Keeping up with an industry as fast-moving as AI is a tall order. So until an AI can do it for you, here’s a handy roundup of recent stories in the world of machine learning, along with notable research and experiments we didn’t cover on their own. This week in AI, DeepMind, the Google-owned AI R&D lab, released a paper proposing a framework for evaluating the societal and ethical risks of AI systems. The timing of the paper — which calls for varying levels of involvement from AI developers, app developers and “broader public stakeholders” in evaluating and auditing AI — isn’t accidental. Next week is the AI Safety Summit, a U.K.-government-sponsored event that’ll bring together international governments, leading AI companies, civil society groups and experts in research to focus on how best to manage risks from the most recent advances in AI, including generative AI (e.g. ChatGPT, Stable Diffusion and so on). There, the U.K. is planning to introduce a global advisory group on AI loosely modeled on the U.N.’s Intergovernmental Panel on Climate Change, comprising a rotating cast of academics who will write regular reports on cutting-edge developments in AI — and their associated dangers. DeepMind is airing its perspective, very visibly, ahead of on-the-ground policy talks at the two-day summit. And, to give credit where it’s due, the research lab makes a few reasonable (if obvious) points, such as calling for approaches to examine AI systems at the “point of human interaction” and the ways in which these systems… Click below to read the full story from TechCrunch
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