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”!

What’s in a name?

On my way to Brussels to chair a discussion on Shoshana Zuboff’s The Age of Surveillance Capitalism I fell to reading Leo Marx’s celebrated essay, ”Technology: The Emergence of a Hazardous Concept”, in which he ponders when — and why — the term ‘technology’ emerged. The term — in its modern sense of “the mechanical arts generally” did not enter public discourse until around 1900 “when a few influential writers, notably Thorstein Veblen and Charles Beard, responding to German usage in the social sciences, accorded technology a pivotal role in shaping modern industrial society.”

Marx thinks that, to a cultural historian, some new terms, when they emerge, serve “as markers, or chronological signposts, of subtle, virtually unremarked, yet ultimately far-reaching changes in culture and society.”

His assumption, he writes,

”is that those changes, whatever they were, created a semantic—indeed, a conceptual—void, which is to say, an awareness of certain novel developments in society and culture for which no adequate name had yet become available. It was this void, presumably, that the word technology, in its new and extended meaning, eventually would fill.”

Which brought me back to musing about Zuboff’s new book and why it (and the two or three major essays of hers that preceded it) came as a flash of illumination. Especially the title. What ‘void’ (to use Marx’s idea) does it fill?

On reflection I think the answer lies in the conceptual vacuity of the terms we have traditionally used to describe the phenomenon of digital technology — in particular the trope of “the Fourth Industrial Revolution” beloved of the Davos crowd, or “the digital era” (passim). For one thing these terms are drenched in technological determinism, implying as they do that it’s the technology and its innate affordances that are driving contemporary history. In that sense these cliches are the spiritual heirs of “the age of Machinery” — Thomas Carlyle’s coinage to describe the industrial revolution of his day.

That’s why ‘Surveillance Capitalism’ represents a conceptual breakthrough. It does not assume that our condition is inexorably determined by the innate affordances of digital technology, but by particular ways in which capitalism has morphed in order to exploit it for its own purposes.

So what’s the Killer App for 5G?

If Ben Evans doesn’t know (and he doesn’t, really), then nobody knows.

In 2000 or so, when I was a baby telecoms analyst, it seemed as though every single telecoms investor was asking ‘what’s the killer app for 3G?’ People said ‘video calling’ a lot. But 3G video calls never happened, and it turned out that the killer app for having the internet in your pocket was, well, having the internet in your pocket. Over time, video turned out to be one part of that, but not as a telco service billed by the second. Equally, the killer app for 5G is probably, well, ‘faster 4G’. Over time, that will mean new Snapchats and New YouTubes – new ways to fill the pipe that wouldn’t work today, and new entrepreneurs. It probably isn’t a revolution – or rather, it means that the revolution that’s been going on since 1995 or so keeps going for another decade or more, until we get to 6G.

Shoshana Zuboff’s new book

Today’s Observer carries a five-page feature about Shoshana Zuboff’s The Age of Surveillance Capitalism consisting of an intro by me followed by Q&A between me and the author.

LATER Nick Carr has a perceptive review of the book in the LA Review of Books. John Thornhill also had a good long review in last Saturday’s Financial Times, sadly behind a paywall.

Peak Apple? No: just peak smartphone

This morning’s Observer column:

On 2 January, in a letter to investors, Tim Cook revealed that he expected revenues for the final quarter of 2018 to be lower than originally forecast.

Given that most of Apple’s revenues come from its iPhone, this sent the tech commentariat into overdrive – to the point where one level-headed observer had to point out that the sky hadn’t fallen: all that had happened was that Apple shares were down a bit. And all this despite the fact that the other bits of the company’s businesses (especially the watch, AirPods, services and its retail arm) were continuing to do nicely. Calmer analyses showed that the expected fall in revenues could be accounted for by two factors: the slowdown in the Chinese economy (together with some significant innovations by the Chinese internet giant WeChat); and the fact that consumers seem to be hanging on to their iPhones for longer, thereby slowing the steep upgrade path that had propelled Apple to its trillion-dollar valuation.

What was most striking, though, was that the slowdown in iPhone sales should have taken journalists and analysts by surprise…

Read on

Media credulity and AI hype

This morning’s Observer column:

Artificial intelligence (AI) is a term that is now widely used (and abused), loosely defined and mostly misunderstood. Much the same might be said of, say, quantum physics. But there is one important difference, for whereas quantum phenomena are not likely to have much of a direct impact on the lives of most people, one particular manifestation of AI – machine-learning – is already having a measurable impact on most of us.

The tech giants that own and control the technology have plans to exponentially increase that impact and to that end have crafted a distinctive narrative. Crudely summarised, it goes like this: “While there may be odd glitches and the occasional regrettable downside on the way to a glorious future, on balance AI will be good for humanity. Oh – and by the way – its progress is unstoppable, so don’t worry your silly little heads fretting about it because we take ethics very seriously.”

