Lecture

AI and Ethics

Related lectures (29)

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

Explores the ethical implications of deploying machine learning algorithms and emphasizes the importance of fairness in decision-making processes.

Ethics and Law of AI

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

Normative News Recommender Systems

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

Ethics and Law of AI

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

Ethics in Natural Language Processing: Addressing Bias and Misinformation

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

Ethics in AI: A Deep Dive

Explores the ethical implications of AI, emphasizing transparency and accountability in its applications.

Ethics in Artificial Intelligence: Key Considerations

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

Faster Gaze Prediction: Dense Networks and Fisher Pruning

Explores the development of faster architectures for saliency prediction using deep networks and pruning methods.

The Ethics of AI: Autonomy and Responsibility

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

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.