Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Quizes
Exercises
Publications
Startups
Units
Show all results for
Home
Lecture
AI Ethics: Bias, Responsibility, and Accountability
Graph Chatbot
Related lectures (32)
Information Revolutions
Examines historical information revolutions, ethical data concerns, automation impact, and AI ethics.
Ethical Challenges of AI: Responsibilities and Norms
Explores ethical challenges posed by robots, emphasizing research question formulation and essay structure.
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.
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 in NLP
Log in to Mediaspace to watch this video
Discusses the ethical implications of NLP systems, focusing on biases, toxicity, and privacy concerns in language models.
Bias in Machine Learning
Log in to Mediaspace to watch this video
Delves into the impact of bias in machine learning models and the importance of evaluating potential harm in developing such systems.
Ethics of AI: Data, Algorithms, and Integration
Log in to Mediaspace to watch this video
Explores the ethical challenges of AI, including data ethics, algorithm ethics, and societal impact.
Generative AI and Reinforcement Learning: Future Directions
Log in to Mediaspace to watch this video
Explores advancements in generative AI and reinforcement learning, focusing on their applications, safety, and future research directions.
Deep Learning: Data, Models, and Challenges
Log in to Mediaspace to watch this video
Provides an overview of deep learning concepts, focusing on data, model architecture, and challenges in handling large datasets.
Geometric Ergodicity: Convergence Diagnostics
Log in to Mediaspace to watch this video
Covers the concept of geometric ergodicity in the context of convergence diagnostics for Markov chains.
Previous
Page 2 of 2
Next
