The potential for machine learning to answer questions of environmental science, monitoring, and regulatory enforcement is evident, but there is cause for concern regarding …
We explore the promises and challenges of employing sequential decision-making algorithms--such as bandits, reinforcement learning, and active learning--in law and public …
Virtually all aspects of our societal functioning—from food security to energy supply to healthcare—depend on the dynamics of environmental factors. Nevertheless, the social …
A New AI Lexicon: Sustainability - AI Now Institute 2023 Landscape Our Work People Careers About Us The AI Now Institute produces diagnosis and actionable policy research on artificial …
Recent advances in machine learning (ML) have seen systems achieve human-like performance in specific tasks, especially in the realms of sequential decision-making and …
E Benami, N Jo, B Ragnauth, DE Ho - … Tailored Reminders Improve …, 2023 - papers.ssrn.com
Environmental law relies on self-monitoring by regulated parties, but reporting violations persist in nontrivial numbers. Failure to report on time can mask pollution problems and …
We explore the promises and challenges of employing sequential decision-making algorithms–such as bandits, reinforcement learning, and active learning–in the public sector …