AI in legal profession: Threat or tool for Justice

Author: Anushka, NMIMS Navi Mumbai

Artificial Intelligence (AI) is revolutionizing businesses all over the world, and the legal profession is no exception. AI refers to the creation of computer programs that can accomplish tasks demanding human intellect, e.g., learning, reasoning, problem-solving, and decision-making. In the legal industry, AI is being utilized more and more for legal research, contract review, litigation forecasting, and even judicial decision-making.

The implementation of AI in the practice of law has ignited a broad discussion. On the one hand, AI vows to improve efficiency, make justice more accessible, lower costs, and deliver more predictable legal results. On the other side, it raises serious ethical and legal issues such as bias, transparency, accountability, and the risk of replacing human lawyers and judges. This article examines the use of AI in the legal profession and discusses if it is a threat to the fundamental values of justice or if it is a useful tool to enhance the legal system.

AI comprises a broad range of technology which includes machine learning, natural language processing (NLP), neural networks and expert systems which makes it unique and enables it to perform human tasks. 

Machine Learning - This system helps AI to improve its performance through experience and data analysis without being explicitly programmed.

Natural Language Processing - This system in AI analyses and understands human language which enables them to interpret legal documents and arguments.

Neural Networks- AI imitates human brain function to recognise patterns and improve decision-making.

Expert System - This is the system which is designed to provide expert ₹level advice and analysis in specialised domains like law.

The use of AI technology in the legal field can be categorized into the following types:

1. Legal Research and Analysis

Lawyers now have IT-powered services, like Westlaw, LexisNexis, ROSS Intelligence, which make the process of legal research much easier.

AI systems make it possible to extract relevant arguments or case law by analyzing a variety of databases containing statutes, case laws, and legal commentary. 

2. Contract Review and Drafting

Kira Systems and Luminance are two examples of AI tools which review contracts, extract important languages, and try to reduce the risks by suggesting different languages.

Consistency and pattern recognition in contracts with the help of machine learning algorithms greatly enhances the accuracy of contract drafting while also reducing the time to perform the tasks. 

3. Litigation Prediction

AI tools predict the outcome of court litigations based on previous rulings and case laws.

Premonition and Lex Machina are tools that give an understanding of specific judges’ tendencies, assisting lawyers to form more efficient litigating aids. 

4. E-Discovery

AI makes it possible to review and scan numerous records, documents, files, and emails within a fraction of the time human reviewers would require to locate helpful evidence for court cases.

AI helps in selecting the crucial documents with the aid of machine learning and predictive coding more quickly, accurately, and efficiently than human reviewers. 

5. Automated Legal Aid Services

AI Chatbots and virtual legal assistants offer primary legal guidance and prepare legal documents for a client. 

Websites like DoNotPay provide AI assistance regarding consumer rights and other legal matters.  

6. Judicial Decision AI applications

AI is being implemented for use in judicial processes involving decision making, such as sentencing or bail out decisions. 

AI in Estonia is used in the resolution of small claims cases and other minor cases of legal disputes.

A. Improved Efficiency and Lower Costs

AI performs time-consuming and mundane tasks like legal research, document review, and contract analysis, leading to a substantial saving of time and cost in legal work. 

1.Lower Billable Hours

-AI allows law firms to provide fixed-fee or subscription-based billing, keeping legal services within a client's means.

-Automating routine work enables lawyers to concentrate on nuanced legal strategy and client contact.

2.Affordable Legal Services

-Small and medium-sized law firms have access to advanced legal analysis and research tools, making the playing field equal with large firms.

-Clients receive reduced legal expenses and quicker resolution of cases.

1. Legal Research and Case Analysis Old-style legal research is time-consuming and time-consuming. Al-based legal research software enhances this procedure substantially by processing extensive databases of case law, legislation, regulation, and legal comment. • ROSS Intelligence - ROSS is an Al-driven legal research platform that employs NLP to enable attorneys to pose legal questions and obtain answers complete with pertinent case law and legal analysis. • Westlaw and LexisNexis - These tools utilize Al to deliver more precise search results, recognize leading legal arguments, and indicate pertinent precedents. • Example: A law firm in New York employed ROSS to manage a large-volume antitrust case. ROSS determined case law and legal precedent in a matter of minutes compared to what human attorneys would have spent, lowering research expenses by 30%.

2. Contract Review and Drafting Al-based contract review platforms are able to review and draft contracts quicker and more precisely than human attorneys. • Kira Systems - Kira applies machine learning to review contracts, flag risks, and recommend alternative provisions. • Luminance - Luminance analyzes and classifies contracts for inconsistencies and incomplete terms. • Illustration: Global law firm Clifford Chance employed Kira Systems to analyze more than 1,000 contracts within a merger transaction, cutting the time it takes to review contracts from weeks to days.

