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AI and Human Rights: Criminal Justice System

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Automated decision-making tools are used widely and opaquely both directly in the criminal justice system and in ways that directly feed the criminal justice cycle in the U.S. The map above is a necessarily incomplete representation of these tools. One of the largest reasons is a lack of transparency by design. Affected people are often unable to know what tools the jurisdictions they live in use because of trade secret carveouts in Open Government laws, as well as similar roadblocks in evidentiary and discovery rules. The explanations, documents, and chart showing what tools are used where below are a representation of the patchwork of jurisdictions that are occasionally forthright about the tools they use, the outputs of Open Government requests, and news items often exposing a problematic use of one of the tools.

The tools

Predictive Policing Tools include "any policing strategy or tactic that develops and uses information and advanced analysis to inform forward-thinking crime prevention," according to the National Institute of Justice. Predictive policing comes in two main forms: location-based and person-based. Location-based predictive policing works by identifying places of repeated property crime and trying to predict where they would occur next, while person-based predictive policing aims to pinpoint who might be committing a crime - trying to measure the risk that a given individual will commit crimes. Both are used in different jurisdictions, and use past policing data as the main driver of these predictions, necessarily creating a self-fulfilling prophecy of arresting resources. The Bureau of Justice Assistance has and continues to give grants to Police departments around the country to create and pilot these programs. However, two high profile systems in Chicago and Los Angeles have been shut down due to limited effectiveness and significant demonstrated bias.

Helpful terms to remember:

Automated decision-making tools are tools or systems that analyze data in order to aid in decision-making -- these can vary from simple algorithms to machine learning programs. Most of the systems discussed on this page are automated decision-making systems.

Algorithms are functions that analyze data using a defined set of instructions and yield an output based on the instructions.

Artificial Intelligence (AI) is a broad term used to describe computational systems used to automate or optimize decision-making processes based on a wide range of data inputs.

Machine learning AI is an increasingly common data analysis technique that uses an algorithm or system that can adapt over time based on its inputs and outputs.

Surveillance tools encompass a large swath of technologies and functions that can be used to watch, track, and store information about a person. This ranges from Ring doorbells, whose servicer has direct partnerships with law enforcement, to facial recognition systems at the border and in U.S. cities. Learn more about this topic and EPIC's work here.

Criminalizing algorithms include algorithms used in housing, credit determinations, healthcare, hiring, schooling, and more. Many of these have been shown to make recommendations and decisions that negatively affect marginalized communities, encoding systemic racism, and contribute to entry of the Criminal Justice system. All of the other tools discussed here are affected by the results and data points produced by these criminalizing algorithms.

Risk Assessment Tools are used in almost every state in the U.S. - and many use them pre-trial, although they exist at sentencing, in prison management, and for parole determinations. There are also specific risk assessment tools for different functions in the criminal justice system, such as domestic violence risk or juvenile justice risks, with the understanding that different factors are used in those contexts than in a general criminal risk or violent criminal risk of rearrest or re-offense.

Liberty At Risk imagePretrial Risk Assessment tools are designed to attempt to predict future behavior by defendants and incarcerated persons, and quantify that risk. They use socioeconomic status, family background, neighborhood crime, employment status, and other factors to reach a supposed prediction of an individual's criminal risk, either on a scale from "low" to "high" or with specific percentages. Significant empirical research has shown disparate impacts of Risk Assessment Tools on criminal justice outcomes based on the race, ethnicity, and age of the accused. The concerns with the use of these tools don't stop there. The tools vary but estimate using "actuarial assessments" (1) the likelihood that the defendant will re-offend before trial ("recidivism risk") and (2) the likelihood the defendant will fail to appear at trial ("FTA"). These often proprietary techniques are used to set bail, determine sentences, and even contribute to determinations about guilt or innocence. Yet the inner workings of these tools are largely hidden from public view. As a result, two people accused of the same crime may receive sharply different bail or sentencing outcomes based on inputs that are beyond their control--but have no way of assessing or challenging the results.

As criminal justice algorithms have come into greater use at the federal and state levels, they have also come under greater scrutiny. Many criminal justice experts have denounced "risk assessment" tools as opaque, unreliable, and unconstitutional.

