Do AIs drive autonomous vehicles?

I’m late to Superintelligence: Paths, Dangers, Strategies by Nick Bostrom, so everybody already knows it’s a super-gloomy warning about the possibility and prospects of machine brains overtaking human brains, setting off on a trajectory we can’t control, and at best indifferent to the interests of humans. Even if the explosion of machine intelligence lies far into the future, Bostrom argues, we should be thinking strategically now about how to manage superintelligence – intellects that outperform the best human minds by a long way, and across a lot of cognitive domains – and ensure it is human-friendly.

The book starts with a warning: “I have tried to make it an easy book to read but I don’t think I have quite succeeded … I tried to produce a book I would have enjoyed reading. This could prove a narrow demographic.” Indeed it is rather a dense read, the author being an immensely knowledgable chap – so much so that I suspect it has been bought many more times than it has been read cover to cover.

The first few chapters describe in much detail the forms superintelligence might take (not just AI but ‘whole brain emulation’ ie building an artificial brain), and the various potential pathways and dynamics for its progress in multiple scenarios. The point, I think, is to establish that this is going to happen for sure at some stage. Slightly alarmingly in this section the book, written in 2014, predicts AI might beat the world Go champion ‘in about a decade’ – this happened in May of course with Deep Mind’s Alpha Go.

The second section is about what values machine superintelligence might have and what rules of morality might possibly be encoded. There are not very cheering sections about how getting this wrong in well-meaning ways could backfire disastrously – for instance if the superintelligences act to use as much resource as possible to achieve their objectives, without regard for the existence of other species or the planet. “The first superintelligence may shape the future of Earth-originating life, could easily have non-anthropomorphic final goals, and would be likely to have instrumental reasons to pursue open-ended resource acquisition.”

There is a short final section, with much less detail than the earlier chapters, urging ‘us’ to think strategically, and co-operate to ensure AI can be managed for human good. In fact, there are almost no specifics here. The book is super-scary without proposing any solutions.

For all the detail about machine intelligence and scenarios for its progress and behaviour, the book is silent on what seem to me to be a some key questions:

  1. Where do superintelligences get their data input? At present there are huge teams of humans putting sensors on the world to provide information to machines. The machines are clearly improving in their ability to read text and to ‘see’ images including in the world. But will this amount to sense perceptions which are so important for human cognition? And could humans fight back if necessary by removing sensors and RFID tags and so on?
  2. How are superintelligences going to be embodied? Will they be mobile physical entities able to, say, mine their own rare minerals or whatever it is they want to do for their own survival and reproduction? Will an AI drive its own autonomous car? If not embodied, could superintelligence actually become a runaway threat?
  3. In a similar vein, superintelligences would need a supporting infrastructure, such as wireless communications. Given that the major transport arteries in the UK don’t have 4G along much of their route, or even 3G in some parts, the superintelligences won’t be driving up the M6 very soon. Maybe the humans could escape to the Scottish highlands or West Wales if the machines run amok, as there is hardly any mobile or fast broadband there at all. Similarly, the power network will be pretty vital – machines (or their batteries) have to be plugged in. We will have to build the machines’ infrastructure. Could we fight back by unplugging them if they turn on us?

These are very interesting questions. For all that it was slightly heavy going at times, I really enjoyed the book because it made me think. Above all, surely this is all too important to be left to technologists, and social scientists need to start thinking seriously about the implications of machine intelligence, so that whatever happens, there is some human design in the outcome.


Agreeing about GDP, disagreeing about the beyond

It’s always a pleasure for me to have a new book about GDP or economic statistics more generally to read (no surprise!) – and this is no longer such a niche taste as it once was. So I very much enjoyed Lorenzo Fioramonti’s The World After GDP: Politics, Business and Society in the Post-Growth Era, a sequel to his Gross Domestic Problem.

The book rightly points to the fact that the many known flaws with GDP as a measure of economic welfare are becoming still more severe. The environmental issues are obvious. There have been longstanding critiques of the omission of much ‘household production’ (although not, as the book seems to suggest, all informal economic activity as it is household services such as cleaning and childcare that are left out; household products such as food is included in the definition of GDP). Still, as the book observes, GDP conceives of firms and governments as productive and households as non-productive and while this has some logic in terms of transactions, it has none in terms of economic welfare.

The digital transformation of the economy is making measurement ever harder: “One of the crucial flaws of GDP is its inability to capture the dynamic value embedded in all sorts of innovations, especially when they reduce costs, distribute access and increase what economists call ‘consumer surplus’.”

Fioramonti also highlights the political economy of GDP – its role as a sole criterion for assessing success or failure, and the growing ‘administrative uses’ such as debt and deficit rules expressed as a percentage of GDP, distorting policies. Unlike Ehsan Masood (in The Great Invention), who argues for a replacement for GDP, Fioramonti favours a suite of indicators. I don’t know which I think is better – there is a strong argument for needing more than one dimension of measurement but there are too many dashboards and sets of goals already. And perhaps people can only pay attention to one summary statistic? Either way, as Fioramonti says here, economic transformations go hand in hand with transformed measurement frameworks.

