Understanding Explainability
The conversation delves into the complexities of explainability in AI, particularly within safety-critical systems like transportation. Emphasizing the need for a shift from deterministic testing to probabilistic reasoning, the discussion highlights the government's expertise gap in regulating autonomous technologies. Furthermore, the focus on edge cases—data that algorithms may overlook—underscores the importance of gaining deeper insights into AI decision-making processes.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Infrastructure for Autonomous Vehicles with Missy Cummings - #128
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