{"id":995556,"date":"2024-01-05T08:05:12","date_gmt":"2024-01-05T16:05:12","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-project&p=995556"},"modified":"2025-03-31T12:41:21","modified_gmt":"2025-03-31T19:41:21","slug":"afmr-cognition-and-societal-benefits","status":"publish","type":"msr-project","link":"https:\/\/www.microsoft.com\/en-us\/research\/project\/afmr-cognition-and-societal-benefits\/","title":{"rendered":"AFMR: Cognition and Societal Benefits"},"content":{"rendered":"
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Cognition and Societal Benefits<\/h1>\n\n\n\n

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Academic research plays such an important role in advancing science, technology, culture, and society. This grant program helps ensure this community has access to the latest and leading AI models.<\/em><\/strong><\/p>\nBrad Smith, Vice Chair and President<\/cite><\/blockquote>\n\n\n\n

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AFMR Goal: Improve human interactions via sociotechnical research<\/h2>\n\n\n\n

which increases trust, human ingenuity, creativity, and productivity, and decreases the digital divide while reducing the risks of developing AI which does not benefit individuals and society<\/p>\n<\/div>\n\n\n\n

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The proposals mainly focus on significant advancements in the field of healthcare, education, and various social aspects. They highlight the use of Large Language Models (LLMs) to enhance several aspects, such as improved teaching in online education platforms, generating personalized education for cybersecurity, and advancing health outcomes research. There are also proposals focused on understanding the proficiency of LLMs in extracting and understanding clinical data, simulating student interactions in classrooms, and developing privacy-aware medical dialogue systems. Other studies investigate the utility and harms of LLMs for mental health support, their use in English as a foreign language (EFL) education, and their potential application within the legal field. In healthcare, LLMs aim to not only assist doctors in patient-trial matching and radiology report summarization but also to provide patients with more understandable health data. Additionally, there are efforts to align LLMs with the diversity of global user preferences, and establish standardized protocols for using Generative Artificial Intelligence (GAI) in behavioral research, among others.<\/p>\n\n\n\n

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George Mason University<\/strong>: Ziyu Yao (PI)<\/p>\n\n\n\n

The proposal is focused on using Large Language Models (LLMs) to simulate student agents discussing STEM concepts in a virtual classroom. The platform is intended to aid STEM concept learning in PreK-12 education, facilitating teacher professional development and immersive peer learning. The researchers aim to develop student agents with consistent stances in concept understanding, which would interact and debate with each other. A human teacher or student can also partake in the discussions, fostering deeper concept learning.<\/p>\n\n\n\n

Related paper:<\/strong><\/p>\n\n\n\n