The Rising Role of Artificial Intelligence in the Legal Industry
In the modern legal landscape, the role of Artificial Intelligence is rapidly rising and becoming increasingly significant. AI algorithms and machine learning technology possess demonstrated potential to transform the justice system by playing an increasingly crucial role in automating routine, high-volume tasks such as automating legal research, document drafting, document review, providing legal advice, and even predicting the outcomes of cases.
With its growing importance in the industry, legal professionals are beginning to invest in AI technology to have a competitive edge. Because, AI algorithms can quickly and accurately collect relevant data, process an enormous quantity of legal documents and cases and analyze it, discover pertinent precedents, and provide insights. So, the justice system can also harness this technology and reap benefits in an array of ways, including boosting effectiveness, efficiency, accuracy, and accessibility, along with bolstering access to justice mechanisms and promoting fairness. Since the potential use cases for artificial intelligence have already been cemented with solid grounds, it appears to be expedient to explore the growing role of AI-driven powerful machines in the legal industry. Let’s dive deeper into this premise.
Predictive Analytics:
As aforesaid, AI algorithms can analyze past judicial decisions, legal precedents, and other relevant data to predict the outcome of a particular case and assess the risk of recidivism among offenders, which can enable judges to make more informed decisions when making bail, sentencing, and parole decisions. Taken for example, in determining appropriate sentences for offenders, predictive algorithms can assist judges by way of analyzing a variety of factors such as the severity of the crime, the nature of the offense, the offender’s criminal history, and other relevant data. Such a practice is also celebrated as predictive justice, where AI-assisted court systems can improve the accuracy of legal judgments, reduce costs, and increase efficiency within the justice system.
Predictive policing practices also encourage police departments to use data and AI algorithms to predict potential criminal hotspots and determine which areas need more police attention, enabling the police to make more informed decisions about how to allocate resources, better respond to potential threats, and make more effective use of their time. Even with concerns and controversy, such proprietary AI tools will play an increasing role in our personal lives and the criminal justice system.
Decisional Support:
Like predictive analytics, Artificial Intelligence can provide judges with additional information and context to help them make more informed decisions in complex cases, such as evaluating and analyzing evidence more efficiently and objectively, as well as understanding the emotional impact of a case on the parties involved by analyzing their statements and behavior in court, which can help judges make more empathetic and fair decisions.
Case Management and Docketing:
AI can assist judges and court clerks with managing their caseloads, organizing relevant documents, and scheduling and prioritizing case hearings based on their importance and urgency. Presently, courts are using AI to handle repetitive, non-value-add processes like auto-docketing and to deliver higher quality, more efficient service to the public. AI can also help judges and the judiciary streamline processes such as scheduling, document management, and case tracking, allowing them to focus on more important tasks.
In Palm Beach County, Florida, AI-empowered software is classifying and docketing court filings with 85% accuracy. Legal case management AI software with docket management includes Clio, CARET Legal, PracticePanther Legal Software, Filevine, CosmoLex, Law Ruler Software, and CASEpeer. C-Track court management software also provides an advanced rules engine, calendaring/scheduling, and docketing. The best-case management software for law firms includes an integrated click-to-call dialer, which is also powered by artificial intelligence. AI also can automate billing processes and will continue to improve legal case management software in the future. Case management software from Sprinklr can automate workflows across 30+ channels to reduce costs, accelerate time-to-resolution, and increase customer satisfaction (CSAT).
Document analysis:
AI can play a significant role in assisting judges in quickly and accurately analyzing large volumes of legal documents, such as contracts or pleadings, to identify relevant information and trends. Document analysis in court with the aid of AI is becoming commonplace. Lawyers can use AI within Document Intelligence to classify, extract information from, and analyze documents in innovative ways. Using AI for document analysis can reduce due diligence document review time by up to 70% while uncovering hidden risks. It also empowers legal teams to make decisions rapidly by prioritizing critical documents.
Technology Assisted Review (hereafter, TAR) is a way of handling the review phase of eDiscovery by deploying algorithms that can classify documents. This AI-powered technology can analyze how documents are coded and predicts the likelihood that a given document is responsive or privileged, and also provide better results than manual review, as it has higher precision rates. The Irish Commercial Court accepted and approved the use of TAR 1.0 in 2015 to assist with discovery in Irish Bank Resolution Corporation Ltd v. Quinn (2015) IEHC 175. In this case, the computer then demonstrated scientifically its accuracy and reliability when making decisions about which documents were responsive or privileged. However, there are still challenges with using TAR 1.0, such as requiring a complex workflow and demonstrating scientific accuracy and reliability when making decisions about which documents are responsive or privileged.
