Ethics in AI: A Challenging TaskSpeaker: Ricardo Baeza-Yates – Palo Alto, CA, United States
Topic(s): Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing
In the first part we cover current specific challenges: (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); and (4) stupid models (e.g., Signal) . These examples do have a personal bias but set the context 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 the future.
About this LectureNumber of Slides: 50
Duration: 60 minutes
Languages Available: English, Portuguese, Spanish
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