Association for Computing Machinery (ACM) Courses

Treatment Effect Risk - Bounds and Inference

Explore bounds and inference in treatment effect risk analysis, focusing on statistical methods for causal inference and risk assessment in experimental studies.

• YouTube
• 16 minutes
• Self-Paced
• Conference Talk

People Are Not Coins - Morally Distinct Types of Predictions Necessitate Different Fairness Constraints

Explore ethical implications of AI predictions and fairness constraints in different contexts, examining moral distinctions and their impact on algorithmic decision-making.

• YouTube
• 15 minutes
• Self-Paced
• Conference Talk

Four Years of FAccT - A Reflexive, Mixed-Methods Analysis of Research Contributions, Shortcomings, and Future Prospects

Reflexive analysis of FAccT research, examining contributions, limitations, and future directions in computing fairness, accountability, and transparency over four years.

• YouTube
• 16 minutes
• Self-Paced
• Conference Talk

Bias Evaluation on Data and Algorithms for Affect Recognition in Faces

Explore bias in facial affect recognition algorithms, examining data and methods to identify and mitigate demographic disparities in emotion detection accuracy.

• YouTube
• 15 minutes
• Self-Paced
• Conference Talk

Subverting Machines, Fluctuating Identities - Re-Learning Human Categorization

Explore the complexities of human categorization and identity in the digital age, challenging machine learning assumptions and discussing the fluidity of personal identities.

• YouTube
• 16 minutes
• Self-Paced
• Conference Talk

A Review of Taxonomies of Explainable Artificial Intelligence - XAI Methods

Explore various taxonomies of Explainable AI methods, comparing their structures and implications for understanding and categorizing XAI approaches.

• YouTube
• 15 minutes
• Self-Paced
• Conference Talk

Justice in Misinformation Detection Systems - An Analysis of Algorithms, Stakeholders, and Potential Harms

Explore the ethical implications and potential harms of misinformation detection algorithms, analyzing stakeholder impacts and justice considerations in AI-driven content moderation.

• YouTube
• 15 minutes
• Self-Paced
• Conference Talk

Algorithmic Fairness and Vertical Equity - Income Fairness with Tax Audit Models

Explore income fairness in tax audit models, examining algorithmic fairness and vertical equity principles to enhance equitable tax enforcement strategies.

• YouTube
• 15 minutes
• Self-Paced
• Conference Talk

Should Attention Be All We Need? The Ethical and Epistemic Implications of Unification in Machine Learning

Explore the ethical and epistemic implications of unification in machine learning, focusing on attention mechanisms and their impact on AI development and society.

• YouTube
• 17 minutes
• Self-Paced
• Conference Talk

Best vs. All - Equity and Accuracy of Standardized Test Score Reporting

Explore the equity and accuracy implications of different standardized test score reporting methods, examining their impact on fairness and precision in educational assessment.

• YouTube
• 15 minutes
• Self-Paced
• Conference Talk

FADE - FAir Double Ensemble Learning for Observable and Counterfactual Outcomes

Learn a novel machine learning approach for fair prediction of both observable and counterfactual outcomes, enhancing decision-making in various domains.

• YouTube
• 15 minutes
• Self-Paced
• Conference Talk

How Platform-User Power Relations Shape Algorithmic Accountability - A Case Study of Instant Loan Platforms and Financially Stressed Users in India

Explore power dynamics between instant loan platforms and financially stressed users in India, examining algorithmic accountability and its impact on vulnerable populations.

• YouTube
• 17 minutes
• Self-Paced
• Conference Talk

Multi-disciplinary Fairness Considerations in Machine Learning for Clinical Trials

Explore fairness in machine learning for clinical trials through a multi-disciplinary lens, examining ethical implications and potential biases in healthcare research.

• YouTube
• 15 minutes
• Self-Paced
• Conference Talk

Disclosure by Design - Document Engineering for Meaningful Data Disclosures

Explore document engineering techniques for creating meaningful data disclosures, enhancing transparency and user understanding in data-driven systems.

• YouTube
• 15 minutes
• Self-Paced
• Conference Talk

Epistemic Values in Feature Importance Methods - Lessons From Feminist Epistemology

Explore how feminist epistemology insights can enhance feature importance methods in machine learning, addressing biases and improving interpretability in AI systems.

• YouTube
• 17 minutes
• Self-Paced
• Conference Talk