He makes some points I hadn’t considered and will think about more. For instance, the switch from GNP (the total output of all nationally-owned entities) to GDP (the total output produced within the national territory) provided “an accounting system in support of neoliberal economic globalization,” he writes. That ‘in support of’ suggests intentionality – I don’t know what the historical process was but doubt this was the case. However, it’s an interesting question whether the switch enabled or encouraged globalization (I’ll overlook the n-word).

While there’s much I agree with, there are also points on which I disagree, sometimes strongly. For instance, there is a truly bizarre section on competition, which Fioramonti sees as a wholly negative phenomenon, creating negative externalities. He alludes to competition as ‘random, disorganized interactions’, and yet at the same time describes it as a top down, and centralized process. I’m not sure how he thinks the technological change he refers to elsewhere happens without rivalry between businesses, and clearly sees markets as centralized – but then, how does competition come in to it? He argues also for localized, co-operative production which seems to me a largely romantic dream, which is feasible for some kinds of business (including, perhaps ironically, some ‘sharing’ platforms), but does not scale to an economy capable of providing goods and services to the population as a whole. This section cites Eleanor Ostrom, whose work is indeed marvellous, highlighting the range of possible collective economic institutions, other than markets and centralized states. However, she also underlines that the institutions she explores cannot function beyond a certain scale. The idea that all or many of the products and services in modern economies could be produced at homespun scale is a nonsense. But then, I also think the idea of a post-growth era overlooks the intangible character of modern growth and anyway requires some honesty about what the politics of no-growth would be like – think 10 years of stagnant real earnings, not cosy homesteading.
Still, a certain amount of disagreement adds savour to the book. I really enjoyed reading it, and so will anyone interested in the GDP and measurement debates – and there are plenty of you out there.


Are you ready for the digital future?

Like so many people who enjoyed their previous book, The Second Machine Age by Andrew McAfee and Erik Brynjolfsson, I was excited by the prospect of their latest, Machine, Platform, Crowd: Harnessing Our Digital Future. It’s an interesting and enjoyable book too, but not aimed at readers like me who have long followed their work and the wider literature. Rather, Machine, Platform, Crowd is aimed at the general business audience, and each chapter ends both with a bullet-point chapter summary and with a section of questions for people to think about in the context of their own business and organisations. For example, “What is your machine learning strategy? How far along are you in bringing machine learninginto your ogranization?” or “How and how much are you using the crowd?” or “Are there new ways to use technology for decentralization in your industry that don’t necessarily involve markets?”

The framework of the book is a ‘triple revolution’: ‘machine’ refers to the AI and ML revolution; ‘platform’ is self-explanatory; ‘crowd’ is the growing role of open source, crowdsourcing etc. The argument is that each is in a changing relationship with a counterpart – respectively, the human mind, products, and the ‘core’ or internal expertise and capabilities of organisations. The three sections of the book explore each relationship, mind-machine, product-platform, core-crowd, in turn.

There are lots of nice examples and anecdotes. I loved the literal ‘paperwork mine’, and underground repository of paper records on US Federal Government retirees in a former limestone mine. Completing the paperwork takes the same length of time now as in 1977 (61 days), while the state of Texas, which has digitized its processes, takes 2 days. I think the book will do very well, and is head and shoulders above the typical run of business ‘how to’ books. So I still think Shapiro and Varian’s (1998) Information Rules remains the best single book on the implications of digital technology for business, but ‘MPC’ is a worthy update for the next stage of the digital technologies .


My life in books?

In case anyone is interested in my wider reading habits, I did an interview with the website The Reading Lists. It isn’t all economics (although mostly….)



The Grenfell Tower disaster has shaken Britain. It has exposed as damaging pretence the idea that housing can be left to the ‘free market’, and put the spotlight on one of the many dimensions of social and economic inequalities that are stretched beyond the tolerable.

I’ve been in several conversations about who to blame and how to hold them responsible. No doubt there will be many lawsuits and perhaps criminal charges. I know little about the law, but the discussions sent me back to a wonderful book, Louis Menand’s (2001) The Metaphysical Club. It features the four founding fathers of Pragmatism, Charles Peirce, William James, John Dewey and Oliver Wendell Holmes. There is a section on the concept of tort liability and how US liability law evolved alongside the rapidly industrialising American economy. It’s a very thought-provoking read on the issues and the interaction of the law, social trends, and ethics.

The book is anyway a brilliant intellectual history, and beautifully written.

As for the disaster, justice is vital, but so is action. Britain’s housing policies from building regulations to taxation, and planning rules to housebuilding, must change. National and local politicians are the people responsible for making sure it happens.