A 2016 investigation by ProPublica tested the COMPAS system adopted by the state of Florida using the same benchmark as COMPAS: a likelihood of re-offending in two years. ProPublica found that the formula was particularly likely to flag black defendants as future criminals, labeling them as such at almost twice the rate as white defendants. In addition, white defendants were labeled as low risk more often than black defendants. But the investigators also found that the scores were unreliable in forecasting violent crime: only 20 percent of the people predicted to commit violent crimes actually went on to do so. When considering a full range of crimes, including misdemeanors, the correlation was found to be higher but not exceedingly accurate. Sixty-one percent of the candidates deemed liked to reoffend were arrested for any subsequent crimes within two years. According to ProPublica, some miscalculations of risk stemmed from inaccurate inputs (for example, failing to include one's prison record from another state), while other results were attributed to the way factors are weighed (for example, someone who has molested a child may be categorized as low risk because he has a job, while someone who was convicted of public intoxication would be considered high risk because he is homeless).

COMPAS is one of the most widely used algorithms in the country. Northpointe published a validation study of the system in 2009, but it did not include an assessment of predictive accuracy by ethnicity. It referenced a study that had evaluated COMPAS' accuracy by ethnicity, which reported weaker accuracy for African-American men, but claimed the small sample size rendered it unreliable. Northpointe has not shared how its calculations are made but has stated that the basis of its future crime formula includes factors such as education levels and whether a defendant has a job. Many jurisdictions have adopted COMPAS, and other "risk assessment" methods generally, without first testing their validity.

Defense advocates are calling for more transparent methods because they are unable to challenge the validity of the results at sentencing hearings. Professor Danielle Citron argues that because the public has no opportunity to identify problems with troubled systems, it cannot present those complaints to government officials. In turn, government actors are unable to influence policy

Over the last several years, prominent groups such as Pretrial Justice Institute (PJI) strongly advocated for the introduction of these tools and the Public Safety Assessment among many other risk assessments has been adopted in nearly every state, up from only a handful in the beginning of the decade. However, in February 2020, PJI reversed this position, specifically stating that they "now see that pretrial risk assessment tools, designed to predict an individual’s appearance in court without a new arrest, can no longer be a part of our solution for building equitable pretrial justice systems." One week later, Public Safety Assessment, a widely used risk assessment developed by the Laura and John Arnold Foundation, released a statement in which they clarify that "implementing an assessment cannot and will not result in the pretrial justice goals we seek to achieve."

Transparency is seldom required with pre-trial risk assessments. One of the primary criticisms of these risk assessment tools is that they are proprietary tools, developed by technology companies that refuse to disclose the inner workings of the "black box." Trade secret and other IP protection defenses have been given to demands of the underlying logic of the systems. In March 2019, Idaho became the first state to enact a law specifically promoting transparency, accountability, and explainability in pre-trial risk assessment tools. Pre-trial risk assessments are algorithms that help inform sentencing and bail decisions for defendants. The law prevents a trade secrecy or IP defense, requires public availability of 'all documents, data, records, and information used by the builder to build or validate the pretrial risk assessment tool,' and empowers defendants to review all calculations and data that went into their risk score.

For a deeper dive into Pre-Trial Risk Assessments, visit EPIC's report: "Liberty At Risk, Pre-trial Risk Assessment Tools in the U.S."

Risk Assessment Tools State-By-State

The following table is based on a survey of state practices by EPIC performed September 2019, updated February 2020 with Mississippi FOI Documents. The functions vary between pre-trial, sentencing, prison management, and parole. Most of these tools, including their existence, are largely opaque and change often.

