Powerful large-scale AI models like GPT-4 are showing dramatic improvements in reasoning, problem-solving, and language capabilities. This marks a phase change for artificial intelligence—and a signal of accelerating progress to come.In this Microsoft Research Podcast series, AI scientist and engineer <a href="https://www.microsoft.com/en-us/research/people/allorens/" style="color:rgb(70,120,134);">Ashley Llorens</a> hosts conversations with his collaborators and colleagues about what these models—and the models that will come next—mean for our approach to creating, understanding, and deploying AI, its applications in areas such as healthcare and education, and its potential to benefit humanity.This episode features Partner Research Manager <a href="https://www.microsoft.com/en-us/research/people/wallach/">Hanna Wallach</a>, whose research into fairness, accountability, transparency, and ethics in AI and machine learning has helped inform the use of AI in Microsoft products and services for years. Wallach describes how she and a team of applied scientists expanded their tools for measuring fairness-related harms in AI systems to address harmful content more broadly during their involvement in the deployment of Bing Chat; her interest in filtering, a technique for mitigating harms that she describes as widely used but not often talked about; and the cross-company collaboration that brings policy, engineering, and research together to evolve and execute the Microsoft approach to developing and deploying AI responsibly.Learn more: <a href="https://www.microsoft.com/en-us/ai/principles-and-approach/" style="color:rgb(70,120,134);">Microsoft AI: Responsible AI Principles and Approach</a>  <a href="https://www.microsoft.com/en-us/research/focus-area/ai-and-microsoft-research/" style="color:rgb(0,103,184);">AI and Microsoft Research</a>

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AI Frontiers: Measuring and mitigating harms with Hanna Wallach

Microsoft Research Podcast