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Exploring algorithmic biases in content distribution, including microtargeting, truth perception, polarization control, and recommender systems' effects on online news environments.
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.
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.
Explore problem formulation, fairness in testing, and sociotechnical systems in machine learning. Gain insights on ethical considerations and challenges in AI development and implementation.
Explore the use of machine learning in employment decisions, covering legal aspects, discrimination theories, and impact measurement of people analytics tools in hiring processes.
Hands-on exploration of gender biases in word embeddings, quantifying stereotypes, and implementing techniques to reduce bias in natural language processing applications.
Explore the impact of pre-trial detention decisions through legal insights, risk assessment tools, and personal experiences. Gain a deeper understanding of criminal justice data beyond statistics.
Explore key terms in fairness, accountability, and transparency in algorithmic systems. Learn how different disciplines interpret these concepts to improve cross-disciplinary communication and research in human-centered software.
Learn techniques to audit and interpret complex machine learning models, focusing on detecting unintended dependencies and biases using a specialized software library through hands-on examples.
Explore 21 mathematical definitions of fairness in machine learning, their embedded values, and implications for ethics and policy. Gain insights into the complexities of algorithmic fairness and its connection to theories of justice.
Explore the intersection of machine learning fairness and political philosophy, drawing insights to address ethical challenges in AI decision-making systems.
Explore algorithmic decision-making in child welfare hotline screening, examining ethical implications and real-world impact through a comprehensive case study analysis.
Explore limitations of automated content analysis on social media, examining accuracy, bias, and implications for free expression and content moderation policies.
Exploration of discrimination's definition, permissibility, and ethical implications. Surveys scholarly perspectives on discrimination law's purpose and debates surrounding various approaches to identifying wrongful discrimination.
Explore fair and equitable privacy protections in computing, addressing challenges and proposing solutions for inclusive data protection across diverse populations.
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