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Artificial Intelligence (RAI) is about ensuring that socioenvironmental responsibility is a fundamental and permeating consideration in all stages (conception, evaluation, deployment, monitoring, etc.) of AI
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knowledge; technological support for decision making (including predictive analytics, machine learning and artificial intelligence); the main types of information systems in health care and their design; and
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. They also present challenges: New types of data, (e.g., from DNA testing) may increase risk to privacy. For machine learning and artificial intelligence to work properly, data needs to be centralized
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academia, industry, and government that leverages the power of artificial intelligence (AI), robotics, materials sciences, and high-throughput chemistry to create self-driving laboratories (SDLs), also
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academia, industry, and government that leverages the power of artificial intelligence (AI), robotics, materials sciences, and high-throughput chemistry to create self-driving laboratories (SDLs), also
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academia, industry, and government that leverages the power of artificial intelligence (AI), robotics, materials sciences, and high-throughput chemistry to create self-driving laboratories (SDLs), also
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academia, industry, and government that leverages the power of artificial intelligence (AI), robotics, materials sciences, and high-throughput chemistry to create self-driving laboratories (SDLs), also
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academia, industry, and government that leverages the power of artificial intelligence (AI), robotics, materials sciences, and high-throughput chemistry to create self-driving laboratories (SDLs), also