AI Ethics: Legal Framework

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Related lectures (31)

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Data Ethics: Al & Equality

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

Global Data Justice: Social Justice Approach to Data Governance

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

Ethics and Law of AI: Feedback and Challenges

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

AI Ethics: Data Bias and Justice

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

Ethics and Law of AI

Covers the Ethics and Law of AI, addressing relevant ethical and legal questions and providing insights on AI regulation.

AI Ethics: EU Regulations Overview

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

AI Ethics: Trustworthy AI and Ethical Principles

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

AI Ethics and Justice

Explores the ethical implications of AI on justice and fairness in society, emphasizing the importance of considering social aspects in decision-making.

AI Ethics: Bias, Responsibility, and Accountability

Explores AI ethics, addressing bias, responsibility, and accountability in algorithm design and outcomes.

Ethics in Natural Language Processing: Addressing Bias and Misinformation

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