In AI We Trust. But Should We? | Aaron Hunter | TEDxAbbotsford

In this TEDx talk, Dr. Aaron Hunter, an AI scientist, delves into the critical issue of trusting AI. He presents three key questions to assess AI reliability: verifying the truthfulness of AI information, its subject matter expertise, and understanding the AI's goals. Highlighting examples like AI-generated misinformation and biases in facial recognition, Dr. Hunter stresses the need for transparency in AI's training and biases. The talk is a valuable resource for understanding the complexities of AI trust. Dr. Aaron Hunter is the Mastercard Chair in Digital Trust at BCIT. He is an Artificial Intelligence (AI) researcher, with a particular focus on applications in cybersecurity. Aaron has published extensively in AI, where his work has focused on computational logic, reasoning, belief revision, and trust. Our world is changing quickly due to advances in AI, and some people are worried. Should we trust the information we are given by AI systems? Should we allow AI systems to take action on our behalf? And when should AI systems trust each other? Unfortunately, we don’t always agree on what trust means – and we often make choices that are irrational or inconsistent with our current trust relationships. In this talk, Aaron will discuss how the notion of trust will play a key role in our AI future. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx

Видео In AI We Trust. But Should We? | Aaron Hunter | TEDxAbbotsford канала TEDx Talks