumbest human is good at, but which will lie beyond the capability of even the smartest machine for some time to come…

Read on.