STATE TYPE/SCOPE OF USE (if known) Has the state conducted a validity study?
Alabama VPRAI / Jefferson County Yes
Alaska State Created / Statewide Yes
Arizona PSA / Statewide | VPRAI / 2 County Superior Courts Unknown
Arkansas State Created / Statewide Yes
California (Sample risk assessment documents from San Francisco, and Napa County) PSA / 3 counties | PRRS II / 2 Counties In Progress
Colorado (sample risk assessment documents) CPAT / Statewide | ODARA for DV / Statewide In Progress
Connecticut State created / Statewide Yes
Delaware State created (DELPAT) / Statewide Yes
District of Columbia (see FOI documents below) Maxarth | District Wide Yes
Florida PSA / Volusia County | COMPAS - Sentencing / Statewide | State Created FPRAI Being piloted / 6 Counties Yes
Georgia State created / Some counties Unknown
Hawaii PSA / Statewide | ORAS-PAT / Statewide Yes
Idaho (see FOI documents below) State created / Statewide | Ada County / Revised IPRAI Yes
Illinois PSA / 3 counties | VPRAI/RVRA / Most Courts Yes
Indiana (sample risk assessment documents) Mandatory use of IRAS and IYAS / Statewide Yes
Iowa PSA / 4 Counties via Pilot Program | IRR Yes
Kansas State created / Johnson County Unknown
Kentucky PSA / Statewide Yes
Louisiana PSA / Orleans Parish Yes
Maine ODARA (sex offenders) / Statewide | 2019 Task Force for expansion Unknown
Maryland State created / Most counties Yes
Massachusetts Currently under debate, however not used yet N/A
Michigan COMPAS for Sentencing / Statewide Yes
Minnesota (see Pretrial Release Evaluation Form and Bench Card) MNPAT / Statewide In Progress
Mississippi Yes / Statewide Required every 3 years by 2019 law
Missouri (see FOI documents below) Statewide / State created | Separate statewide system for Juvenile and Sex Offenders | Use Oregon Public Safety Checklist for Sentencing Yes:
Montana PSA / Five Counties Yes
Nebraska (see FOI documents below and sample assessments) Site of Federal PSRAT Piloting/Testing Yes
Nevada State created / Statewide Mar. 2019 by NV Supreme Court Yes
New Hampshire Ohio Risk Assessment System (O-RAS) Yes (2017)
New Jersey PSA / Statewide Yes
New Mexico PSA / 1 County | ODARA for DV Yes
New York (NYC) Criminal Justice Agency / Some Courts |State Created / State-wide for Parole Yes
North Carolina PSA / 1 County | Developing another statewide one Yes
Ohio PSA / 1 County | ORAS-PAT / Statewide Yes
Oklahoma ORAS for Pretrial Services Program + LSI/R / Statewide Yes
Oregon (sample assessments) Public Safety Checklist Yes
Pennsylvania PSA / Statewide | State created / 1 County Yes
Rhode Island PSA / Statewide Yes
South Carolina State Created - Cash Bail Use Unknown
South Dakota PSA / 2 Counties Yes
Tennessee State Created / One Judicial District Test In Progress
Texas (sample assessments) PSA / Harris County | PRAISTX (derivative of ORAS) / Statewide Parole Board Yes
Utah PSA / Statewide Yes
Vermont Statutory Authorization for Risk & Needs Assessment Unknown
Virginia VPRAI revised by Luminosity / Statewide | Use Oregon Public Safety Checklist for Sentencing Yes
Washington PSA / One County Yes
West Virginia LS/CMI Yes
Wisconsin (See FOI documents below and sample assessment documents) PSA / 2 Counties | COMPAS / Statewide Yes
Wyoming COMPAS for Prisoners / Statewide Unknown
Federal PTRA Yes

* Bill enacted Mar. 2019: requires transparency, notification, and explainability.
**There is no official compendium of Risk Assessments used by states.

Abbreviations Key:

DV - Domestic Violence
COMPAS - Correctional Offender Management Profiling for Alternative Sanctions
PSA - Pretrial Safety Assessment
PTRA - Pretrial Risk Assessment Instrument
CPAT - Colorado Pretrial Assessment Tool
PRRS - Pretrial Release Risk Scale
DELPAT - Delaware Pretrial Assessment Tool
ODARA - Ontario Domestic Assault Risk Assessment Tool
MNPAT - Minnesota Pretrial Assessment Tool
ORAS - Ohio Risk Assessment System
LS/CMI - Level of Service/Case Management Inventory
PRAISTX - Pretrial Risk Assessment Information System
VPRAI - Virginia Pretrial Risk Assessment Instrument
IRAS - Indiana Risk Assessment System

EPIC's Interest

EPIC has a strong interest in open government. Public disclosure of this information improves government oversight and accountability. It also helps ensure that the public is fully informed about the activities of government. EPIC routinely files lawsuits to force disclose of agency records that impact critical privacy interests.