Critical analysis of this narrative suggests that the formula for creating it involves mixing one part fact with three parts self-serving corporate cant and one part tech-fantasy emitted by geeks who regularly inhale their own exhaust…

Read on

The real significance of the Apple slide

Apart from the fact that the Chinese economy seems to be faltering and collateral damage from Trump’s ‘trade war’ what the slide signals is that the smartphone boom triggered by Apple with the iPhone is ending because we’re reaching a plateau and apparently there’s no New New Thing in sight. At any rate, that’s Kara Swisher’s take on it:

The last big innovation explosion — the proliferation of the smartphone — is clearly ending. There is no question that Apple was the center of that, with its app-centric, photo-forward and feature-laden phone that gave everyone the first platform for what was to create so many products and so much wealth. It was the debut of the iPhone in 2007 that spurred what some in tech call a “Cambrian explosion,” a reference to the era when the first complex animals appeared. There would be no Uber and Lyft without the iPhone (and later the Android version), no Tinder, no Spotify.

Now all of tech is seeking the next major platform and area of growth. Will it be virtual and augmented reality, or perhaps self-driving cars? Artificial intelligence, robotics, cryptocurrency or digital health? We are stumbling in the dark.

Yep. Situation normal, in other words.

How companies are addressing machine learning

From an O’Reilly newsletter:

In a recent O’Reilly survey, we found that the skills gap remains one of the key challenges holding back the adoption of machine learning. The demand for data skills (“the sexiest job of the 21st century”) hasn’t dissipated—LinkedIn recently found that demand for data scientists in the US is “off the charts,” and our survey indicated that the demand for data scientists and data engineers is strong not just in the US but globally.

With the average shelf life of a skill today at less than five years and the cost to replace an employee estimated at between six and nine months of the position’s salary, there’s increasing pressure on tech leaders to retain and upskill rather than replace their employees in order to keep data projects (such as machine learning implementations) on track. We’re also seeing more training programs aimed at executives and decision makers, who need to understand how these new ML technologies can impact their current operations and products.

Beyond investments in narrowing the skills gap, companies are beginning to put processes in place for their data science projects, for example creating analytics centers of excellence that centralize capabilities and share best practices. Some companies are also actively maintaining a portfolio of use cases and opportunities for ML.

Note the average shelf-life of a skill and then ponder why the UK government is not boosting the Open University.

What the Internet tells us about human nature

This morning’s Observer column:

When the internet first entered public consciousness in the early 1990s, a prominent media entrepreneur described it as a “sit up” rather than a “lean back” medium. What she meant was that it was quite different from TV, which encouraged passive consumption by a species of human known universally as the couch potato. The internet, some of us fondly imagined, would be different; it would encourage/enable people to become creative generators of their own content.

Spool forward a couple of decades and we are sadder and wiser. On any given weekday evening in many parts of the world, more than half of the data traffic on the internet is accounted for by video streaming to couch potatoes worldwide. (Except that many of them may not be sitting on couches, but watching on their smartphones in a variety of locations and postures.) The internet has turned into billion-channel TV.

That explains, for example, why Netflix came from nowhere to be such a dominant company. But although it’s a huge player in the video world, Netflix may not be the biggest. That role falls to something that is rarely mentioned in polite company, namely pornography…

Read on

Reflections on AlphaGoZero

Steven Strogatz in the New York Times:

All of that has changed with the rise of machine learning. By playing against itself and updating its neural network as it learned from experience, AlphaZero discovered the principles of chess on its own and quickly became the best player ever. Not only could it have easily defeated all the strongest human masters — it didn’t even bother to try — it crushed Stockfish, the reigning computer world champion of chess. In a hundred-game match against a truly formidable engine, AlphaZero scored twenty-eight wins and seventy-two draws. It didn’t lose a single game.

Most unnerving was that AlphaZero seemed to express insight. It played like no computer ever has, intuitively and beautifully, with a romantic, attacking style. It played gambits and took risks. In some games it paralyzed Stockfish and toyed with it. While conducting its attack in Game 10, AlphaZero retreated its queen back into the corner of the board on its own side, far from Stockfish’s king, not normally where an attacking queen should be placed.

Yet this peculiar retreat was venomous: No matter how Stockfish replied, it was doomed. It was almost as if AlphaZero was waiting for Stockfish to realize, after billions of brutish calculations, how hopeless its position truly was, so that the beast could relax and expire peacefully, like a vanquished bull before a matador. Grandmasters had never seen anything like it. AlphaZero had the finesse of a virtuoso and the power of a machine. It was humankind’s first glimpse of an awesome new kind of intelligence.

Hmmm… It’s important to remember that board games are a very narrow domain. In a way it’s not surprising that machines are good at playing them. But it’s undeniable that AlphaGoZero is remarkable.