What to account for when accounting for algorithms

Maranke Wieringa

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Ethics and Social Impacts of AI Digitalization, Law, and Regulation Explainable Artificial Intelligence (XAI)

Abstract

As research on algorithms and their impact proliferates, so do calls for scrutiny/accountability of algorithms. A systematic review of the work that has been done in the field of 'algorithmic accountability' has so far been lacking. This contribution puts forth such a systematic review, following the PRISMA statement. 242 English articles from the period 2008 up to and including 2018 were collected and extracted from Web of Science and SCOPUS, using a recursive query design coupled with computational methods. The 242 articles were prioritized and ordered using affinity mapping, resulting in 93 'core articles' which are presented in this contribution. The recursive search strategy made it possible to look beyond the term 'algorithmic accountability'. That is, the query also included terms closely connected to the theme (e.g. ethics and AI, regulation of algorithms). This approach allows for a perspective not just from critical algorithm studies, but an interdisciplinary overview drawing on material from data studies to law, and from computer science to governance studies. To structure the material, Bovens's widely accepted definition of accountability serves as a focal point. The material is analyzed on the five points Bovens identified as integral to accountability: its arguments on (1) the actor, (2) the forum, (3) the relationship between the two, (3) the content and criteria of the account, and finally (5) the consequences which may result from the account. The review makes three contributions. First, an integration of accountability theory in the algorithmic accountability discussion. Second, a cross-sectoral overview of the that same discussion viewed in light of accountability theory which pays extra attention to accountability risks in algorithmic systems. Lastly, it provides a definition of algorithmic accountability based on accountability theory and algorithmic accountability literature.

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References

2009The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration 1981Street-Level Bureaucracy: Dilemmas of the Individual in Public Services 2016The ethics of algorithms: Mapping the debate 2006Meeting the Universe Halfway 2018Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor 2016How the machine ‘thinks’: Understanding opacity in machine learning algorithms 2007Analysing and Assessing Accountability: A Conceptual Framework 1 2016Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability

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2023AI governance: themes, knowledge gaps and future agendas 2021Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure 2022Trustworthy AI: A Computational Perspective 2021Re-imagining Algorithmic Fairness in India and Beyond 2021Algorithmic Impact Assessments and Accountability

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