What AI gets wrong and what failure teaches us
Microsoft Chad Atalla, Jennifer Neville
Jennifer Neville, a Microsoft Research partner research manager, explains how AI evaluation based on simple benchmarks misses failures that show up in realistic, user-driven multiturn and long-horizon tasks. She joined Microsoft in 2021, and emphasizes using practical evaluations and data checks to find where model behavior diverges from user needs. The result is a shift from standard benchmark testing toward evaluation designs that better predict and guide improvements in AI models for real workflows.
Why it matters
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
