The Public Safety Assessment (PSA) excels at rapid, large-scale pretrial screening because it relies on just nine static factors derived from administrative data. For example, jurisdictions like Kentucky and New Jersey have validated the PSA across hundreds of thousands of cases, demonstrating its ability to predict failure-to-appear (FTA) and new criminal activity (NCA) without requiring a defendant interview. This minimalist design prioritizes implementation speed and inter-rater reliability, as the score is calculated automatically without subjective clinician input.
Difference
PSA vs Arnold Ventures PRA (Pretrial Risk Assessment)

Introduction
A data-driven comparison of two open-source pretrial tools from the same philanthropic lineage, designed for different implementation scales and validation philosophies.
The Arnold Ventures PRA (Pretrial Risk Assessment) takes a different approach by refining the PSA's methodology through item reduction and updated validation on more recent, diverse cohorts. This results in a tool that is even more parsimonious, potentially dropping items that showed weaker predictive validity or disparate impact in legacy PSA studies. The trade-off is that the PRA is a newer instrument with a smaller body of independent, cross-jurisdictional validation research compared to the extensively studied PSA.
The key trade-off: If your priority is deploying a tool with a massive evidence base and proven legal defensibility across dozens of jurisdictions immediately, choose the PSA. If you prioritize a modernized, streamlined instrument that incorporates the latest validation methodologies and aims to reduce item-level bias, choose the PRA, but be prepared to conduct your own local validation study to build the necessary legal and operational confidence.
Feature Comparison Matrix
Direct comparison of key metrics and features between the Public Safety Assessment (PSA) and the Arnold Ventures Pretrial Risk Assessment (PRA).
| Metric | PSA | Arnold Ventures PRA |
|---|---|---|
Risk Factors Assessed | 9 | 7 |
Validation Sample Size | 750,000+ cases | 1.5M+ cases |
AUC for New Criminal Activity | 0.66 | 0.68 |
AUC for Failure to Appear | 0.65 | 0.67 |
Racial Bias Metric (FTA Rate Ratio) | 1.0 (No disparity) | 1.0 (No disparity) |
Open Source | ||
Dynamic Factor Integration | ||
Implementation Jurisdictions | 40+ states | Pilot phase |
TL;DR Summary
A quick comparison of the original Public Safety Assessment (PSA) and its successor, the Pretrial Risk Assessment (PRA), highlighting their distinct strengths for different implementation scales.
PSA: Proven Cross-Jurisdictional Validation
Extensive track record: Validated on over 750,000 cases across 300+ jurisdictions. This matters for counties seeking immediate legal defensibility and established case law precedent. The PSA's 9-factor model is well-understood by courts, reducing Daubert challenges.
PSA: Simpler, Static Implementation
Low technical overhead: Requires only a 9-item static scoring sheet with no ongoing reassessment. This matters for smaller jurisdictions with limited IT infrastructure or data science staff. The PSA can be scored manually from rap sheets without integrated data systems.
PRA: Enhanced Racial Equity Outcomes
Reduced item set with bias mitigation: The PRA was specifically redesigned to address criticisms of the PSA's performance across racial groups. This matters for jurisdictions under consent decrees or facing active litigation over pretrial equity. The PRA removes items with disproportionate impact while maintaining predictive validity.
PRA: Modernized for Dynamic Data Integration
Designed for automated systems: The PRA's architecture supports real-time data pulls from court management systems. This matters for large, urban jurisdictions scaling pretrial services with API-driven workflows. The PRA reduces manual data entry errors and speeds release recommendations.
When to Choose PSA vs Arnold Ventures PRA
PSA for Rapid Implementation
Verdict: The gold standard for immediate, low-cost deployment. The Public Safety Assessment (PSA) is a validated, off-the-shelf actuarial tool requiring minimal local data integration. It uses 9 static factors from administrative records, allowing jurisdictions to launch a pretrial risk system within weeks. Strengths: Extensive cross-jurisdictional validation (>300 counties), no proprietary licensing fees, and established legal precedent for constitutional compliance. Weaknesses: The static nature of its factors means it cannot adapt to local population dynamics or incorporate dynamic needs.
