Ethics: Concepts and Case Studies

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Related lectures (31)

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Ethics of AI: Data, Algorithms, and Integration

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

Cost-Benefit Analysis: Decision Making and Ethics

Explores cost-benefit analysis in decision-making, emphasizing ethical considerations and societal values.

Ethics: Three Big Moral Theories

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

Ethics and Law of AI

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

Framing and Narratives: Ethical Considerations in AI

Addresses the significance of framing and narratives in AI ethics and their impact on technology development and societal perceptions.

Designing Learning Tools: Introduction

Introduces 'How People Learn: Designing Learning Tools' at EPFL, focusing on emotions, diversity, and ethics in engineering education.

Ethics in AI: Consequentialism and Categorical Imperative

Explores consequentialism and categorical imperative in AI ethics, emphasizing the importance of defining values and justifications for ethical decision-making.

Goals of Engineering Ethics Education

Explores key features of engineering ethics and ethical decision-making in real-world engineering dilemmas.

Ethics in Technology: Understanding AI Implications

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

Ethics in Natural Language Processing: Addressing Bias and Misinformation

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