The volume of the calls to "AI all the things" at $PlaceOfWork is becoming deafening.

(To be clear I'm referring to general LLMs/Chatbots - not validated tools (e.g. Alphafold) trained on well curated public datasets for a specific task.)

• Where AI generates hypotheses: These hypotheses still need careful experimental validation, especially if work is clinical or translational. So funding AI at the expense of actual data-generating science (I'm looking at you, UK STFC) is an idiot's game

• Where AI is used to analyse data or find signals in noisy data - you still need to experimentally validate these findings. See first point.

• Maybe you want to generate better AI models, you still need careful curated data to "feed the beast". Training AI on AI slop leads to an ouroboros of shit. See first point.

• Using AI to generate hypotheses doesn't actually enhance your intellectual development as a scientist - You just become the meat avatar of an algorithm trained on stolen data. Development as a scientist (which never stops, btw) allows you to deploy your skills, experience, and intuition* to answer the questions you're asking.

*I see science as a creative endeavour. It's exploration. You shouldn't just blindly follow the whim of your bloated new silicon overlords.