Toxic tech?

This morning’s Observer column:

The headline above an essay in a magazine published by the Association of Computing Machinery (ACM) caught my eye. “Facial recognition is the plutonium of AI”, it said. Since plutonium – a by-product of uranium-based nuclear power generation – is one of the most toxic materials known to humankind, this seemed like an alarmist metaphor, so I settled down to read.

The article, by a Microsoft researcher, Luke Stark, argues that facial-recognition technology – one of the current obsessions of the tech industry – is potentially so toxic for the health of human society that it should be treated like plutonium and restricted accordingly. You could spend a lot of time in Silicon Valley before you heard sentiments like these about a technology that enables computers to recognise faces in a photograph or from a camera…

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As she used to be

From a National Geographic photograph by Eric Kruszewski.

Source

It’s not all bad news. The wonderful (and, sadly, late) Andrew Fallon made an intensive and comprehensive laser-scan of the entire building some years ago. Alexis Madrigal tells the story here. So a reference blueprint (should that be dataprint?) exists from which restorers can work.

Moral crumple zones

This morning’s Observer column:

This mindset prompts Dr Elish to coin the term “moral crumple zone” to describe the role assigned to humans who find themselves in the positions that the Three Mile Island operators, the Air France pilots – and the safety driver in the Uber car – occupied. It describes how responsibility for an action may be wrongly attributed to a human being who had limited control over the behaviour of an automated or autonomous system.

“While the crumple zone in a car is meant to protect the human driver,” she writes, “the moral crumple zone protects the integrity of the technological system, at the expense of the nearest human operator. What is unique about the concept of a moral crumple zone is that it highlights how structural features of a system and the media’s portrayal of accidents may inadvertently take advantage of human operators (and their tendency to become “liability sponges”) to fill the gaps in accountability that may arise in the context of new and complex systems.”

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The ‘horseless carriage’ morphs into the horse

From Kara Swisher:

I will die before I buy another car.

I don’t say that because I am particularly old or sick, but because I am at the front end of one of the next major secular trends in tech. Owning a car will soon be like owning a horse — a quaint hobby, an interesting rarity and a cool thing to take out for a spin on the weekend.

Before you object, let me be clear: I will drive in cars until I die. But the concept of actually purchasing, maintaining, insuring and garaging an automobile in the next few decades?

Finished.

Swisher has form in this area. Many years ago, long before the smartphone, she cancelled her landline phone contract on the grounds that in due course most other people would do so too. (After all, why should phones be tethered to the wall, like goats?) The statistics on how many younger people only have a mobile phone confirm her far-sighted hunch. As far as cars are concerned, though, it’ll probably come down to whether you are an urban or a rural dweller — which partly explains the gilets jaunes crisis in France.

The 5G enigma

This morning’s Observer column:

The dominant company in the market at the moment is Huawei, a $100bn giant which is the world’s largest supplier of telecoms equipment and its second largest smartphone maker. In the normal course of events, therefore, we would expect that the core networks of western mobile operators would have a lot of its kit in them. And initially, that’s what looked like happening. But in recent months someone has pressed the pause button.

The prime mover in this is the US, which has banned government agencies from using Huawei (and ZTE) equipment and called on its allies to do the same. The grounds for this are national security concerns about hidden “backdoors”: it would be risky to have a company so close to the Chinese government building key parts of American critical infrastructure. Last week Huawei filed a lawsuit against the US government over the ban. New Zealand and Australia have obligingly complied with the ban, blocking the use of Huawei’s equipment in 5G networks. And last December BT announced that it was even removing Huawei kit from parts of its 4G network.

Other countries – notably Japan and Germany – have proved less compliant; the German Data Commissioner was even tactless enough to point out that “the US itself once made sure that backdoor doors were built into Cisco hardware”.

The UK’s position is interestingly enigmatic…

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Quote of the day

“When it’s impossible to distinguish facts from fraud, actual facts lose their power. Dissidents can end up putting their lives on the line to post a picture documenting wrongdoing only to be faced with an endless stream of deliberately misleading claims: that the picture was taken 10 years ago, that it’s from somewhere else, that it’s been doctored.

As we shift from an era when realistic fakes were expensive and hard to create to one where they’re cheap and easy, we will inevitably adjust our norms. In the past, it often made sense to believe something until it was debunked; in the future, for certain information or claims, it will start making sense to assume they are fake. Unless they are verified.”

Zeynep Tufecki

After the perfect picture, what?

Photography (in the technical rather than aesthetic sense) was once all about the laws of physics — wavelengths of different kinds of light, quality of lenses, refractive indices, coatings, scattering, colour rendition, depth of field, etc.) And initially, when mobile phones started to have cameras, those laws bore down heavily on them: they had plastic lenses and tiny sensors with poor resolution and light-gathering properties. So the pictures they produced might be useful as mementoes, but were of no practical use to anyone interested in the quality of images. And given the constraints of size and cost imposed by the economics of handset manufacture and marketing there seemed to be nothing much that anyone could do about that.

But this view applied only to hardware. The thing we overlooked is that smartphones were rather powerful handheld computers, and it was possible to write software that could augment — or compensate for — the physical limitations of the cameras.

