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Medical AI struggles with new patients
AI tools designed to predict how people with schizophrenia will respond to different antipsychotic drugs failed to adapt to new patients. The algorithms worked well for people who were part of the models’ training sample, but their performance dropped to little better than chance for subsets of the initial sample or for people who were part of an entirely different dataset. “It’s a huge problem that people have not woken up to,” says psychiatrist and study co-author Adam Chekroud.
Supercomputer AI finds battery material
A solid electrolyte material discovered by an AI system could reduce the lithium content in batteries by up to 70%. The system was given access to computing power equivalent to around 1,000 machines and spent a little more than three days whittling down 32 million candidate materials to 18 promising ones. A prototype battery built with one of the most promising materials was used to power a lightbulb. Lithium is expensive and mining it has considerable environmental impact, so reducing its use without decreasing performance is “the holy grail” in the battery industry, explains energy-storage researcher Nuria Tapia-Ruiz.
Reference: arXiv preprint (not peer reviewed)
Chances of human extinction: 5%
In a survey of 2,700 AI researchers who had published at top AI conferences, a majority said there was an at least 5% chance that superintelligent AI will destroy humanity. Yet opinions on this topic were divided. Most respondents thought that both extremely good and extremely bad scenarios were possible with superhuman AI. It’s important to remember that AI experts “don’t have a good track record” of forecasting the future, says philosopher Émile Torres.
Reference: arXiv preprint (not peer reviewed)
AI spots similarities in fingerprints
A pair of algorithms can identify fingerprints from different fingers belonging to the same person with 75-90% accuracy. This challenges the unproven assumption that fingerprints are not alike. “We don't know for sure how the AI does it," admits roboticist and study co-author Hod Lipson. “It seems like it is using something like the curvature and the angle of the swirls in the centre,” rather than the branchings and endpoints that human specialists focus on. The researchers suggest that the tool could help to generate leads in forensic investigations.
Reference: Science Advances paper
Features & opinion
Europe’s AI Act needs fixing
The European Commission said that its new AI Office, which will enforce Europe’s upcoming AI regulations, will have “a strong link with the scientific community”. Researchers need to seize this opportunity, argues a Nature editorial. “There are holes in the act that need to be filled before it enters into full force”, in around two years’ time. So far, there are no reviewable criteria for what constitutes low-risk applications of AI, which won’t be submitted for regulation. And AI developers will, in many instances, be able to self-assess products deemed high-risk.
How to use ChatGPT as a research manager
ChatGPT can tackle menial tasks and free up time for coaching and mentoring, say the research managers who use the chatbot to:
• draft research proposals, letters and reports (though watch out for made-up facts and references),
• improve the readability of texts,
• generate plain-language summaries of journal articles,
• check that funding proposals comply with submission guidelines.
Infographic of the week
Up to 76% of industrial fishing activity escapes public tracking — blind spots that could hamper ocean conservation efforts. “In this data void, it is all too easy to do harm to the environment, mismanage marine resources or disregard the law,” says machine learning engineer and study co-author Fernando Paolo. He and his team developed three deep-learning models that combed through 2 petabytes of satellite imagery collected between 2017 and 2021. The results were compared with public data from trackers that many, but not all, ships are required to use. (Mongabay | 8 min read)