Opportunity Information: Apply for 19 571
The NSF Program on Fairness in Artificial Intelligence (AI) in Collaboration with Amazon (Funding Opportunity Number 19-571) is a National Science Foundation discretionary grant opportunity designed to advance fundamental, computational research that improves the trustworthiness of AI and machine learning systems. The central idea behind the program is that as AI becomes more widely deployed in high-impact, real-world settings, public confidence and broad adoption will increasingly depend on whether these systems can be shown to behave fairly and responsibly. NSF frames this as more than a technical performance issue: even highly accurate AI can fail society if it produces unjust outcomes, hides decision logic, cannot be audited, or disproportionately harms certain groups. The program therefore targets research that helps the community ensure, assess, and demonstrate fairness-related properties in AI systems, with an emphasis on approaches that move beyond current capabilities and are motivated by realistic deployment constraints.
A key focus of the solicitation is the set of topics commonly associated with trustworthy AI, especially fairness, transparency, explainability, and accountability. Within that umbrella, NSF highlights specific areas of interest including identifying and understanding adverse biases and unintended effects, developing mitigation strategies, creating methods to validate or measure fairness claims, and incorporating inclusivity considerations so the benefits of AI are broadly available across all segments of society. The opportunity is explicitly oriented toward research contributions that can stand up in practice: the goal is not only to propose principles, but to develop theories, techniques, and methodologies that can be used to evaluate and improve real systems, ultimately supporting broader acceptance of AI technologies and enabling their responsible use in addressing major societal challenges.
Although Amazon provides partial funding, the program description makes a point of clarifying that Amazon will not participate in selecting proposals for award. NSF positions the partnership as a way to strengthen and accelerate research progress while keeping the merit-review and award decision process independent. The program also emphasizes that fairness in AI is inherently interdisciplinary. Strong proposals are expected to draw from, or collaborate across, fields such as computer science and information science, engineering, statistics and mathematics, and human-centered disciplines like cognitive science and psychology. This reflects the view that fairness and bias are not purely computational problems; they involve measurement choices, human interpretation, behavioral impacts, and social context, all of which benefit from multiple scientific perspectives.
From an administrative standpoint, this opportunity is offered as a grant under the broad federal activity category of science and technology research and development. The CFDA numbers listed are 47.070 and 47.075, and the agency is the National Science Foundation. The original posting date is March 26, 2019, with an original closing date of June 25, 2019. NSF anticipated making about nine awards, and the public listing shows an award ceiling of 0, which typically indicates that the ceiling is not specified in the high-level synopsis and applicants should rely on the full solicitation for budgeting guidance and any constraints. Eligibility is summarized as "Others (see text field entitled Additional Information on Eligibility for clarification)," meaning applicants would need to consult the full program announcement to confirm which organizations and partnership types are permitted.
Overall, the opportunity is best understood as a targeted NSF research program aimed at building the scientific and technical foundations needed to make AI systems demonstrably fair and worthy of trust at scale. By funding work on measurement, auditing, explanation, accountability mechanisms, bias identification and mitigation, and inclusivity-aware design and validation, NSF intends to help ensure that the economic and societal benefits of AI can be realized without leaving segments of the population behind or creating new forms of harm that undermine confidence in the technology.Apply for 19 571
- The National Science Foundation in the science and technology and other research and development sector is offering a public funding opportunity titled "NSF Program on Fairness in Artificial Intelligence (AI) in Collaboration with Amazon" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 47.070, 47.075.
- This funding opportunity was created on Mar 26, 2019.
- Applicants must submit their applications by Jun 25, 2019. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- The number of recipients for this funding is limited to 9 candidate(s).
- Eligible applicants include: Others (see text field entitled Additional Information on Eligibility for clarification).
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Frequently Asked Questions (FAQs)
What is the NSF Program on Fairness in Artificial Intelligence (AI) in Collaboration with Amazon?
It is a National Science Foundation (NSF) discretionary grant opportunity (Funding Opportunity Number 19-571) that supports fundamental, computational research aimed at improving the trustworthiness of AI and machine learning systems, especially in real-world, high-impact deployments.
What is the main goal of this funding opportunity?
The main goal is to advance research that helps AI systems behave fairly and responsibly in practice, so that public confidence and broad adoption can grow as these systems are deployed in settings where decisions can significantly affect people and communities.
Why does NSF emphasize fairness and trustworthiness even if an AI system is highly accurate?