I vividly remember the first time this occurred to me. It was a glorious late afternoon years ago in Provence and we were taking a friend on a drive round the spectacular Gorges du Verdon. About half-way round we stopped for a drink and stood contemplating the amazing views in the blazing sunlight. I reached for my (high-end) digital camera and fruitlessly struggled (by bracketing exposures) to take some photographs that could straddle the impossibly wide dynamic range of the lighting in the scene .

Then, almost as an afterthought, I took out my iPhone, realised that I had downloaded a HDR app, and so used that. The results were flawed in terms of colour balance, but it was clear that the software had been able to manage the dynamic range that had eluded my conventional camera. It was my introduction to what has become known as computational photography — a technology that has come on in leaps and bounds ever since that evening in Provence. Computational photography, as Benedict Evans puts it in a perceptive essay, ”Cameras that Understand”, means that

“as well as trying to make a better lens and sensor, which are subject to the rules of physics and the size of the phone, we use software (now, mostly, machine learning or ‘AI’) to try to get a better picture out of the raw data coming from the hardware. Hence, Apple launched ‘portrait mode’ on a phone with a dual-lens system but uses software to assemble that data into a single refocused image, and it now offers a version of this on a single-lens phone (as did Google when it copied this feature). In the same way, Google’s new Pixel phone has a ‘night sight’ capability that is all about software, not radically different hardware. The technical quality of the picture you see gets better because of new software as much as because of new hardware.” Most of how this is done is already — or soon will be — invisible to the user. Just as HDR used to involve launching a separate app, it’s now baked into many smartphone cameras, which do it automatically. Evans assumes that much the same will happen with the ‘portrait mode’ and ‘night sight’. All that stuff will be baked into later releases of the cameras.

“This will probably”, writes Evans,

also go several levels further in, as the camera goes better at working out what you’re actually taking a picture of. When you take a photo on a ski slope it will come out perfectly exposed and colour-balanced because the camera knows this is snow and adjusts correctly. Today, portrait mode is doing face detection as well as depth mapping to work out what to focus on; in the future, it will know which of the faces in the frame is your child and set the focus on them”. So we’re heading for a point at which one will have to work really hard to take a (technically) imperfect photo. Which leads one to ask: what’s next?

Evans thinks that a clue lies in the fact that people increasingly use their smartphone cameras as visual notebooks — taking pictures of recipes, conference schedules, train timetables, books and stuff we’d like to buy. Machine learning, he surmises, can do a lot with those kinds of images.

”If there’s a date in this picture, what might that mean? Does this look like a recipe? Is there a book in this photo and can we match it to an Amazon listing? Can we match the handbag to Net a Porter? And so you can imagine a suggestion from your phone: “do you want to add the date in this photo to your diary?” in much the same way that today email programs extract flights or meetings or contact details from emails.“

Apparently Google Lens is already doing something like this on Android phones.

The inescapable infrastructure of the networked world

This morning’s Observer column:

“Quitting smoking is easy,” said Mark Twain. “I’ve done it hundreds of times.” Much the same goes for smartphones. As increasing numbers of people begin to realise that they have a smartphone habit they begin to wonder if they should do something about the addiction. A few (a very few, in my experience) make the attempt, switching their phones off after work, say, and not rebooting them until the following morning. But almost invariably the dash for freedom fails and the chastened fugitive returns to the connected world.

The technophobic tendency to attribute this failure to lack of moral fibre should be resisted. It’s not easy to cut yourself off from a system that links you to friends, family and employer, all of whom expect you to be contactable and sometimes get upset when you’re not. There are powerful network effects in play here against which the individual addict is helpless. And while “just say no” may be a viable strategy in relation to some services (for example, Facebook), it is now a futile one in relation to the networked world generally. We’re long past the point of no return in our connected lives.

Most people don’t realise this. They imagine that if they decide to stop using Gmail or Microsoft Outlook or never buy another book from Amazon then they have liberated themselves from the tentacles of these giants. If that is indeed what they believe, then Kashmir Hill has news for them…

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What makes a ‘tech’ company?

The Blackrock Blog points out that something strange is going on in the investment world.

MSCI and S&P are updating their Global Industry Classification Standards (GICS), a framework developed in 1999, to reflect major changes to the global economy and capital markets, particularly in technology.

Take Google, a company long synonymous with “tech” and internet software. Google parent Alphabet derives the bulk of its revenue from advertising, but also makes money from apps and hardware, and operates side ventures including Waymo, a unit that makes self-driving cars. Decisions about what makes a “tech” giant are not as simple as they once were.

The sector classification overhaul, set in motion last year, will begin in September and affect three of the 11 sector classifications that divide the global stock market. A newly created Communications Services sector will replace a grouping that is currently called Telecommunications Services. The new group will be populated by legacy Telecom stocks, as well as certain stocks from the Information Technology and Consumer Discretionary categories.

What does this mean?

Facebook and Alphabet will move from Information Technology to Communications Services in GICS-tracking indexes. Meanwhile, Netflix will move from Consumer Discretionary to Communications Services. None of what the media has dubbed the FANG stocks (Facebook, Amazon.com, Netflix and Google parent Alphabet) will be classified as Information Technology after the GICS changes, perhaps a surprise to those who think of internet innovation as “tech.” The same applies to China’s BAT stocks (Baidu, Alibaba Group and Tencent). All of these were Information Technology stocks before the changes; none will be after.

Or, in a tabular view:

This change is probably only significant for index funds, but still, it must rather dent the self-image of the ‘tech’ boys to be categorised as merely “communications services”!