Across two vignette experiments, liberals and racial minorities rated affirmative algorithms as favorably as fair ones, while conservatives and White participants rated them as negatively as discriminatory algorithms, with beliefs about marginalization named as the source.
"Look! It's a Computer Program! It's an Algorithm! It's AI!": Does Terminology Affect Human Perceptions and Evaluations of Algorithmic Decision-Making Systems?
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abstract
In the media, in policy-making, but also in research articles, algorithmic decision-making (ADM) systems are referred to as algorithms, artificial intelligence, and computer programs, amongst other terms. We hypothesize that such terminological differences can affect people's perceptions of properties of ADM systems, people's evaluations of systems in application contexts, and the replicability of research as findings may be influenced by terminological differences. In two studies (N = 397, N = 622), we show that terminology does indeed affect laypeople's perceptions of system properties (e.g., perceived complexity) and evaluations of systems (e.g., trust). Our findings highlight the need to be mindful when choosing terms to describe ADM systems, because terminology can have unintended consequences, and may impact the robustness and replicability of HCI research. Additionally, our findings indicate that terminology can be used strategically (e.g., in communication about ADM systems) to influence people's perceptions and evaluations of these systems.
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cs.CY 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
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Laypeople's Attitudes Towards Fair, Affirmative, and Discriminatory Decision-Making Algorithms
Across two vignette experiments, liberals and racial minorities rated affirmative algorithms as favorably as fair ones, while conservatives and White participants rated them as negatively as discriminatory algorithms, with beliefs about marginalization named as the source.