Ethics in AI: A Challenging Task - Lecture by Ricardo Baeza-Yates

Ricardo Baeza-Yates gives a lecture at the NoBIAS Summer School on Ethics in AI.
Abstract:
In the first part we cover five current specific challenges through examples emphasizing bias issues: (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., lack of understanding semantics and context) and (5) indiscriminated use of computing resources (e.g., large language models). These examples do have a personal bias but set the stage for the second part where we 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 finish discussing what we can do to address these challenges in the near future.