Managing data responsibly while protecting privacy and security
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Reviews privacy-preserving techniques for AI in healthcare including federated learning, differential privacy, and secure multi-party computation.
Overview of trends in privacy-preserving technologies for AI developers and stakeholders, examining solutions for data protection challenges.
Reviews challenges and approaches to data governance for AI systems, proposing comprehensive framework for trustworthy data management.
A declaration developed in 2018 through a unique citizen co-construction process involving 500+ participants, presenting 10 principles for responsible AI.
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Foundational principles, values, and frameworks guiding responsible AI development
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