Journal article
The algorithm audit: Scoring the algorithms that score us
Big data & society, Vol.8(1), p.205395172098386
01/01/2021
DOI: 10.1177/2053951720983865
Abstract
In recent years, the ethical impact of AI has been increasingly scrutinized, with public scandals emerging over biased outcomes, lack of transparency, and the misuse of data. This has led to a growing mistrust of AI and increased calls for mandated ethical audits of algorithms. Current proposals for ethical assessment of algorithms are either too high level to be put into practice without further guidance, or they focus on very specific and technical notions of fairness or transparency that do not consider multiple stakeholders or the broader social context. In this article, we present an auditing framework to guide the ethical assessment of an algorithm. The audit instrument itself is comprised of three elements: a list of possible interests of stakeholders affected by the algorithm, an assessment of metrics that describe key ethically salient features of the algorithm, and a relevancy matrix that connects the assessed metrics to stakeholder interests. The proposed audit instrument yields an ethical evaluation of an algorithm that could be used by regulators and others interested in doing due diligence, while paying careful attention to the complex societal context within which the algorithm is deployed.
Details
- Title: Subtitle
- The algorithm audit: Scoring the algorithms that score us
- Creators
- Shea Brown - University of IowaJovana Davidovic - University of IowaAli Hasan - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Big data & society, Vol.8(1), p.205395172098386
- DOI
- 10.1177/2053951720983865
- ISSN
- 2053-9517
- eISSN
- 2053-9517
- Publisher
- Sage
- Number of pages
- 8
- Language
- English
- Date published
- 01/01/2021
- Academic Unit
- Physics and Astronomy; Law Faculty; Philosophy
- Record Identifier
- 9984397199002771
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