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AI and Ethics
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Related lectures (29)
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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.
Deep Learning: Principles and Applications
Covers the fundamentals of deep learning, including data, architecture, and ethical considerations in model deployment.
Autonomous Weapons: The Future of Warfare
Delves into the development and implications of autonomous weapons, emphasizing the urgent need for ethical considerations and regulation.
Critical Data Studies: Introduction and Models
Introduces the Critical Data Studies course, covering data models, trust, reproducibility, biases, and ethics.
Data Ethics: Al & Equality
Explores data ethics, focusing on fairness, justice, and Al systems' broader implications.
Ethics and Law of AI
Explores the Ethics and Law of AI, focusing on data ethics, bias, and social justice in AI systems.
Generative AI and Reinforcement Learning: Future Directions
Explores advancements in generative AI and reinforcement learning, focusing on their applications, safety, and future research directions.
Ethics of AI in Finance
Explores the ethical challenges of AI in finance, including biases, market manipulation, and the need for ethical AI models.
Understanding Autonomy
Explores the challenges and distinctions between human and artificial autonomy, touching on ethical implications and the conditions required for true autonomy.
Ethics of AI: Data, Algorithms, and Integration
Explores the ethical challenges of AI, including data ethics, algorithm ethics, and societal impact.
