Mapping the Field of Algorithm Auditing: A Systematic Literature Review Identifying Research Trends, Linguistic and Geographical Disparities
CoRR(2024)
摘要
The increasing reliance on complex algorithmic systems by online platforms
has sparked a growing need for algorithm auditing, a research methodology
evaluating these systems' functionality and societal impact. In this paper, we
systematically review algorithm auditing studies and identify trends in their
methodological approaches, the geographic distribution of authors, and the
selection of platforms, languages, geographies, and group-based attributes in
the focus of auditing research. We present evidence of a significant skew of
research focus toward Western contexts, particularly the US, and a
disproportionate reliance on English language data. Additionally, our analysis
indicates a tendency in algorithm auditing studies to focus on a narrow set of
group-based attributes, often operationalized in simplified ways, which might
obscure more nuanced aspects of algorithmic bias and discrimination. By
conducting this review, we aim to provide a clearer understanding of the
current state of the algorithm auditing field and identify gaps that need to be
addressed for a more inclusive and representative research landscape.
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