Lectures related to Ethical Issues in AI

Delves into ethics and law in AI, focusing on values, normative ambitions, and ethical challenges.

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

Ethics of AI: Data, Algorithms, and Integration

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

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.

Generative AI and Reinforcement Learning: Future Directions

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

The Ethics of AI: Autonomy and Responsibility

Explores the ethical aspects of AI, emphasizing autonomy, responsibility, and accountability in innovation processes.

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.

Ethics in Technology: Understanding AI Implications

Covers the ethical implications of artificial intelligence in technology, focusing on data, algorithms, design, sustainability, and accountability.

Ethics and Law of AI

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

Ethics in Artificial Intelligence: Key Considerations

Discusses the ethical implications of artificial intelligence for engineers and its regulatory context.

Ethics: Three Big Moral Theories

Explores consequentialism, deontology, and virtue ethics, highlighting their strengths and challenges in making ethical decisions.

TILT EPFL-UNIL: Interdisciplinary Learning and Teaching

Introduces the TILT course, emphasizing reproducibility, data construction, and ethical considerations in a quantified world.

Machine's Mission

Explores ethical dilemmas faced by a machine designed to ensure survival.

Normative News Recommender Systems

Explores challenges in developing normative news recommender systems and the ethical considerations in AI, journalism, and diversity.

Understanding Intelligence and AI Ethics

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

Ethics and Law of AI

Delves into different ethical theories and thought experiments in the context of AI, exploring the challenges of defining AI.

Provably Beneficial AI: Towards Human-level Understanding

Explores provably beneficial AI, aligning AI goals with human preferences and behaviors, illustrating complexities through examples like image classification and fetching coffee.

Ethics and Law of AI

Explores the Ethics and Law of AI, focusing on data ethics, bias, and social justice in AI systems.

Ethics of AI: Update Al Act

Explores the ethical implications and risks of AI, focusing on the Update Al Act and high-risk AI systems.

Ethics in Natural Language Processing: Addressing Bias and Misinformation

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