The DOI matches its Crossref record; 29 of the 33 references it cites were found in a registry or an index.
Public’s views of risk assessment algorithms and pretrial decision making
Open accessAbstract
Risk assessment algorithms are increasingly–and controversially–being used to inform whether criminal defendants are released or held in custody prior to their adjudications. A representative sample of Californians (n=420)–the most recent state to consider eliminating cash bail and adopting an algorithmic approach to pretrial detention–was used to assess public knowledge and general support for the new law. The sample evidenced limited awareness of bail reform, was mixed in support of change to the current system, and believed that an algorithm would augment rather than decrease racial and socioeconomic disparities. In terms of actually implementing a risk assessment algorithm for the purpose of pretrial decision making, it is ultimately a decision maker who must apply a decision threshold and determine whether a given risk level is sufficient to occasion a particular course of action (e.g., deny pretrial release). The sample was also queried about their pretrial decision thresholds. The average respondent’s decision threshold for “low risk” (or pretrial release) was 33%, indicating a 33% or less likelihood of failing to reappear or committing a new crime was tolerable, and 60% for “high risk” (or confinement), indicating a likelihood of 60% or greater of failing to reappear or committing a new crime was acceptable to deny a defendant release. Incorporating the public’s values into the decision-making process is likely to promote the legitimacy of the use of risk assessment a…
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“Even when such variables are prohibited from use in AI models, other related variables such as employment stability, two-parent households, neighbourhoods, etc. can become proxies for race and socio-economic clusters leading to higher predictability”
From AI adoption and diffusion in public administration: A systematic literature review and future research agenda (2023) · cites this paper as Scurich & Krauss, 2020
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Madan, R., & Ashok, M. (2023) · Government Information Quarterly · doi:10.1016/j.giq.2022.101774 · Cited by 468
“Even when such variables are prohibited from use in AI models, other related variables such as employment stability, two-parent households, neighbourhoods, etc. can become proxies for race and socio-economic clusters leading to higher predictability (Scurich & Krauss, 2020).”
Social equity in the data era: A systematic literature review of data‐driven public service research
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Predictive Validity of Pretrial Risk Assessments: A Systematic Review of the Literature
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Investigating Algorithmic Risk and Race
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The Empirical Case for Pretrial Risk Assessment Instruments
Desmarais, S. L., Monahan, J. T., & Austin, J. (2021) · Criminal Justice and Behavior · doi:10.1177/00938548211041651 · Cited by 35
Metadata
- Authors
- Scurich, N., & Krauss, D. A.
- Affiliations
- University of California, Irvine (US)
- Claremont McKenna College (US)
- Venue
- Psychology, Public Policy, and Law
- Published
- 2020-02
- Volume
- 26
- Issue
- 1
- Pages
- 1-9
- ISSN
- 1076-8971 (ISSN-L)
- 1939-1528
- OpenAlex
- W2993938946
- Cited by
- 17
- References
- 33
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 3 · 2023: 2 · 2022: 4 · 2021: 4 · 2020: 1
- FWCI
- 4.53
- Type
- journal article
- Language
- en
- Open access
- green
- papers.ssrn.com
- Locations
- Psychology Public Policy and Law (publishedVersion)
- SSRN Electronic Journal (submittedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Criminal Justice and Corrections Analysis
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Law › Artificial Intelligence in Law
- Keywords
- risk assessment algorithm, pretrial detention, bail reform, public opinion, public support, racial disparities, socioeconomic disparities, decision threshold, pretrial release, algorithmic decision-making, legitimacy
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