Explaining AI Through the Lens of Human Memory: Insights from Healthcare, Social Media, and Insurance

In this session, Emily Stevens delves into the challenges posed by the limits of human working memory and how they intersect with the need for explainable artificial intelligence (XAI). Using real-world examples from healthcare, social media, and insurance, she highlights how explainability in AI can foster greater trust, clarity, and informed decision-making. The talk emphasizes designing AI systems that complement human cognition—ensuring that critical, high-impact decisions are supported by tools that enhance understanding rather than complicate it.

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