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Explore all talks and presentations from ACM FAccT Conference. Dive deep into the latest insights, research, and trends from the world's leading experts.
Explore research ethics beyond "broader impact" with this ACM tutorial. Learn through case studies and exercises, in under an hour.
Learn about data externalities from experts at Harvard, Northwestern, MIT, and U of California, Berkeley in this ACM tutorial. Explore privacy values, data sharing, and collective bargaining.
Explore causal fairness analysis with Columbia U's Elias Bareinboim in this 1-2 hour tutorial by ACM. Dive into structural causal models, fairness frameworks, and counterfactual effects.
Learn practical AI fairness assessments in finance with ACM's tutorial. Understand harms, benefits, and design goals in a 1-2 hour study.
Learn responsible AI practices in industry from experts at Amazon, Google, and Microsoft with ACM's 1-2 hour tutorial. Topics include ML Ops, fairness, and case studies.
Explore political philosophy's power dynamics with Seth Lazar from Australian National U in this 1-2 hour tutorial by ACM. Delve into power structures, legitimacy, and justification.
Explore causal fairness analysis in AI with Columbia U's Elias Bareinboim in this 1-2 hour tutorial offered by ACM.
Explore the implications of AI with ACM's tutorial, covering topics from identifying harms to AI's social impact. Requires 1-2 hours of study.
Explore algorithms, accountability, and journalism with Julia Angwin in this less than 1-hour material from the Association for Computing Machinery. Dive into data privacy, technology, and investigative journalism.
Explore bias in e-commerce product recommendations with ACM's short study, covering algorithms, data collection, and exposure bias.
Learn to audit technology with an AI policy toolkit, designed for community advocates and activists. Offered by ACM, it requires less than an hour.
Learn about operationalizing accountability in computing systems with a focus on traceability, offered by ACM. Less than 1-hour workload.
Explore the co-construction of algorithmic impacts with ACM's concise study, focusing on internal governance, institutional practices, and diversity of expertise.
Explore human-like biases in image representations with ACM's research track. Learn methods, results, and future directions in under an hour.
Explore the risks of large language models with ACM's short study, covering unmanageable data and mitigation strategies.
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