Replication Data for: Case Studies in Public Interest Technology
Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)
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Title |
Replication Data for: Case Studies in Public Interest Technology
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Identifier |
https://doi.org/10.7910/DVN/D2A279
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Creator |
Zang, Jinyan
Sweeney, Latanya |
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Publisher |
Harvard Dataverse
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Description |
Case Studies in Public Interest Technology Today, there are multiple ways where digital technologies adversely impacts the public interest, whether that’s the spread of misinformation online, the loss of privacy, the threat of algorithmic discrimination, and more. Public interest technology is an emerging field that seeks to use cross-disciplinary techniques to research and address these issues in order to advance the public interest. For this dissertation, I present three different case studies of public interest tech research projects, each of which focuses on a different technology and relevant public interest. In Chapter 2, I research how Facebook’s advertising algorithms can discriminate by race and ethnicity. In Chapter 3, I test how the predictability of Social Security Number (SSN) assignment based on easily accessible data about Americans presents a risk of identity theft. In Chapter 4, I demonstrate how TraceFi, a Wi-Fi based collocation detection technology, can be deployed for COVID-19 contact tracing. I propose how we can adapt Lawrence Lessig’s pathetic dot model as the “Three Forces Model of Public Interest Tech” to understand the current dysfunctional state of relationships between technology, society, and the public interest, where the public interest is often affected as an output of technology but not fully considered as an input. The three forces of the law, norms, and market can affect a given technology or vice versa which in turn affects the public interest. For different combinations of technologies and public interests, the amount of force exerted by the law, norms, or market could also differ and so could the degree of feedback between the technology and each of the forces. Since the normative goal of public interest tech as a field is to ultimately advance the public interest, the goal state of the Three Forces Model demonstrates how the public interest can be an input for the law, norms, and market in how they affect a technology’s design and usage, which would in turn affect the public interest. Stakeholders relevant to each of the forces can consider the public interest as a priority in how they interact with a technology and its designer. In Chapter 5, I present how we can apply the Three Forces Model for Public Interest Tech to each case study to describe the current state and the ideal goal state. In order to effectively respond to the multiple ways of how digital technologies have adversely impacted the public interest, we need a “whole-society” strategy that coordinates our laws, norms, and markets in how they interact with our technologies to prioritize the public interest. As public interest technologists, we need to work across disciplines to advance the public interest. Let’s get started. |
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Subject |
Computer and Information Science
Social Sciences SSN Contact Tracing Public Interest Technology |
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Language |
English
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Contributor |
Zang, Jinyan
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Type |
program source code
experimental data event/transaction data |
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