A quarter century of weightlessness

It’s 25 years since my first book The Weightless World was published, back in 1997. We were early adopters of the online world at home, and in my job (journalism for The Independent at the time) I had been reporting on technology companies. So when approached by an agent, I knew what the subject would be. How does it stand up to the test of time?

The headline is that the central metaphor, of economic value becoming increasingly intangible, was spot on. The role of ideas and intangibles in how economies progress has become ever more apparent – watch out for the new Haskel and Westlake book on this shortly. The material intensity of economic output has declined. At the same time, I missed two big issues: energy use and climate change; and the adverse trends in concentration in digital markets & the power of big tech. The tone is more upbeat than it might be if I wrote it now, although to be fair to myself The Weightless World does flag trade-offs and the transition costs of digital adoption.

I’m most impressed with my young self in looking at the chapter headings. It was a time of higher unemployment than now so jobs are a focus, including flexibility and what we now refer to as the gig economy. As one of the jobs chapters points out, the technology offered a lot of potential for changing patterns of work but to date it had operated solely in favour of employers, not individuals. Perhaps the pandemic and WFH will finally shift that balance. Other chapters cover the impact of digital on globalisation, economic geography and clustering in cities, the need for a new social contract, the role of the third sector and reforming government. For example, I was very clear that the need for more and more exchange of ideas would enhance clustering, as has indeed happened over the past quarter century.  I even flag up the increasing scope of increasing returns.

It’s highly embarrassing reading one’s old work, so I’m not going to recommend others go back to it. This post is just to pat myself on the back for having been in on the ground floor of the digital economy. I published the book too early, probably – prescience is no use if nobody pays attention! With luck, though, digital transformation will keep me busy for the next 25 years.

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Here I am in 1996, writing The Weightless World too early

Here I am in 1996, writing The Weightless World too early

 

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How to invent ideas

I found Zorina Khan’s Inventing Ideas: Patents, Prizes and the Knowledge Economy very interesting. It uses an impressive assembly of empirical evidence about inventors, patents, the administrators and recipients of innovation prizes and awards, and industrial exhibitions – largely in the US, UK and France – to support a specific analysis of what enabled the US to become the most innovative and richest industrial nation from the late 19th century on. As she points out, much of the literature asks why Britain was the first country to experience an industrial revolution, so the question itself is distinctive.

Her argument is that compared with Europe, there were “dramatic differences in the new approach to growth that were manifested in early US policies.” The key difference – supported by the mass of evidence – is a far greater emphasis in the US on patents (as a market-oriented innovation system) rather than prizes and awards (an administered system). A second and consequential difference is the preponderance of incremental and commercially successful innovations in the US. “Elites have always mistrusted markets: wealth and influence often lead to the convistion that the insights of the favored fiew can outperform spontaneous co-ordination,” Khan observes. The US was strongly anti-elitist (at least in that era), whereas “the most significant variable affecting whether or not a British inventor received a prize was elite education at Oxford or Cambridge,” neither university at the time focused on technical or scientific excellence.

Along the way to supporting its argument that the marketplace of ideas beats elite technocracy, the book demolishes quite persuasively the recent trend toward innovation prizes as an effective incentive mechanism. Less persuasive is the argument that patent trolling is no greater a problem than it ever was (although there clearly was a lot of litigation over patents in the 19th century).

It also makes the point that European and American patent systems operated differently. The specific institutional details mattered. So the conclusion one could draw is that the underlying elitism of European societies and egalitarianism of the US does more to account for latter’s emergence as technological leader. In which case, the longer term outlook for the US staying at the frontier may be less rosy. In any case, much food for thought in the book, and fascinating empirical and historical detail.

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Taking ideas seriously

In preparation for delivering the 2021 John Urry lecture at Lancaster University on Thursday, I’ve been re-reading the book that introduced me to his work, Economies of Signs and Space, co-authored with Scott Lash. It was published in 1994, but being an economist, and therefore more ignorant of the other social sciences than I ought to be, I had only just found it when I wrote my 1997 The Weightless World. The commonalities in our ideas were striking – more so to me now than I recall them being 25 years ago, although I cite the book.