NSF notes that high accuracy alone does not guarantee socially acceptable outcomes. An AI system can still fail society if it produces unjust results, hides its decision logic, cannot be audited, or disproportionately harms certain groups.
What kinds of research topics does the program prioritize?
The solicitation centers on trustworthy AI topics, with particular emphasis on fairness, transparency, explainability, and accountability. It highlights research such as identifying and understanding adverse biases and unintended effects, developing mitigation strategies, creating methods to validate or measure fairness claims, and incorporating inclusivity considerations so AI benefits are broadly available.
Is this program focused on theoretical ideas, practical tools, or both?
Based on the description, the program is oriented toward research contributions that can stand up in practice. NSF emphasizes moving beyond principles alone and instead developing theories, techniques, and methodologies that can evaluate and improve real AI systems under realistic deployment constraints.
What does NSF mean by “fairness-related properties” in AI systems?
In this context, fairness-related properties include whether a system produces unjust outcomes, whether its decision logic can be examined or explained, whether its decisions can be audited, and whether it avoids disproportionate harm to particular groups. The program supports research that can ensure, assess, and demonstrate such properties.
What is included under the program’s “trustworthy AI” umbrella?
The program description associates trustworthy AI with fairness, transparency, explainability, and accountability, including research on bias identification, unintended impacts, mitigation, measurement/validation of fairness claims, and inclusivity-aware design and validation.
How does the program address bias in AI?
It targets research that can identify and understand adverse biases and unintended effects, as well as research that develops mitigation strategies and methods to validate or measure fairness-related claims in AI systems.
What does “inclusivity considerations” mean in this solicitation?
It refers to incorporating design and evaluation considerations so that AI benefits are broadly available across all segments of society, rather than concentrating benefits or causing harms that fall disproportionately on certain groups.
What role does Amazon play in this opportunity?
Amazon provides partial funding to strengthen and accelerate research progress, but the program description explicitly states that Amazon will not participate in selecting proposals for award.
Does Amazon have any influence over which proposals are funded?
The description emphasizes that the merit-review and award decision process remains independent, and that Amazon will not participate in selecting proposals for award.
Which agency is offering this grant opportunity?
The offering agency is the National Science Foundation (NSF).
What is the federal activity category for this opportunity?
The opportunity is offered as a grant under the federal activity category of science and technology research and development.
What CFDA numbers are associated with this program?
The CFDA numbers listed are 47.070 and 47.075.
What is the Funding Opportunity Number?
The Funding Opportunity Number is 19-571.
When was this opportunity originally posted?
The original posting date is March 26, 2019.
What was the original closing date?
The original closing date is June 25, 2019.
How many awards did NSF anticipate making?
NSF anticipated making about nine awards.
Is there a stated maximum award amount (award ceiling)?
The public listing shows an award ceiling of 0, which typically indicates the ceiling is not specified in the high-level synopsis. Applicants are expected to rely on the full solicitation for budgeting guidance and any constraints.
Who is eligible to apply?
Eligibility is summarized as “Others (see text field entitled Additional Information on Eligibility for clarification).” This indicates applicants should consult the full program announcement to confirm which organizations and partnership types are permitted.
Is this program interdisciplinary?
Yes. NSF emphasizes that fairness in AI is inherently interdisciplinary, and strong proposals are expected to draw from or collaborate across multiple fields.
Which disciplines does NSF specifically mention as relevant?
The description mentions computer science and information science, engineering, statistics and mathematics, and human-centered disciplines such as cognitive science and psychology.
Why does NSF encourage participation from human-centered disciplines?
Because fairness and bias are not viewed as purely computational problems. They involve measurement choices, human interpretation, behavioral impacts, and social context, which benefit from multiple scientific perspectives.
What kinds of outcomes is NSF trying to prevent through this research program?
The program is motivated by preventing unjust outcomes, preventing decision logic that is hidden or not explainable, avoiding systems that cannot be audited, and reducing or preventing disproportionate harms to certain groups that could undermine trust in AI.
How does NSF connect this research to broader societal impact?
NSF frames the work as foundational to responsible AI use in major societal challenges, aiming to ensure AI’s economic and societal benefits can be realized without leaving segments of the population behind or creating new harms that reduce public confidence.
What is the overall purpose of this targeted NSF research program?
Overall, it is intended to build the scientific and technical foundations for AI systems that can be demonstrably fair and worthy of trust at scale, including work on measurement, auditing, explanation, accountability mechanisms, bias identification and mitigation, and inclusivity-aware design and validation.
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