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Explore techniques to manipulate fair image search algorithms using adversarial perturbations, examining methods, experiments, and implications for algorithmic fairness.
Explore three models for classifying AI systems: the Switch, the Ladder, and the Matrix. Gain insights into AI governance and evaluation criteria for effective classification frameworks.
Explore automated decision-making, proxy discrimination, and its various forms, including causal descendants, influence, and capacity-induced use in algorithmic systems.
Explore the impact of differentially private synthetic data on classification fairness, examining its potential for preserving privacy while maintaining data utility in machine learning.
Explore the ethical implications of algorithmic decision-making systems, focusing on arbitrariness, unfairness, and potential solutions in automated processes across various domains.
Evaluates post-hoc explanations for machine learning models, comparing different explainers to help practitioners choose the most suitable one for their specific application and context.
Explore ethical implications of emotion in AI systems, covering theories, proxy data, and concerns. Gain insights into the intersection of AI, emotions, and ethics.
Explore differential privacy in healthcare ML, addressing unique challenges, extreme tradeoffs, and fairness considerations for underrepresented groups in medical datasets.
Explore the evolution and controversies surrounding computerized psychological testing, examining its impact on courts, corporations, and clinics in this thought-provoking presentation.
Explores racial categorization in computer vision, examining usage, consistency, and implications for fairness in AI systems. Highlights challenges and potential biases in facial recognition technology.
Exploring AI explainability challenges in GDPR compliance using COVID-19 scenarios, emphasizing justifiability over technical explanations in legal and ethical contexts.
Explore a pilot study on evaluating AI-generated radiology reports through clinical judgments, examining methodologies, results, and implications for healthcare technology.
Explore an agent-based model evaluating interventions on dating platforms to reduce racial homogamy, examining societal impacts and potential solutions.
Explore axiomatic approaches to high-dimensional model explanations, covering value functions, design principles, and characterization results, with a case study on movie reviews.
Explore narratives and counternarratives on data sharing in Africa, examining challenges, power dynamics, trust issues, and open data implications for the continent's digital landscape.
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