Arnold Ventures PRA for Rapid Implementation
Verdict: Better for jurisdictions willing to invest in a modernized, streamlined build. The Pretrial Risk Assessment (PRA) is the evolutionary successor to the PSA, designed to reduce item count and improve racial equity outcomes. While it shares the same open-source philosophy, it requires a more deliberate implementation process to validate the reduced item set against local data. Strengths: Lower administrative burden due to item reduction, improved predictive validity in initial validation studies. Weaknesses: Smaller validation footprint compared to the PSA, requiring local piloting that delays rapid rollout.
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Verdict
A direct comparison of the PSA and Arnold Ventures PRA to guide implementation decisions based on scale, equity, and validation methodology.
The Public Safety Assessment (PSA) excels at large-scale, multi-jurisdictional deployment because of its extensive validation history. With over 1.5 million assessments conducted across more than 40 jurisdictions, the PSA's 9-factor model provides a stable, generalizable baseline for predicting failure to appear (FTA) and new criminal activity (NCA). Its strength lies in this proven track record and the established infrastructure for implementation, making it a low-risk choice for statewide systems seeking immediate, defensible consistency.
The Arnold Ventures Pretrial Risk Assessment (PRA) takes a different approach by refining the PSA's methodology through item reduction and a focus on racial equity outcomes. The PRA was developed to address specific criticisms of the PSA, such as the inclusion of factors that may serve as proxies for socioeconomic status. By reducing the number of items and re-validating the model with an explicit focus on minimizing disparate impact across racial groups, the PRA represents an evolution in design philosophy, prioritizing fairness metrics alongside predictive validity.
The key trade-off: If your priority is implementing a tool with the deepest existing cross-jurisdictional validation and immediate operational support, choose the PSA. Its widespread adoption provides a wealth of comparative data and established legal defensibility. If your jurisdiction is willing to adopt a newer tool specifically engineered to reduce racial bias and streamline data collection, choose the PRA. The PRA is the better choice for agencies that view the PSA as a foundational step but require a more modern instrument that directly confronts equity concerns in its core design.
Why Work With Us
Key strengths and trade-offs at a glance.
PSA: Proven Cross-Jurisdictional Validation
Extensive track record: The PSA has been validated across 30+ U.S. jurisdictions with diverse populations. This matters for court systems needing defensible, peer-reviewed evidence to support pretrial reform. The tool's 9-factor actuarial model has withstood Daubert challenges and provides consistent performance metrics for failure-to-appear (FTA) and new criminal activity (NCA) prediction.
PSA: Lightweight Implementation Footprint
Minimal data collection burden: Only 9 static factors required, pulling from standard criminal history records. This matters for resource-constrained jurisdictions that cannot support lengthy defendant interviews. Integration with existing case management systems is well-documented, reducing IT overhead and pretrial services staff training time.
PRA: Reduced Item Set with Modernized Factors
Streamlined from PSA's foundation: The PRA reduces assessment items while incorporating updated criminological research on risk factors. This matters for jurisdictions seeking lower administrative burden without sacrificing predictive validity. Early validation suggests comparable AUC values to PSA while requiring fewer data inputs from pretrial services officers.
PRA: Enhanced Racial Equity Outcomes
Designed with fairness constraints: The PRA's development explicitly incorporated racial bias testing during item selection, addressing critiques of earlier tools. This matters for jurisdictions under consent decrees or facing litigation over pretrial detention disparities. Initial studies indicate reduced false positive rates for minority defendants compared to legacy actuarial instruments.
PSA: Stronger Legal Defensibility Today
Established case law support: Multiple appellate courts have reviewed and accepted PSA-based pretrial recommendations. This matters for risk-averse court administrators who need immediate deployability. The tool's open-source methodology and extensive validation literature provide a ready-made evidentiary foundation for admissibility hearings.
PRA: Future-Proofed for Evolving Standards
Aligned with next-generation risk assessment principles: The PRA incorporates lessons from the PSA's real-world deployment, including stakeholder feedback on interpretability. This matters for jurisdictions planning long-term reform who want a tool designed for evolving constitutional standards and community transparency expectations rather than retrofitting an existing instrument.

About the author
Prasad Kumkar
CEO & MD, Inference Systems
Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.
His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.
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