Responsible AI

Speaker:  Ricardo Baeza-Yates – Palo Alto, CA, United States
Topic(s):  Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing

Abstract

In the first part we cover five current specific problems that motivate the needs of responsible AI: (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., 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 address four challenges: (1) too many principles (e.g., principles vs. techniques), (2) cultural differences; (3) regulation and (4) our cognitive biases. We finish discussing what we can do to address these challenges in the near future to be able to develop responsible AI, particularly under the umbrella of the incoming regulation (European Union's AI Act & White House's Blueprint for an AI Bill of Rights)

About this Lecture

Number of Slides:  25 - 55
Duration:  30 - 80 minutes
Languages Available:  English, Portuguese, Spanish
Last Updated: 

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