Four more things we worked on in 2022

We had a busy 2022. Here are a few things we worked on but didn’t cover here.

We’re grateful to you for reading this blog / newsletter. It’s made our book project much more rewarding. We had a busy 2022. Here are links to things we worked on but didn’t cover here. 1. The reproducibility crisis in ML-based science. AI hype isn’t limited to commercial products. Researchers hype their results just as much. This has led to overoptimism about ML in many scientific fields including medicine and political science. Over the summer, we organized an online workshop on the topic. Over a thousand people registered and the YouTube livestream has been watched over 5,000 times.…

related reading

• Scientists should use AI as a tool, not an oraclenormaltech.ai
• LessWronglesswrong.com
• Sloppy Use of Machine Learning Is Causing a ‘Reproducibility Crisis’ in Science | WIREDwired.com
• ML is useful for many things, but not for predicting scientific replicabilitynormaltech.ai
• Danger, AI Scientist, Danger - by Zvi Mowshowitzthezvi.substack.com
• Researchgleech.org
• How much science is verifiable? Results from replicating ICML 2026 oral paperssai.science
• Beware of AI pseudoscience and snake oilbaldurbjarnason.com
• Who Should Stop Unethical A.I.? | The New Yorkernewyorker.com
• Thoughts — Jason Weijasonwei.net
• A Bird's Eye View of the ML Field [Pragmatic AI Safety #2] — LessWronglesswrong.com
• A Bird's Eye View of the ML Field [Pragmatic AI Safety #2] — AI Alignment Forumalignmentforum.org