Balancing Justice: The Role of Artificial Intelligence in the Courtroom
In the realm of law, Artificial Intelligence (AI) has played an increasing role in nearly every facet of the field. Specifically, AI has been slowly integrating itself within the courtroom through case management, document processing, and increasing the efficiency of administrative workflows. [1] Predictive analysis relates to harnessing AI and machine learning to efficiently analyze large sets of data that include prior case rulings and judicial decisions. Through predictive analysis in legal decision-making, future legal outcomes can be predicted, and strategies can be guided by identifying patterns and trends. [2] However, it is imperative to note that these algorithms can also contribute to harmful algorithmic bias and can have a plethora of ethical and legal challenges.
There is currently a wide array of applications of artificial intelligence in the courtroom. To begin, AI-powered legal research is used to enhance the speed and accuracy of legal work. Through leveraging natural language processing and machine learning algorithms, the technology is able to analyze a large amount of data and offer useful insights and automation of legal research and analysis. [3] By implementing virtual legal assistants and chatbots for immediate legal queries, AI is proving to be a more efficient and cheaper alternative for law firms. Currently, the industry is moving from non-specialized AI to AI trained on large datasets of legal materials, where it can oftentimes produce more sophisticated versions than most lawyers. Furthermore, with access to the world's best lawyers being highly expensive, AI seems to be the next best option.
In terms of predictive analysis in legal decisions, there are five key areas in which it can help. To begin, by assessing outcomes from previous cases and the number of judgments and settlements, predictive data analysis can offer an objective answer to whether or not a matter should be litigated or settled. Furthermore, predictive data analysis can answer the question of whether or not a motion will prevail as history tends to repeat itself, and success rates of similar motions can be assessed. Additionally, valuations of certain entities within the legal realm can be better identified through prior patterns. Lastly, whether or not a case can be pursued more efficiently can be assessed by predictive analysis. By harnessing prior legal data, predictive data analysis can revolutionize the courtroom in a much more efficient manner than most lawyers. [4]
While predictive data analysis, machine learning algorithms, and artificial learning have proven to be highly beneficial within the legal realm, many ethical and legal challenges should be considered. To begin, algorithmic bias has been known to unintentionally discriminate against minority groups. Algorithmic bias occurs when an algorithm systematically intercepts data in a way that produces unintentional discriminatory results. For instance, a study by ProPublica revealed that the COMPAS algorithm, used in criminal sentencing, disproportionately assigned higher risk scores to Black defendants compared to white defendants, leading to potential disparities in sentencing and bail decisions. [5] These results can impact sentencing times, bond amounts, and other factors of a defendant's freedom. [6] Another legal concern that should be considered is the loss of privacy as AI is integrated into law. Specifically, laws such as the General Data Protection Regulation and the California Consumer Privacy Act were developed to protect individuals' rights regarding their data. [7] However, a drawback of this could be that it is an ineffective algorithm that doesn't have the full scope of the legal case.
As far as the future of AI in the courtroom is concerned, my view is that the technology can be utilized, but with care and great caution. AI has the potential to offer immense value to legal processes by making them more efficient and reducing the impact of humans. These impacts include bias and time spent digging through history and countless. This is not only making justice more accessible but also providing individuals with the chance to work on other areas of law that require human behavior and interaction. However, as was previously mentioned, there are numerous risks that also need to be considered and, if not addressed, can be extremely detrimental. As AI possesses no true human judgment and moral reasoning, its contextual knowledge of anything outside data points is rather poor, leading to unjust decisions and reinforcing wicked prejudices. Nevertheless, if society maintains guidelines under which humans monitor what AI determines and provide the social and behavioral aspects AI lacks, then this technology will prove more helpful than harmful. While AI can be a useful tool in the courtroom, it must be used judiciously and to augment human decision-making, not replace it.
Artificial Intelligence has revolutionized the way hundreds of career fields operate and has had a profound positive effect on the legal realm. However, it is imperative to understand that while AI in the courtroom can be highly beneficial, the balance between data privacy and algorithm efficacy is extremely delicate. Such algorithms should not be used as the sole determinant of legal outcomes. Instead, AI should function as a complementary tool, enhancing legal research, streamlining case management, and providing data-driven insights while leaving final decisions in the hands of human professionals. By maintaining this balance, lawyers and legal professionals can harness the technology to advance the field in its mission of achieving justice for every individual, ensuring that ethical considerations, human judgment, and legal precedent remain at the forefront of the judicial process.
Edited by Ava Betanco-Born
Endnotes
[1] Rosenblum Law, “AI in Court Systems: Nevada Courts Are Utilizing AI,” Rosenblum Law, 2024, https://www.rosenblumlawlv.com/ai-law/#:~:text=AI%20in%20Court%20Systems:%20Nevada%20courts%20are,dates%2C%20and%20even%20manage%20evidence%20more%20efficiently[2] American Bar Association, “Using AI for Predictive Analytics in Litigation,” ABA, October 2024, https://www.americanbar.org/groups/senior_lawyers/resources/voice-of-experience/2024-october/using-ai-for-predictive-analytics-in-litigation/#:~:text=Predictive%20analytics%20involves%20using%20AI,by%20identifying%20patterns%20and%20trends.
[3] Harvard Law School, “Harvard Law Expert Explains How AI May Transform the Legal Profession in 2024,” Harvard Law Today, 2024, https://hls.harvard.edu/today/harvard-law-expert-explains-how-ai-may-transform-the-legal-profession-in-2024/.
[4] Thomson Reuters, “Five Common Legal Questions That Predictive Data Analytics Can Help Answer,” Thomson Reuters, 2024, https://legal.thomsonreuters.com/en/insights/articles/five-common-legal-questions-that-predictive-data-analytics-can-help-answer.
[5] ProPublica, “Machine Bias: Risk Assessments in Criminal Sentencing,” ProPublica, May 2016, https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing.
[6] Congressional Black Caucus Foundation, “The Unintended Consequences of Algorithmic Bias,” CBCF, April 2022, https://www.cbcfinc.org/wp-content/uploads/2022/04/2022_CBCF_CPAR_TheUnintendedConsequencesofAlgorithmicBias_Final.pdf.
[7] DigitalOcean, “AI and Privacy,” DigitalOcean, 2024,https://www.digitalocean.com/resources/articles/ai-and-privacy.