Ethics in AI: A Challenging Task
10 - 11 a.m. PDTVirtual Event
In the first part of this seminar, we will cover five current specific challenges through examples: (1) discrimination (e.g., facial recognition, justice, sharing economy, language models); (2) phrenology (e.g., biometric-based predictions); (3) unfair digital commerce (e.g., exposure and popularity bias); (4) stupid models (e.g., Signal, minimal adversarial AI) and (5) indiscriminate use of computing resources (e.g., large language models). These examples do have a personal bias but set the context for the second part where we will address four generic challenges: (1) too many principles (e.g., principles vs. techniques), (2) cultural differences (e.g., Christian vs. Muslim); (3) regulation (e.g., privacy, antitrust) and (4) our cognitive biases. We will wrap up the seminar by discussing what we can do to address these challenges in the near future.
Speaker: Ricardo Baeza-Yates
Institute For Experiential AI
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