Legal Research:
AI systems can help judges and other legal professionals quickly and accurately search through large volumes of legal data to help them make informed decisions. AI-based legal research software allows legal professionals to quickly scan and search large databases of case law, statutes, regulations, and other sources of information and mine archives of legal precedents to quickly find relevant or supporting documents to bolster a legal argument. It helps lawyers save time by automating routine tasks such as document review, contract analysis, e-discovery, and due diligence.
The available AI systems for legal research include Westlaw Edge by Thomson Reuters, CARA by Casetext, Genie AI, and LexCheck among others. Thomson Reuters’ Westlaw Edge is one of the best AI models in the legal world, having a large and organized legal data set, and a team of dedicated scientists and technology experts specialized in analytics, artificial intelligence, and natural language processing. LexCheck is an AI contract management tool that enables AI to accomplish the review work of a lawyer in negotiating contracts. Casetext’s ‘CARA’ also uses advanced algorithms to analyze briefs and memoranda to find relevant cases that traditional research might miss. As an open-source legal library, ‘Genie AI’ utilizes legal data and generative AI to help users draft legals with confidence.
Automation of Routine Tasks:
By automating routine tasks such as legal workflows, documentation or contract review or predictive coding or case management, etc., legal professionals use AI machines to deliver significant efficiency and cost-saving benefits. Particularly, AI algorithms can be used to automate routine tasks in the courtroom, such as transcribing court proceedings and generating documents, document management, and data entry, freeing up them to focus on more complex tasks that require human expertise. A bunch of legal AI startups includes PracticeLeague Legaltech, Neota Logic, LawPavilion, Luminance Technologies, LEVERTON, Everlaw, Atrium, Kira, Nalanda Technology, LegalSifter, Autto, Cognitiv+, LawGeex, ROSS Intelligence, Intraspexion, Brightflag, Legal Robot, Omni Software Systems, and Pensieve, and IBM’s LegalMation.
Principles and Policies in AI Applications:
A wider recognition exposes associated risks of disruptive technologies like AI algorithms applicable in legal fields. This high-stakes environment mandates respect for some key principles and policies to ensure its responsible use. Objectivity and fairness come at the forefront. In making unbiased and fair decisions, AI systems require to be designed and trained to dispel prejudice and discrimination. AI systems when applied in law should attain accuracy and reliability based on the data and information provided to them. Then comes transparency and explainability which requires AI systems to be understandable, transparent, and accountable in their decision-making processes, with clear explanations and justifications for their actions, which altogether paves the way for judicial accountability.
Individuals’ privacy, security, and confidentiality are valued equally in the light of relevant rules and regulations, and the idea of justice. Other ethical and legal norms and rules are also critical if legal technology is enabled by artificial intelligence. What is more crucial is that humans have authority and oversight over artificially intelligent systems given that they have been developed to augment and support human decision-making as opposed to disrupt or supersede it. As a consequence, appropriate safeguards and governance need to be put in place that preserve the overarching importance of human agency and authority. Continuous development, training, evaluation, and refinement of AI algorithms and machine learning are recommended to accommodate ever-evolving circumstances and ensure accuracy, efficacy, efficiency, and fairness in decision-making.
Concluding Remarks:
Although the vast amount of judicial data combined with AI-driven analytics will provide a deeper understanding of court processes and allow for insights that can help shape the future of justice, voices are already heard for an outright ban on predictive, profiling, and risk assessment AI and automated decision-making systems in law enforcement and criminal justice because they can have devastating consequences for people who are profiled as criminals or considered a risk even though they haven’t actually committed a crime. Accordingly, despite it has numerous potential use cases, this disruptive technology also gives rise to ethical and legal implications, such as disparate impacts like bias, discrimination, inaccuracy, unfairness, and other unintended outcomes. As a result, harnessing the AI promises and potentials in the legal industry will seriously be taken into consideration and determined on a case-by-case basis, with the possible advantages and drawbacks thoroughly weighed to ensure inclusive and equitable uses in given cases.
