Ethical Challenges of AI: Responsibilities and Norms

Related lectures (31)

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Explores data ethics, focusing on fairness, justice, and Al systems' broader implications.

Covers the structure and content requirements for an AI ethics essay.

Covers the logistics of assignments and evaluation for the course.

Covers ethical considerations in NLP, focusing on bias, toxicity, and misinformation.

Discusses trustworthy AI, ethical principles, and US AI regulation.

Explores global data justice, social fairness in data governance, algorithmic ethics, and the political responsibility of researchers.

Examines historical information revolutions, ethical data concerns, automation impact, and AI ethics.

Explores advancements in generative AI and reinforcement learning, focusing on their applications, safety, and future research directions.

Explores the definition of intelligence in AI and humans, the role of communication and emotion, and ethical considerations in AI regulation.

Discusses student feedback, challenges in balancing laws and ethics, and the need for more critical thinking in AI ethics.