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The three structural trends shaping the AI crisis in higher education

  1. The sociotechnical transformation of AI. It’s not simply that the technology is improving, it’s that the space for reflexivity is diminishing because the burden of articulation in chatbots is going down, inline automation tools are being built into everything and wearable AI blurs the boundary between human and technology.
  2. The political economy of the bubble. Either the investment bubble will burst, ranging from a ‘correction’ through to a systemic crisis, or the big AI labs will go to IPO. In either case there will be a new attention on business fundamentals and likely many firms getting destroyed in the process. It means that current offers aren’t stable (particularly from smaller startups) and that current pricing models will without a doubt change significantly.
  3. The political economy of higher education. In the UK context there’s a financial crisis in the sector which is going to get progressively worse. If we’re moving towards a post-pandemic economy defined by ecological and economic volatility globally then higher education will be under structural attack. It will be very difficult to reopen funding settlements while degree-based models contingent on the expectation of economic advantage will rapidly struggle if degrees no longer offer any advantage

What do I think follows from these for what universities do under present conditions?

  • We can’t lock in reliably until the post-crash/IPO pricing models are much clearer than they are now. Otherwise we’re embedding products for we can reasonably expect the prices to be ratcheted up a few years down the line.
  • The prospect for securing the existing assessment system is extremely limited in the medium term and the long term. It’s not going to be possible to separate out technological practice from non-technological practice in the manner which assessment security presupposes. This means that we urgently need to begin working towards assessment reform.
  • The manner in which we respond to the first two challenges will be shaped by the financial and political pressures the sector is under. A dash for productivity through automation risks locking in unreliable system and incurring much greater costs later, as well as further undermining assessment integrity in a way which accelerates the declining (perceived) value of our degrees. A failure to address assessment integrity (and to be seen to do so) furthermore hands ammunition to critics of the sector for whom ‘ChatGPT degrees’ will figure alongside ‘woke degrees’ as economc criticism fuses with culture war criticism.

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