Concept

AI alignment

Related lectures (29)

Generative AI and Reinforcement Learning: Future Directions

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

AI Ethics: Data Bias and Justice

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

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.

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.

Lie Theorem and Irreducible Representations

Explores the Lie theorem and irreducible representations in group theory.

Regulation & Policies: Demystifying the EU AI Act

Explores the EU AI Act, covering essential requirements and high-risk systems.

AI Ethics: Trustworthy AI and Ethical Principles

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

AI Ethics: Essay Structure and Content

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

Answer Justification in AI Ethics

Emphasizes the importance of clear justifications and effective argumentation in AI ethics exams, focusing on quality over substance.

AI Ethics Narratives

Explores the impact of narratives on AI development, the role of different producers in shaping narratives, and the concept of soft power in international relations.

Ethics and Law of AI

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

Limits to Infinity

Explores limits to infinity, including convergence, algebraic properties, and geometric progressions.

Decolonising Collections: Babylonian Vision

Delves into decolonising collections through AI-generated technoheritage and artistic explorations in synthetic image-making.

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Reinforcement Learning: Q-Learning

Covers Q-Learning in reinforcement learning, exploring action values, policies, and the societal impact of algorithms.

AI Ethics: Legal Framework

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

Global Governance of AI

Explores the importance of global governance in Artificial Intelligence, emphasizing ethical practices, bias issues, and trust in AI technologies.

Convergence Criteria: Series & Functions

Explores convergence criteria for series and functions, including the squeeze theorem and D'Alembert's criterion.

Efficient Methods in Natural Language Processing

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

Value Tensions in AI: Mitigating Harms and Fostering Benefits

Delves into value tensions in AI ethics, balancing inclusion and privacy.