Association for Computing Machinery (ACM) Courses

Translation Tutorial - Data Externalities

Explore data externalities through case studies, examining privacy values, excessive sharing, low reimbursements, and data substitutability. Discuss collective bargaining as a potential solution.

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

Translation Tutorial - Causal Fairness Analysis

Explore causal fairness analysis through structural causal models, examining real-world cases like university admissions and criminal justice predictions to understand and mitigate algorithmic bias.

• YouTube
• 1 hour 20 minutes
• On-Demand
• Conference Talk

Implications Tutorial - Using Harms and Benefits to Ground Practical AI Fairness Assessments

Explore practical AI fairness assessments in finance using a harms and benefits approach. Learn methodologies, case studies, and strategies for evaluating system objectives and performance.

• YouTube
• 1 hour 34 minutes
• On-Demand
• Conference Talk

Responsible AI in Industry - Lessons Learned in Practice

Explore practical lessons on implementing responsible AI in industry, covering explainability, fairness, and challenges faced by major tech companies.

• YouTube
• 1 hour 31 minutes
• On-Demand
• Conference Talk

Power in Political Philosophy - Nature and Justification

Explore the nature and justification of power in political philosophy, examining concepts like power over, power to, modalities, structure, agency, and legitimacy.

• YouTube
• 1 hour 27 minutes
• On-Demand
• Conference Talk

Translation Tutorial - Causal Fairness Analysis

Explore causal fairness analysis in AI, covering structural causal models, causal diagrams, and demographic disparities. Learn why causality matters and how to address fairness challenges in artificial intelligence.

• YouTube
• 1 hour 32 minutes
• On-Demand
• Conference Talk

Implications Tutorial - AI on the Ground Approach

Explore the real-world impact of AI through case studies, examining challenges, harms, and social implications. Learn strategies for studying AI's effects on communities and society.

• YouTube
• 1 hour 5 minutes
• On-Demand
• Conference Talk

Algorithms, Accountability and Journalism

Explore algorithmic accountability in journalism with Julia Angwin. Discover The Markup's innovative approaches to privacy, data analysis, and investigative reporting on tech companies and societal impacts.

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

When the Umpire is also a Player - Bias in Private Label Product Recommendations on E-commerce Marketplaces

Explore bias in e-commerce product recommendations, focusing on private labels. Analyze exposure bias and sponsored recommendations to understand fairness implications in online marketplaces.

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

An Action-Oriented AI Policy Toolkit for Technology Audits by Community Advocates and Activists

Explore a toolkit for community advocates to audit AI technologies, focusing on algorithmic equity, policy implications, and practical assessment methods for identifying potential biases and injustices.

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

Outlining Traceability - A Principle for Operationalizing Accountability in Computing Systems

Explore traceability as a key principle for accountability in computing systems, focusing on voting machines and their vulnerabilities, with insights on implementation and future challenges.

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

Algorithmic Impact Assessments and Accountability - The Co-construction of Impacts

Explore the challenges and complexities of algorithmic impact assessments, focusing on accountability, governance, and the diverse perspectives needed for effective evaluation.

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

Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases

Explore how unsupervised pre-training in image representations can lead to human-like biases, examining methods, results, and implications for AI fairness and ethics.

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

On the Dangers of Stochastic Parrots - Can Language Models Be Too Big?

Explore the risks and ethical concerns of large language models, including data management, research implications, and potential mitigation strategies for AI development.

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

You Can't Sit With Us - Exclusionary Pedagogy in AI Ethics Education

Explores exclusionary practices in AI ethics education, highlighting methodological dogmatism, lack of co-creation, and siloed citations. Proposes ideas for more collaborative and inclusive pedagogical approaches.

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