AI and civic tech: Engaging citizens in decision-making processes but not without risks

J Duberry - Artificial Intelligence and Democracy, 2022 - elgaronline.com
Artificial Intelligence and Democracy, 2022elgaronline.com
Collaborative governance is about offering civil society accessible and relevant consultation
and decision opportunities. This new approach to the institution-citizen relationship differs
fundamentally from more traditional approaches to engaging citizens in policymaking
processes, which too often limit their participation to the adoption stage. Civic tech refers to
the technology that aims to increase citizen participation. It is constituted of top-down
initiatives correspond to those participatory platforms either developed internally (eg, by IT …
Collaborative governance is about offering civil society accessible and relevant consultation and decision opportunities. This new approach to the institution-citizen relationship differs fundamentally from more traditional approaches to engaging citizens in policymaking processes, which too often limit their participation to the adoption stage. Civic tech refers to the technology that aims to increase citizen participation. It is constituted of top-down initiatives correspond to those participatory platforms either developed internally (eg, by IT department of a government) or externally (by companies and universities most often). But civic tech also comprises of bottom-up initiatives that are based on platforms developed outside the control of the state. AI is used in this context for efficiency purposes: to process a vast number of comments and text published by citizens on some of these platforms. However, civic tech also presents challenges. First, many citizens still lack access to internet and have limited digital skills, which means that civic tools may contribute to marginalize further parts of the population. Civic tech's digital infrastructures may also be opaque to the users. When using AI, and because of its black box characteristics, it may be difficult to explain how AI makes its decisions. In other words, it could make the outcome document suspicious ie, reducing trust in the process and its perceived legitimacy, as well as hinder citizen participation'motivation. Data processing may also be biased either due to the algorithm itself or the data sample. Additionally, the nature of data collected requires high security and privacy levels, which may be hampered by legacy infrastructure and cybersecurity vulnerabilities.
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