This Project Grant award from the National Science Foundation (NSF) under CFDA 47.070 - Computer and Information Science and Engineering is for $395,927 over the period of Sep 1, 2024 to Aug 31, 2027. The award aims to develop theoretical and algorithmic foundations for building a safe and robust human-AI ecosystem, where machine learning (ML) and artificial intelligence (AI) techniques are used in applications involving humans, such as recommendation systems, lending, and healthcare. The key...
This $346,500 three-year Project Grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) will fund research at The Ohio State University examining the long-term impacts of fair machine learning under strategic individual behavior. The researchers will establish an analytical framework to characterize complex sequential interactions between individuals and machine learning systems over repeated interactions. This framework aims to enable...
This Project Grant award of $164,940 from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) supports research at Emory University focused on addressing fairness challenges in artificial intelligence (AI) algorithms. The key research goals are to investigate the impact of generalization, privacy, and robustness issues on fairness, and develop effective solutions to ensure fairness in real-world AI applications such as...
This $439,425 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant supports research to enable the safe deployment of learning-enabled systems that can robustly learn and optimize their behavior based on uncertain human feedback and intent. The key objectives are to: (1) develop methods for providing probabilistic performance guarantees when learning policies from human input,...
This $414,995 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop personalized artificial intelligence (AI) systems that can tailor their responses to individual users based on their unique backgrounds and needs. Key objectives include: Gathering a diverse dataset to characterize the types of responses preferred by different people, particularly underrepresented groups. Using this data to...
This $400,000 project grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports research to develop a systematic framework for visualizing, understanding, and rewriting the learned computations of multimodal generative AI models. The key objectives are to: 1) create new methodologies to visualize the internal mechanisms and hierarchical structures of pre-trained multimodal generative models, 2) explore model...
This $299,977 federal Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop AI-powered approaches to address challenging societal problems in the areas of drought resilience, emissions reduction, and infectious disease response. The overarching goal is to establish theoretical and algorithmic foundations for responsible and equitable AI-powered sequential, collective decision-making. The...
The National Science Foundation (NSF) awarded a $800,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of Illinois Urbana-Champaign. The 3-year grant, effective September 1, 2024, focuses on enhancing the safety of large language models (LLMs) used in high-stakes applications. The project aims to develop quantifiable safety measures and algorithms to detect and mitigate unsafe behaviors in LLMs, such as providing false or...
This Project Grant award, valued at $375,000 and awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), supports The Ohio State University's research on safe and reliable reinforcement learning (RL) systems. The key objectives of this 4-year project are to develop foundational technologies for safe RL-enabled systems, including policy safety, exploration safety, and environmental safety. The research will...
This $348,757 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to quantify social and affective cognition in humans and machines. The project aims to define objective measures for assessing the emotional understanding capabilities of large language models used in AI chatbots, in order to enable the development of more capable and safer conversational AI systems. Key aspects include...
This $400,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) supports research at The Ohio State University to develop theoretical and algorithmic foundations for building a safe and reliable human-AI ecosystem. The key objectives are to: 1) create an analytical framework to characterize human-AI interactions and safety components, 2) examine feedback effects between agents and the machine learning system to ensure long-term safety, and 3) establish a causal understanding of human-AI dynamics to design transparent interventions for long-term safety. The research aims to benefit applications like lending, recruitment, healthcare, and recommendation systems by addressing challenges around ensuring the safety and integrity of AI/ML systems when integrated with human decision-making. No sub-awards are planned under this grant, which has a performance period from September 1, 2024 to August 31, 2027.