Modern Slavery and Human Rights Policy and Evidence Centre’s Post

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MIT researchers introduce the idea of a "human generalization function," which explores how our interactions with LLMs shape our confidence in their abilities. The research shows that when there's a mismatch between what we expect and how the models actually perform, it can lead to overconfidence or caution in using these tools. By aligning LLMs more closely with human expectations, we can improve their deployment and make them more reliable partners in a wide range of applications. https://lnkd.in/djdDEH2f

🗣️💬 There’s been a lot of discourse circulating about artificial intelligence, and the general perception of this groundbreaking phenomenon is a rather mixed bag. ⁉️ Want to delve deep into artificial intelligence and be in on all the discourse but don’t know where to start? 🤔 📚 Look no further! The New York Times shared a list of interesting books you might want to check out in pursuit of understanding artificial intelligence from its birth and beyond. 🚀 (SOURCE: Errol Richardson, The New York Times) 🌐 www.ai-purity.com #AIPurity

In Siegel's inquiry-driven approach to grantmaking, the emphasis lies heavily on the process, values, and questions posed, rather than fixating on predetermined answers. It's a dynamic, iterative process, commencing and concluding with meticulous questioning and refinement of those inquiries. In embodying this ethos, this spring the Siegel Research Team embarked on a journey to articulate the "10 big questions" they deemed crucial for comprehending the myriad challenges and opportunities confronting us all. They mapped questions spanning from civic knowledge and democracy, to climate and AI and inequality. But, spoiler alert: Their journey of questioning is far from over, and instead of reaching a conclusion, it has sparked even more inquiries. And that's where you come in – we want to hear from you! 🔗 Read the story, the 10 Big Questions, and how you can contribute to the discussion in our latest insight post on our website. https://lnkd.in/essTKyn6

Catch up with all the recent trends and innovations in temporal graph learning, and get a peek at where the field might be headed in 2024 — here's a comprehensive overview coauthored by Shenyang Huang, Emanuele Rossi, Michael Galkin, Andrea Cini, and Ingo Scholtes.

How can we update our skills and mindset for the 21st Century Technological area? Apply the EFACTOR habit change model!!! Another Chapter finished for the new book published in september!!! Have you got the Creativity skills to survive Artificial Intelligence? Let me help you!!!

In my blog, my musings about how Salvador Dali's Conquest of the Irrational essay helps us understand some of the challenges that Artificial Intelligence pose today. https://lnkd.in/eY_T-Pru

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