
NSF Org: |
CNS Division Of Computer and Network Systems |
Recipient: |
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Initial Amendment Date: | July 15, 2024 |
Latest Amendment Date: | July 15, 2024 |
Award Number: | 2426397 |
Award Instrument: | Standard Grant |
Program Manager: |
Sara Kiesler
skiesler@nsf.gov (703)292-8643 CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
Start Date: | October 1, 2024 |
End Date: | September 30, 2027 (Estimated) |
Total Intended Award Amount: | $199,990.00 |
Total Awarded Amount to Date: | $199,990.00 |
Funds Obligated to Date: |
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History of Investigator: |
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Recipient Sponsored Research Office: |
300 TURNER ST NW BLACKSBURG VA US 24060-3359 (540)231-5281 |
Sponsor Congressional District: |
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Primary Place of Performance: |
620 Drillfield Drive BLACKSBURG VA US 24061-1050 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): | Secure &Trustworthy Cyberspace |
Primary Program Source: |
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Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.070, 47.075 |
ABSTRACT
Privacy is often perceived as an abstract concept by both internet users and software developers. When users are engaged in online activities, it is difficult for them to make informed decisions about their personal data due to the challenges they face in understanding and experiencing the privacy implications of their behaviors in advance. Similarly, many software developers lack the ability to comprehend how the data practices of their applications may impact user privacy and to implement proper data practices that conform to users? privacy expectations. This project is tackling this problem by developing a new, empathy-based framework to enhance privacy education and design. The project team is using generative AI to create synthetic personas with AI-generated personal data. Using the personas, the team is designing, creating, and studying new interactive sandboxes and developer tools that allow individuals to empathize with these personas, leading to a more concrete and situated understanding of privacy. This understanding, in turn, fosters positive privacy-oriented behaviors among internet users and privacy-responsible software development practices among software developers.
To enhance users? privacy knowledge and developers? privacy-responsible software development practices, the project is systematically studying the mechanisms and applications of empathy invocation in the context of privacy. The goal is to develop metrics, guidelines, and conceptual frameworks for empathy-based approaches that foster privacy and security in cyberspace. Using these findings, the project team is employing user-centered design methods to develop: 1) systems that invoke empathy to improve users? privacy literacy and decision-making; and 2) empathy-based developer tools that support developers to proactively identify and address diverse privacy needs of users at the early stages of the development life cycle. These systems are deployed in outreach events to promote privacy literacy in under-resourced user and developer communities. Additionally, they are incorporated into college-level privacy literacy educational modules to support hands-on experiential learning.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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