These included the intuition about the increasing salience of time and space – both books have a ‘cities’ chapter – fragmenting production systems, the importance of the cultural industries, the deficit of institutions lagging behind economic and cultural change. But above all the increasing share of value assigned to the intangible or weightless. They write: “What is increasingly produced are not material objects but signs,” and note the “increasing component of sign-value or image embedded in material objects.”

The lecture this week will pick up on these insights – I think I and they were pretty prescient – to talk about what it means to have an economy of ideas, but will also talk about the need to re-focus on the material foundation of this economy: giant warehouses and energy-guzzling AIs. Oh, and human brains.

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Our robot overlords?

I’ve chatted to Martin Ford about his new book Rule of the Robots for a Bristol Festival of Ideas event – the recording will be out on 6 October.

It’s a good read and quite a balanced perspective on both the benefits and costs of increasingly widespread use of AI, so a useful intro to the debates for anyone who wants an entry into the subject. There are lots of examples of applications with huge promise such as drug discovery. The book also looks at potential job losses from automation and issues such as data bias.

It doesn’t much address policy questions with the exception of arguing in favour of UBI. Regular readers of this blog will know I’m not a fan, as UBI seems like the ultimate Silicon Valley, individualist, solution to a Silicon Valley problem. I’d advocate policies to tilt the direction of automation, as there’s a pecuniary externality: individual firms don’t factor in the aggregate demand effects of their own cost-reduction investments. And also policies that address collective needs – public services, public transport, as well as a fair and sufficiently generous benefits system. No UBI in practice would ever be set high enough to address poverty and the lack of good jobs: if you want to pay everyone anything like average income, you’d have to collect taxes at a level more than average income.

But that debate is what the Bristol event is all about!

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Actually existing AI

For the first time in a year I managed to get abroad for a few days – the Ambrosetti Forum at the Villa D’Este on Lake Como – and apart from the inherent joy of being somewhere beautiful and sunny and foreign, it gave me plenty of reading time. One of the books I polished off is Kate Crawford’s excellent Atlas of AI. It’s a forensic exploration of the unseen structures shaping the way AI is being developed and deployed in the world, and it is fair to say she is prfoundly sceptical about whether ‘actually existing AI’ is serving society broadly as opposed to making a small minority of (mainly) men rich and powerful. “To understand how AI is fundamentally political,” she writes in the introduction, we need to go beyond neural nets and statistical pattern recognition to instead ask what is being optimized, and for whom, and who gets to decide.”

The book starts with the material basis of the industry, in particular the extraction of rare earths and its voracious and growing consumption of energy. We all surely know about the energy appetite of crypto but one point I hadn’t really appreciated is this: “The amount of compute used to train a single AI model has increased by a factor of ten every year.” The next chapter goes on to discuss the extent to which AI depends on low-cost human labour. I think the way Amazon’s Mechanical Turk works is quite well known – a nice book about this was Ghost Work – but this chapter focuses on Amazon warehouses, image-labelling work (“the technical AI research community relies on cheap crowd-sourced labour for many tasks that can’t be done by machine”), and also – nice neologism – ‘fauxtomation’ when tasks are transferred from human workers to human customers: think ‘automated’ checkouts in shops. The chapter has a nice section discussing the role of time in business models: in an evolution of the industrial organisation of time, the continuing automation of economic activity is requiring humans to work ever-faster. The battle is for ‘time sovereignity’.

There is not surprisingly a chapter on data, underlining the point that it is profoundly relational, but also making the point that the reliance on ‘data’ downgrades other forms of knowledge, such as linguistic principles, and how little questioning there is of where it comes from and what it actually measures. I hadn’t realised that many computer science departments have not had ethical review processes on the basis that they do not have human subjects for their research. It’s also a bit of a shocker to realise that some widely used AI databases are palimpsests of older collections of data embedding unpalatable classifications and assumptions.

There’s a similarly shocking chapter on facial recognition – bad enough in the ungoverned way it’s being used but I hadn’t clocked the latest trend of using it to “identify” people’s moods. And the book winds up back at power. As Crawford writes, “We must focus less on ethics and more on power.” I couldn’t agree more. There are a gazillion ethics statements and loads of ethics research but it won’t change anything. I’d add incentives too, but given the concentration of all that compute, understanding the way AI and power structures interact will shape the kind of world we are in 10 years from now. Excellent book.

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