already create similar incentives, and citation based solely on abstracts is far from uncommon, but AI once again takes an existing problem and intensifies it. If this bypassing of original texts be- comes widespread, it could fundamentally reshape how journal articles are written and shared. If your prose is unlikely to ever be read by a human, why invest time in crafting it? AI-mediated reading natu- rally encourages AI-mediated writing. Generative tools can already produce passable introductions, generate methods sections from protocols, analyse data, and write up results. Without rigor- ous checking, this would be disastrous for research. Errors would proliferate, careful analysis would be displaced by sheer volume, and an already problem- atic publish-or-perish culture would be further entrenched. If peer review follows the same path, we may as well automate the entire system and be done with it. And yet, we also know that generative AI can only reproduce patterns from the past: it cannot make genuine leaps of judgement or produce truly new ideas.


Finding the middle way


It is very easy, with any AI development, to fall into one of two camps. Either AI


is the next great leap forward, and its flaws are simply the price of progress, or it is the end of scholarship as we know it and should be resisted outright. As ever, it seems to me that the reality lies somewhere in between. Tools like LeapSpace are genuinely useful. They are also expensive, imperfect, and out of


reach for many. At the Francis Crick, we have not yet committed to a subscription to any of these platforms, although I know some researchers are already using them. I remain unconvinced that they are quite where I need them to be to justify a significant investment, but I am watching closely. IP


28 INFORMATION PROFESSIONAL


April-May 2026


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