NSF Program on Fairness in Artificial Intelligence in Collaboration with Amazon

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Funding Opportunity ID: 326363
Opportunity Number: 20-566
Opportunity Title: NSF Program on Fairness in Artificial Intelligence in Collaboration with Amazon
Opportunity Category: Discretionary
Opportunity Category Explanation:
Funding Instrument Type: Grant
Category of Funding Activity: Science and Technology and other Research and Development
Category Explanation:
CFDA Number(s): 47.070
47.075
Eligible Applicants: Others (see text field entitled “Additional Information on Eligibility” for clarification)
Additional Information on Eligibility: *Who May Submit Proposals: Proposals may only be submitted by the following: -Non-profit, non-academic organizations: Independent museums, observatories, research labs, professional societies and similar organizations in the U.S. associated with educational or research activities. -Institutions of Higher Education (IHEs) – Two- and four-year IHEs (including community colleges) accredited in, and having a campus located in the US, acting on behalf of their faculty members.Special Instructions for International Branch Campuses of US IHEs: If the proposal includes funding to be provided to an international branch campus of a US institution of higher education (including through use of subawards and consultant arrangements), the proposer must explain the benefit(s) to the project of performance at the international branch campus, and justify why the project activities cannot be performed at the US campus. *Who May Serve as PI: The lead PI on each proposal is expected to bring computer science expertise to the research.
Agency Code: NSF
Agency Name: National Science Foundation
Posted Date: Apr 16, 2020
Close Date: Jul 13, 2020
Last Updated Date: Apr 16, 2020
Award Ceiling: $0
Award Floor: $0
Estimated Total Program Funding: $7,600,000
Expected Number of Awards: 10
Description: NSF has long supported transformative research in artificial intelligence (AI) and machine learning (ML). The resulting innovations offer new levels of economic opportunity and growth, safety and security, and health and wellness, intended to be shared across all segments of society. Broad acceptance and adoption of large-scale deployments of AI systems rely critically on their trustworthiness which, in turn, depends on the ability to assess and demonstrate the fairness (including broad accessibility and utility), transparency, explainability, and accountability of such systems. For example, the behavior of algorithms for face recognition, speech, and language, especially when integrated into decision support systems applied across different segments of society, would benefit from new foundational research in fairness of AI systems. NSF and Amazon are partnering to jointly support computational research focused on fairness in AI, with the goal of contributing to trustworthy AI systems that are readily accepted and deployed to tackle grand challenges facing society. Specific topics of interest include, but are not limited to transparency, explainability, accountability, potential adverse biases and effects, mitigation strategies, algorithmic advances, fairness objectives, validation of fairness, and advances in broad accessibility and utility. Funded projects will enable broadened acceptance of AI systems, helping the U.S. further capitalize on the potential of AI technologies. Although Amazon provides partial funding for this program, it will not play a role in the selection of proposals for award. Advancing AI is a highly interdisciplinary endeavor drawing on fields such as computer science, information science, engineering, statistics, mathematics, cognitive science, and psychology. As such, NSF and Amazon expect these varied perspectives to be critical for the study of fairness in AI. NSF's ability to bring together multiple scientific disciplines uniquely positions the agency in this collaboration, while building AI that is fair and unbiased is an important aspect of Amazon's AI initiatives. This program supports the conduct of fundamental computer science research into theories, techniques, and methodologies that go well beyond today's capabilities and are motivated by challenges and requirements in real systems. NSF’s mission calls for the broadening of opportunities and expanding participation of groups, institutions, and geographic regions that are underrepresented in STEM disciplines, which is essential to the health and vitality of science and engineering. Consistent with this principle of diversity and particularly suitable for the thrust of this program, NSF and Amazon encourage proposals (either independently or in multi-institution collaborations) from investigators at institutions that serve groups historically underrepresented in STEM disciplines.
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