AI will force change in research assessment - Research Professional News
Ah, the Coalition for Advancing Research Assessment has finally noticed that AI is making a mess of their neat little boxes. Their grand insight? That AI tools are making it 'harder to disentangle the contribution of researchers from technology' in funding proposals. Brilliant. So after years of academia pretending that AI was just another tool like a calculator, they're now discovering that when a large language model writes half the grant proposal, it's a bit tricky to figure out who deserves the Nobel. The solution? Shift towards 'recognizing processes and diverse contributions' – which in academia-speak means 'we have no idea how to evaluate this, so let's make the criteria so vague that everyone's a winner.'
Meanwhile, the labs that actually built these models are laughing all the way to the bank. While research councils agonise over whether to credit the grad student or the transformer, frontier AI companies are busy absorbing the brightest minds and patenting the very techniques that made assessment difficult. The Coalition's call for change is about as proactive as rearranging deck chairs on the Titanic – sure, the new layout is nicer, but the iceberg of capability is already upon us. One suspects the real effect will be a flurry of committees, a white paper or two, and then business as usual until the next AI milestone makes the whole exercise obsolete.
The tragic irony is that the assessment system they're trying to reform was already creaking under the weight of publish-or-perish metrics. Now AI has simply exposed the rot. The Coalition's proposal to recognise 'diverse contributions' sounds lovely, but without a concrete mechanism to distinguish human insight from machine output, it's just a feel-good mandate. Expect grant reviewers to spend even more time trying to reverse-engineer whether the methodology section was written by a human or a bot – and ultimately, to reward the most polished prose, whether it came from a mind or a token predictor.