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Participatory Design to build better contact- and proximity-tracing apps

June 4, 2020 by MAIEI

Full paper in PDF formDownload

Below is the abstract from the full paper, authored by Abhishek Gupta and Tania De Gasperis. (equal contributions from each author)

Abstract

With the push for contact- and proximity-tracing solutions as a means to manage the spread of the pandemic, there is a distrust between the citizens and authorities that are deploying these solutions. The efficacy of the solutions relies on meeting a minimum uptake threshold which is hitting a barrier because of a lack of trust and transparency in how these solutions are being developed.

We propose participatory design as a mechanism to evoke trust and explore how it might be applied to co-create technological solutions that not only meet the needs of the users better but also expand their reach to underserved and high-risk communities. We also highlight the role of the bazaar model of development and complement that with quantitative and qualitative metrics for evaluating the solutions and convincing policymakers and other stakeholders in the value of this approach with empirical evidence.

Keywords: participatory design, contact tracing, proximity tracing, trust, transparency

Full paper in PDF formDownload

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  • © MONTREAL AI ETHICS INSTITUTE. All rights reserved 2020.
  • This work is licensed under a Creative Commons Attribution 4.0 International License.
  • Creative Commons LicenseLearn more about our open access policy here.