The Economist has an interesting article on how major universities are now having trouble holding on to their machine-learning and AI academics. As the industrial frenzy about these technologies mounts, this is perfectly understandable, though it’s now getting to absurd proportions. The Economist claims, for example, that some postgraduate students are being lured away – by salaries “similar to those fetched by professional athletes” – even before they complete their doctorates. And Uber lured “40 of the 140 staff of the National Robotics Engineering Centre at Carnegie Mellon University, and set up a unit to work on self-driving cars”.
All of which is predictable: we’ve seen it happen before, for example, with researchers who have data-analytics skillsets. But it raises several questions.
The first is whether this brain brain will, in the end, turn out to be self-defeating? After all, the graduate students of today are the professors of tomorrow. And since, in the end, most of the research and development done in companies tends to be applied, who will do the ‘pure’ research on which major advances in many fields depend?
Secondly, and related to that, since most industrial R&D is done behind patent and other intellectual-property firewalls, what happens to the free exchange of ideas on which intellectual progress ultimately depends? In that context, for example, it’s interesting to see the way in which Google’s ownership of Deepmind seems to be beginning to constrain the freedom of expression of its admirable co-founder, Demis Hassabis.
Thirdly, since these technologies appear to have staggering potential for increasing algorithmic power and perhaps even changing the relationship between humanity and its machines, the brain drain from academia – with its commitment to open enquiry, sensitivity to ethical issues, and so on – to the commercial sector (which traditionally has very little interest in any of these things) is worrying.