Supervised Feed

What happens when AI becomes faster at scientific discovery than the institutions designed to verify it? We are entering a paradox. AI can map proteins, model new materials, analyse massive datasets and accelerate research from years to hours. DeepMind’s AlphaFold mapped more than 200 million protein structures, while AI systems are now being used across drug discovery, climate modelling, physics, agriculture and space research. But the same systems are also creating a growing integrity problem. Research audits have identified AI-assisted peer reviews, fabricated citations, synthetic scientific writing and cases where AI-generated “discoveries” still required human experts to determine whether they were scientifically meaningful. The question is not whether AI will transform science. It already is. The question is whether we can accelerate discovery without weakening the human judgement, imagination, verification and trust that science depends on. AI should expand the scientist’s capabilities, not replace scientific responsibility. In my latest analysis, I explore the opportunities, risks and SWOT of AI in scientific research — and the wider paradox of human-machine evolution. wisdomia.ai/ai-and-scientifi… #AI #ArtificialIntelligence #Science #Research #AISafety #AIResearch #Innovation #FutureOfScience #HumanMachine CC @YuHelenYu @efipm @enilev @JagersbergKnut @TysonLester @CurieuxExplorer @GlenGilmore @FrRonconii @chidambara09 @jeancayeux @mvollmer1 @Nicochan33 @RLDI_Lamy @pchamard @mikeflache @Fabriziobustama @Mack1510019 @ipfconline1 @PawlowskiMario @drsharwood @kalydeoo @baski_LA @AnthonyRochand @smaksked @Eli_Krumova @andresvilarino @gvalan @AI_4_Healthcare @bimedotcom @arlenenewbigg @NewsNeus @domingonarvaez1 @bamitav @jornalistavitor @jblefevre60 @FmFrancoise @MHcommunicate @Corix_JC @c4trends @smoothsale @amalmerzouk @PVynckier @bbailey39 @ralf_ladner @mary_gambara