Ethics of artificial intelligence

Related lectures (32)

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Explores the legal framework of AI ethics, including the interpretation of laws, sources of legal norms, and the prohibition of harmful AI practices.

Explores the efficiency of training large language models and the environmental impact of AI.

Explores user management in digital humanities, focusing on modeling, motivation, and engagement, with insights from Twitter, Quora, and Wikipedia.

Covers the fundamentals of machine learning for physicists and chemists, focusing on image classification tasks using artificial intelligence.

Explores the ethical challenges of AI, including data ethics, algorithm ethics, and societal impact.

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

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

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

Explores data bias, fairness, and justice in AI systems, highlighting the ethical challenges and considerations involved.

Explores the EU regulations on AI ethics, emphasizing the AI Act's impact on internal markets, fundamental rights, and fair competition.