Artificial Intelligence and Climate Change - Böcker
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3 produkter
356 kr
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Although artificial intelligence (AI) has many potential benefits, it has also been shown to suffer from a number of challenges for successful performance in complex real-world environments such as military operations, including brittleness, perceptual limitations, hidden biases, and lack of a model of causation important for understanding and predicting future events. These limitations mean that AI will remain inadequate for operating on its own in many complex and novel situations for the foreseeable future, and that AI will need to be carefully managed by humans to achieve their desired utility.Human-AI Teaming: State-of-the-Art and Research Needs examines the factors that are relevant to the design and implementation of AI systems with respect to human operations. This report provides an overview of the state of research on human-AI teaming to determine gaps and future research priorities and explores critical human-systems integration issues for achieving optimal performance.
Machine Learning and Artificial Intelligence to Advance Earth System Science
Opportunities and Challenges: Proceedings of a Workshop
Häftad, Engelska, 2022
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The Earth system - the atmospheric, hydrologic, geologic, and biologic cycles that circulate energy, water, nutrients, and other trace substances - is a large, complex, multiscale system in space and time that involves human and natural system interactions. Machine learning (ML) and artificial intelligence (AI) offer opportunities to understand and predict this system. Researchers are actively exploring ways to use ML/AI approaches to advance scientific discovery, speed computation, and link scientific communities.To address the challenges and opportunities around using ML/AI to advance Earth system science, the National Academies convened a workshop in February 2022 that brought together Earth system experts, ML/AI researchers, social and behavioral scientists, ethicists, and decision makers to discuss approaches to improving understanding, analysis, modeling, and prediction. Participants also explored educational pathways, responsible and ethical use of these technologies, and opportunities to foster partnerships and knowledge exchange. This publication summarizes the workshop discussions and themes that emerged throughout the meeting.
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Over the past century, artificial intelligence (AI) has evolved from computational theory to everyday conversational technologies, capturing the attention and interest of the public and the media. It has also caught the attention of the scientific community, where it has provided a new tool to support inquiry and exploration. While AI in the context of scientific investigation has existed for decades, advances in computational technology and sensing in the physical world have created opportunities to integrate AI into science in unexpected ways, with capabilities that are rapidly accelerating. As a result, AI has been leveraged by an expanding collection of disciplines in the physical and biological sciences, as well as engineering domains. While the opportunities for AI in scientific discovery seem endless, there are numerous questions about what makes for trustworthy and reliable discovery, whether such investigation should be performed without human oversight or intervention, and how best to prioritize the research agenda and allocation of resources without magnifying disparities for individuals and nations alike.In recognition of the timeliness and sizable implications of AI in our world, the National Academies of Sciences, Engineering, and Medicine hosted AI for Scientific Discovery - A Workshop on October 12-23, 2023. Leaders from across the globe in the field of AI, preeminent researchers in various science and engineering disciplines, and experts in ethics, law, and social sciences met to appraise the state of the field and provide guidance on the opportunities, as well as the challenges, that lay ahead. Presentations and discussion explored the future of AI in terms of its role as an autonomous researcher carrying out discovery and considered ethical aspects of AI used for independent scientific discovery.