Algorithmic governance: A modes of governance approach

Daria Gritsenko and Matthew Wood

Regulation & Governance, 2022, vol. 16, issue 1, 45-62

Abstract: This article examines how modes of governance are reconfigured as a result of using algorithms in the governance process. We argue that deploying algorithmic systems creates a shift toward a special form of design‐based governance, with power exercised ex ante via choice architectures defined through protocols, requiring lower levels of commitment from governing actors. We use governance of three policy problems – speeding, disinformation, and social sharing – to illustrate what happens when algorithms are deployed to enable coordination in modes of hierarchical governance, self‐governance, and co‐governance. Our analysis shows that algorithms increase efficiency while decreasing the space for governing actors' discretion. Furthermore, we compare the effects of algorithms in each of these cases and explore sources of convergence and divergence between the governance modes. We suggest design‐based governance modes that rely on algorithmic systems might be re‐conceptualized as algorithmic governance to account for the prevalence of algorithms and the significance of their effects.

Date: 2022
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https://doi.org/10.1111/rego.12367

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Persistent link: https://EconPapers.repec.org/RePEc:wly:reggov:v:16:y:2022:i:1:p:45-62

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