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Computer Science
Data Analysis
Computer Networking
Medicine and the Arts: Humanising Healthcare
Exploring Play: The Importance of Play in Everyday Life
Songwriting: Writing the Lyrics
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Exploring approaches to implement intersectionality in algorithmic fairness, addressing hidden biases and unique experiences at the intersection of identities to promote equitable AI systems.
Explore the nature and justification of power in political philosophy, examining key concepts and theories that shape our understanding of political authority and legitimacy.
Explore fairness in AI and its societal implications with experts from NYU and STOP. Gain insights into ethical considerations and practical approaches for responsible AI development.
Explore the legal implications of fairness metrics in machine learning under EU non-discrimination law, examining bias preservation and its impact on algorithmic decision-making.
Explore the limitations and potential pitfalls of explainable machine learning, focusing on when to be cautious about trusting ML explanations in real-world applications.
Explore sociocultural diversity in machine learning through insights from philosophy, psychology, and organizational science. Gain valuable lessons for creating more inclusive and effective AI systems.
Explore AI model monitoring in healthcare, focusing on practical implementation, ethical considerations, and real-world challenges faced by industry professionals.
Explore techniques for balancing transparency and accuracy in predictive decision-making, focusing on strategic prediction methods for ethical and effective data-driven solutions.
Explore the legal implications of fairness metrics in machine learning under EU non-discrimination law, focusing on bias preservation and its impact on algorithmic decision-making.
Explore fairness in AI and its societal implications through expert insights on ethical considerations, surveillance technology, and responsible data practices.
Crash course on integrating ethical thinking in tech education, covering motivation, support, and expansion strategies for educators to foster responsible innovation.
Exploring the value of imperfect mathematical models in computing and their impact on decision-making, ethics, and societal implications in technology and data science.
Explore the intersections of health, technology, and race with Yeshimabeit Milner's insightful keynote, addressing crucial societal issues and their impact on modern healthcare and technological advancements.
Explore Bayesian inference techniques for detecting discriminatory risk in data annotation, enhancing fairness and accountability in machine learning systems.
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