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The environmental impacts of artificial intelligence (AI) may vary significantly. Many deep learning methods have significant carbon footprints and water usage. [1] Some scientists have suggested that artificial intelligence may provide solutions to environmental problems.
Artificial Intelligence for Environment & Sustainability (ARIES) is an international non-profit research project hosted by the Basque Centre for Climate Change (BC3) headquartered in Bilbao, Spain. [1] It was created to integrate scientific computational models for environmental sustainability assessment and policy-making, [2] [3] [4] through ...
AI systems uniquely add a third problem: that even given "correct" requirements, bug-free implementation, and initial good behavior, an AI system's dynamic learning capabilities may cause it to develop unintended behavior, even without unanticipated external scenarios.
The AI Now Institute at NYU is a research institute studying the social implications of artificial intelligence. Its interdisciplinary research focuses on the themes bias and inclusion, labour and automation, rights and liberties, and safety and civil infrastructure.
AI Now publishes an annual reports on the state of AI, and its integration into society. Its 2017 Report stated that, "current framings of AI ethics are failing", and provided ten strategic recommendations for the field - including pre-release trials of AI systems, and increased research into bias and diversity in the field.
AI for the Environment: These teams seek to apply artificial intelligence solutions to the prevention of poaching and illegal fishing in locations around the world, as well as environmental problems like climate modeling and wildfire management. The teams in this group include EarthRanger, Skylight, Climate Modeling, and Wildlands.
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AI safety is an interdisciplinary field focused on preventing accidents, misuse, or other harmful consequences arising from artificial intelligence (AI) systems. It encompasses machine ethics and AI alignment, which aim to ensure AI systems are moral and beneficial, as well as monitoring AI systems for risks and enhancing their reliability.