EPIC also has a strong interest in algorithmic transparency. Secrecy of the algorithms used to determine guilt or innocence undermines faith in the criminal justice system. In support of algorithmic transparency, EPIC submitted FOIA requests to six states to obtain the source code of "TrueAllele," a software product used in DNA forensic analysis. According to news reports, law enforcement officials use TrueAllele test results to establish guilt, but individuals accused of crimes are denied access to the source code that produces the results.

The Universal Guidelines for Artificial Intelligence, grounded in a human rights framework, set forth twelve principles that are intended to guide the design, development, and deployment of AI, and frameworks for policy and legislation. Broadly, the guidelines address the rights and obligations of: 1) fairness, accountability, and transparency; 2) autonomy and human determination; 3) data accuracy and quality; 4) safety and security; and 5) minimization of scope. These principles can also guide the use of algorithms in the pre-trial risk context.

The very first principle, transparency, is seldom required with pre-trial risk assessments. One of the primary criticisms of these risk assessment tools is that they are proprietary tools, developed by technology companies that refuse to disclose the inner workings of the “black box.” Trade secret and other IP protection defenses have been given to demands of the underlying logic of the systems. In March 2019, Idaho became the first state to enact a law specifically promoting transparency, accountability, and explainability in pre-trial risk assessment tools. Pre-trial risk assessments are algorithms that help inform sentencing and bail decisions for defendants. The law prevents a trade secrecy or IP defense, requires public availability of ‘all documents, data, records, and information used by the builder to build or validate the pretrial risk assessment tool,’ and empowers defendants to review all calculations and data that went into their risk score.

EPIC FOI Documents

EPIC obtained the following documents concerning criminal justice algorithms through state freedom of information requests.

  • District of Columbia
  • Georgia
  • Idaho
  • Missouri
  • Mississippi
  • Nebraska
  • New Hampshire
  • Vermont
  • Wisconsin
  • Resources

    Legislation and Regulations

    Government Studies

    Notable Cases

    • EPIC v. DOJ (Suit for records of Criminal Justice Algorithms by the Federal Government)
    • EPIC v. CPB (Suit for documents of secret analytical tools to assign risk assessments to travelers)
    • EPIC v. DHS (Suit for records of DHS program that predicts crime risk based on “physiological and behavioral signals”)
    • United States v. Booker, 125 S. Ct. 738 (2005)
    • Mistretta v. United States, 109 S. Ct. 647 (1989)
    • State v. Loomis, No. 16-6387 (U.S.) (Wisconsin case in which defendant has petitioned U.S. Supreme Court for certiorari)
    • Iowa v. Guise, 921 N.W.2d 235 (2016).
    • Doe v. Sex Offender Registry Board, 466 Mass. 594, 999 N.E.2d 478 (2013) (holding that the Sex Offender Registry board arbitrarily ignored scientific evidence that female offenders generally pose a much lower risk of re-offense; SORB was empowered to consider any useful information including scientific evidence introduced by offender in arriving at a classification decision, and authoritative evidence was introduced suggesting that establish "risk assessment" guidelines, developed from studies of male offenders, could not predict accurately the recidivism risk of a female offender, and that such risk could not be evaluated without examining the effect of gender)
    • Malenchik v. State, No. 79A02-0902-CR-133 (Ind. Ct. App. June 5, 2009) (holding that it was not improper for the trial court to take into consideration a defendant’s LSI-R score at sentencing)
    • In re CDK, 64 S.W.3d 679 (Tex. App. 2002) (holding that admitting an assessment report on a father’s sexual deviancy as expert witness testimony was an abuse of discretion because the plaintiff did not provide how the formulas were derived and whether they have ever been subjected to analysis or testing.

    Academic Articles

    Other resources


    Documents and Reports

    • Pretrial Justice Institute (PJI) No longer recommend Risk Assessment Tools, February 7, 2020.
    • Sample COMPAS risk assessment questionnaire - Wisconsin's 137 question risk assessment
    • Sample sentencing reports judges receive that includes risk assessment results
    • Jennifer Elek, Roger Warren & Pamela Casey, Using Risk and Needs Assessment Information at Sentencing: Observations from Ten Jurisdictions, National Center for State Courts’ Center for Sentencing Initiatives
    • Tara Agense & Shelley Curran, The California Risk Assessment Pilot Project: The Use of Risk and Needs Assessment Information in Adult Felony Probation Sentencing and Violation Proceedings, Judicial Council of California Operations and Programs Division Criminal Justice Services (December 2015)


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