26022
post-template-default,single,single-post,postid-26022,single-format-standard,stockholm-core-2.4,qodef-qi--no-touch,qi-addons-for-elementor-1.6.7,select-theme-ver-9.5,ajax_fade,page_not_loaded,,qode_menu_,wpb-js-composer js-comp-ver-7.4,vc_responsive,elementor-default,elementor-kit-38031
Title Image

Trade Secrets and the Criminal Justice System

Trade Secrets and the Criminal Justice System

While artificial intelligence was originally limited to use within the tech industry, it has since been adopted by a variety of industries due to the increased availability of data, algorithms and computing power.[1] As such, artificial intelligence has infiltrated the criminal justice system and is used at every stage from policing, investigations, pretrial suppression hearings, assessment of guilt during trials, as well as sentencing through parole hearings.[2]

For example, in 2015, a California appellate court denied a death penalty defendant Martell Chubbs access to the code of a forensic software program used to prove his guilt at trial, holding that the source code was protected by trade secret law.[3] The program in question was used to calculate the likelihood of Chubbs’s DNA being part of the DNA sample taken from the crime scene.[4] Even though the trial court ordered the developer to disclose the code subject to a protective order, the appellate court struck down the order, citing California’s statutory trade secret privilege.[5]

In addition, there are many risk-assessment algorithms that are currently used in courtrooms across the United States.[6] A company called Correctional Offender Management Profiling for Alternative Sanctions (COMPAS) “purports to predict a defendant’s risk of committing another crime” by utilizing “a proprietary algorithm that considers some of the answers to a 137-item questionnaire.”[7]

In 2016, defendant Eric Loomis was sentenced to six years in prison because his COMPAS rating indicated that he had a “high risk of recidivism.”[8] The court did not allow Loomis to access any of the information regarding how the algorithm weighed the various input variables and their effect on his final risk score, holding that this information was protected by trade secret law.[9]

There are many intellectual property privacy consequences stemming from artificial intelligence, most notably with regard to trade secret law.[10] Because the purpose of trade secret law is to stimulate the creation and diffusion of information, “it is inextricably intertwined with fundamental rights to freedom of expression and access to information.”[11] When it comes to algorithms, trade secret law seems especially necessary for developers, given that “disclosure of how the product works not only undermines its protection, it can destroy the creator’s ability to exploit their intellectual property and can even render the product ineffective.”[ footnote]Id.[/mfn] However, with trade secret protections, algorithms have the ability to “perpetuate and exacerbate existing discriminatory social structures”[12] due to the lack of transparency.

Footnotes[+]

Karunya Venugopal

Karunya Venugopal is a second-year J.D. candidate at Fordham University School of Law and a staff member of the Intellectual Property, Media & Entertainment Law Journal. She is also a committee member on Fordham Law Women and an executive board member of Fordham First Generation Students. She holds a B.A. in Political Science from Bryn Mawr College.