ArticleArtificial intelligence and law2023
Perceptions of Justice By Algorithms.
Article in Artificial intelligence and law, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 51 citations in OpenAlex.
- Invulnerability bias in perceptions of artificial intelligence's future impact on employment.Scientific reports · 2025Article
- Exploring condition in which people accept AI over human judgements on justified defection.Scientific reports · 2025Article
- Judges versus artificial intelligence in juror decision-making in criminal trials: Evidence from two pre-registered experiments.PloS one · 2025Article
- Trustworthy artificial intelligence and the European Union AI act: On the conflation of trustworthiness and acceptability of risk.Regulation & governance · 2024Article
- Algorithms in the court: does it matter which part of the judicial decision-making is automated?Artificial intelligence and law · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence and algorithms are increasingly able to replace human workers in cognitively sophisticated tasks, including ones related to justice. Many governments and international organizations are discussing policies related to the application of algorithmic judges in courts. In this paper, we investigate the public perceptions of algorithmic judges. Across two experiments (N = 1,822), and an internal meta-analysis (N = 3,039), our results show that even though court users acknowledge several advantages of algorithms (i.e., cost and speed), they trust human judges more and have greater intentions to go to the court when a human (vs. an algorithmic) judge adjudicates. Additionally, we demonstrate that the extent that individuals trust algorithmic and human judges depends on the nature of the case: trust for algorithmic judges is especially low when legal cases involve emotional complexities (vs. technically complex or uncomplicated cases). Supplementary Information: The online version contains supplementary material available at 10.1007/s10506-022-09312-z.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.