Association for Computing Machinery (ACM) Courses

Toward a Theory of Race for Fairness in Machine Learning

Exploring critical race theory concepts for machine learning practitioners to develop a nuanced understanding of race in algorithmic fairness, through discussions and interactive activities.

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

Parole Denied - One Man's Fight Against a COMPAS Risk Assessment

Exploring the impact of COMPAS risk assessment in prisons, focusing on Question 19's influence on parole decisions and the challenges faced by inmates in addressing algorithmic bias.

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

A New Era of Hate

Exploring the evolution of hate movements online, their impact, and the need for improved tech company enforcement measures to combat digital propaganda and its real-world consequences.

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

Translation Tutorial - A History of Quantitative Fairness in Testing

Explores historical quantitative fairness definitions in education and hiring, translating 1960s-70s concepts to modern machine learning notation and highlighting challenges for current fairness research.

• YouTube
• 1 hour 24 minutes
• On-Demand
• Conference Talk

Economic Models II

Explores strategic manipulation, fair decision-making, and affirmative action in economic models. Discusses disparate effects, social costs, and downstream impacts on equality and fairness in algorithmic systems.

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

Empirical Studies

Exploration of fairness in risk assessments, racial bias in health algorithms, ethical issues in social media mental health inference, and China's social credit system behavior definitions.

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

Economic Models I

Exploration of fair machine learning through economic models, addressing equality of opportunity, population-level signaling, competitive equilibrium, and fair allocation algorithms.

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

Explainability

Explore cutting-edge research on explainable AI, including actionable recourse, model reconstruction, diverse explanations, and human-AI comparisons in deception detection.

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

Law and Policy

Explore ethical and legal challenges in AI, including anthropomorphism, explainability, racial categorization, and algorithmic fairness. Gain insights from experts on crucial issues shaping the future of technology and society.

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

Content Distribution

Exploring algorithmic biases in content distribution, including microtargeting, truth perception, polarization control, and recommender systems' effects on online news environments.

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

Fairness Methods

Explores advanced fairness methods in machine learning, including causal awareness, soft-to-hard decision making, and deep weighted averaging classifiers, to address bias and promote equitable AI systems.

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

Profiling and Representation

Explores bias in semantic representations, fair crowdsourced recommendations, profiling potential of computer vision, and rich subgroup fairness in machine learning. Discusses ethical implications in AI and data science.

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

Framing and Abstraction

Explore problem formulation, fairness in testing, and sociotechnical systems in machine learning. Gain insights on ethical considerations and challenges in AI development and implementation.

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

Translation Tutorial - People Analytics and Employment Selection

Explore the use of machine learning in employment decisions, covering legal aspects, discrimination theories, and impact measurement of people analytics tools in hiring processes.

• YouTube
• 1 hour 11 minutes
• On-Demand
• Conference Talk

Quantifying and Reducing Gender Stereotypes in Word Embeddings

Hands-on exploration of gender biases in word embeddings, quantifying stereotypes, and implementing techniques to reduce bias in natural language processing applications.

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