Algorithmic Fairness Courses and Certifications

Institute for Pure & Applied Mathematics (IPAM)

Embedding Fairness into Pricing Algorithms for Vehicle Sharing Systems

Explore fairness in pricing algorithms for vehicle sharing, examining how different fairness notions impact rider surplus and access across various groups and locations.

• YouTube
• 51 minutes
• On-Demand
• Free Video

Uncertainty in Artificial Intelligence

Algorithms in Unjust Systems

Explore the impact of algorithms in unjust systems with Alexandra Chouldechova's keynote talk at UAI 2023, addressing critical issues in AI and fairness.

• YouTube
• 1 hour 6 minutes
• On-Demand
• Free Video

Cooperative AI Foundation

Fostering Cooperation via Fairness in AI Systems

Explore fairness in AI decision-making, addressing efficiency, elicitation, and incentives. Learn theoretical foundations for fairness in voting, resource allocation, and machine learning.

• YouTube
• 1 hour 1 minute
• On-Demand
• Free Video

Toronto Machine Learning Series (TMLS)

Black Loans Matter: Algorithms for Racial Justice in Financial Services

Explore AI fairness in lending, focusing on subgroup discrimination and proposing Distributionally Robust Fairness with SenSR algorithm to combat racial bias in financial services.

• YouTube
• 39 minutes
• On-Demand
• Free Video

Toronto Machine Learning Series (TMLS)

Fairness in Algorithmic Decision Making for Financial Services

Explore fairness in AI algorithms for financial services, addressing bias detection and mitigation to ensure ethical decision-making.

• YouTube
• 30 minutes
• On-Demand
• Free Video

Fairness in Representation Learning - Natalie Dullerud

Explore fairness in deep metric learning, evaluating bias in representations and its impact on minority subgroups. Learn about a novel approach to mitigate bias and improve fairness in machine learning models.

• YouTube
• 55 minutes
• On-Demand
• Free Video

Introduction to the Theory of Computing - Stanford

Explore fundamental concepts of theoretical computer science, including automata, computability, and complexity theory, with practical applications and algorithmic fairness.

• YouTube
• 20 hours
• On-Demand
• Free Video

Ethics in AI Design

Learn how to incorporate ethics into the development and implementation of AI systems.

• edX
• 7 weeks, 2-4 hours a week
• On-Demand
• Free Online Course (Audit)

Biais et discrimination en IA

Explorez les aspects techniques et sociaux des biais, de la discrimination et de l'équité dans l'IA, en mettant l'accent sur les impacts liés au sexe, à la race et à la situation socio-économique dans les modèles prédictifs.

• edX
• 5 weeks, 19-21 hours a week
• On-Demand
• Free Online Course (Audit)

Les coulisses des systèmes de recommandation

Exploration approfondie des systèmes de recommandation, couvrant l'apprentissage automatique, l'évaluation, la modélisation avancée, les bandits contextuels, le classement et l'équité algorithmique.

• edX
• 3 weeks, 29-31 hours a week
• On-Demand
• Free Online Course (Audit)

Ulam Lectures - Cris Moore - Limits of Computers in Science and Society Part 1

Explore computational limits, problem complexity, and algorithmic challenges in science and society. From easy puzzles to impossible problems, delve into the nature of computation and its societal impact.

• YouTube
• 1 hour 26 minutes
• On-Demand
• Free Video

Fairness in Machine Learning: Tasks, Experiences, and Performance Measures

Explore fairness in machine learning, focusing on risk assessment tasks, data representation challenges, and performance measures. Learn about new findings and alternative approaches to promote equitable AI systems.

• YouTube
• 1 hour 10 minutes
• On-Demand
• Free Video

Association for Computing Machinery (ACM)

Going Beyond Popularity and Positivity Bias: Correcting Multifactorial Bias in Recommender Systems - M1.7

Explore techniques for addressing multiple biases in recommender systems, focusing on fairness and accuracy beyond popularity and positivity.

• YouTube
• 14 minutes
• On-Demand
• Free Video

Strange Loop Conference

Privacy Governance and Explainability in ML - AI

Explore privacy governance in ML/AI, addressing GDPR compliance, explainability challenges, bias identification, and strategies for enhancing consumer trust in complex data-driven decision-making processes.

• YouTube
• 45 minutes
• On-Demand
• Conference Talk

IEEE

Doing Good by Fighting Fraud - Ethical Anti-Fraud Systems for Mobile Payments

Explore ethical anti-fraud systems for mobile payments, addressing algorithmic bias and user challenges while examining key metrics and design principles for effective fraud detection.

• YouTube
• 15 minutes
• On-Demand
• Free Video