✳flâneur — a map of the web's best reading

Why an overreliance on AI-driven modelling is bad for science

nature.com · 610 words · saved by 1 readers

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Advertisement Arvind Narayanan is a computer scientist at Princeton University, Princeton, New Jersey, USA. You can also search for this author in PubMed Google Scholar Sayash Kapoor is a computer scientist at the Center for Information Technology Policy, Princeton University, Princeton, New Jersey, USA. You can also search for this author in PubMed Google Scholar Illustration: Denis Freitas You have full access to this article via your institution. The use of artificial intelligence (AI) is exploding across many branches of science.

Email Bluesky Facebook LinkedIn Reddit Whatsapp X Illustration: Denis Freitas Access through your institution Buy or subscribe The use of artificial intelligence (AI) is exploding across many branches of science. Between 2012 and 2022, the average proportion of scientific papers engaging with AI, across 20 fields, quadrupled (see ‘AI’s rise in research’), including economics, geology, political science and psychology 1 . Access options Access through your institution Access Nature and 54 other Nature Portfolio journals Get Nature+, our best-value online-access subscription $32.99 / 30 days can

Explore this link on the map →

related reading