B. Enhancing Access to Justice

AI can democratize access to legal services by making legal advice accessible and affordable.

1.AI-Powered Legal Aid for Disadvantaged Communities

-Chatbots powered by AI offer free legal aid to those who are unable to afford a lawyer.

-Services such as DoNotPay assist consumers in battling traffic tickets, negotiating refunds, and knowing their rights. DoNotPlay helped users overturn 160,000 parking tickets in the UK, saving clients millions of dollars.

2.Automated Document Drafting

-Artificial intelligence programs aid in the drafting of wills, contracts, and legal notices cheaper than going to the lawyer.

-Inexpensive legal services close the gap of justice and enable people to assert their legal rights.

 Online Dispute Resolution (ODR)

 AI assists with online dispute resolution through the examination of evidence and suggesting settlements.

 Modria – An AI-powered platform utilized by eBay and PayPal to settle consumer disputes.

Example: Modria settled more than 60 million eBay and PayPal disputes, minimizing the necessity of human intervention and enhancing customer satisfaction levels.

C. Improved Accuracy and Consistency

Artificial intelligence systems minimize human bias and error through objective analysis of legal data and consistent application of legal precepts.

1.Data-Driven Decision-Making

-Artificial intelligence finds patterns and precedents better than lawyers.

-Predictive models enable lawyers to forecast case outcomes and adapt legal tactics accordingly.

Lex Machina is an artificial intelligence driven platform which analyses legal documents, court decisions and litigation outcomes to predict future case outcomes. A US based law firm used this platform to predict the chances of success in a patent case which helped them improve their litigation strategy.

2.Consistency in Judicial Ruling

-Artificial intelligence can examine previous judgments and suggest uniform sentences and bail orders.

-Artificial intelligence minimizes judicial bias and enhances the fairness of the judicial system.

 AI enhances the accuracy and predictability of legal decisions through data analysis and pattern recognition from previous cases.

Litigation Strategy through Predictive Analytics:AI has the ability to forecast litigation outcomes and suggest approaches based on historical decisions and court behavior.

 Lex Machina – Lex Machina analyses court opinions, judge orders, and case results to make predictions on the outcome of a case.

Example: A US law firm utilized Lex Machina to determine the probability of success in a patent case, enhancing their litigation plan and achieving a favorable settlement.

D. Speeding up and Making the Litigation More Efficient

AI accelerates discovery and the litigation process through swift and precise review of huge data volumes.

 1.Improved Discovery Process

-AI recognizes crucial evidence more accurately and at a faster rate compared to human examinees.

-Reduced cost and time spent reviewing documents

As always, AI finds relevant information in enormous datasets and simplifies the discovery process.Relativity - Like most companies, Relativity applies AI tools to sort, categorize, and audit huge volumes of electronic evidence. Case in point: In a securities fraud matter, a multinational law firm employed Relativity for email document reviews. The firm attempted to reduce document review time from 1.5 million emails to spend 80 percent less time reviewing documents.

 2.Acceleration in the Settlement of Cases

-AI platforms facilitate settlement negotiations as well as alternate dispute resolution.

-AI assists in decongesting courts as well as overall judicial efficiency enhancement.

AI is undergoing application trials in small claims court and administrative law decision making.Estonia's AI Judge - Estonia started using artificial intelligence to settle small claims disputes in order to alleviate high court backlogs and slower resolution times. Example: In its first year, the AI system resolved more than 500 pc of small claims with a success rate better than 90 percent.

A. Loss of Human Intuition and Ethical Dilemmas

AI systems, for the most part, do not possess these important attributes: intuition, moral reasoning, and empathy, which makes the practice of law complex and demanding.

1.Reduced Human Oversight  

-Ethical or moral AI decisions are out of the picture as they rely on statistics and algorithms.

-With so little human oversight in processes, inequitable sentences, unjust bail, and parole decisions become the order of the day.  

Al systems decide based on statistical analysis instead of ethical or moral judgment.Judges and lawyers can rely on Al-based suggestions without thinking them through.

Example: In the COMPAS case of State of Wisconsin v. Loomis, the court embraced Al-based sentencing suggestions in spite of fears over the transparency and bias of the system.

2.Absence of Emotional Intelligence  

-AI legally doesn’t have the capability to grasp the social and emotional aspects of a legal fight.

-A person does not only act at the negotiating table, but also feels and understands, therefore, AI cannot argue and negotiate well enough.  

B. Bias and Discrimination  

An AI remains only as unbiased as the training data, If the training data was historically biased, the AI will exacerbate and reinforce bias still further.   

1.Racial and Gender Bias  

-The AI-based predictive policing systems target minorities and women.

-Hiring algorithms, as well as loan approval algorithms, have been found to be gender biased and racially biased, too.  

COMPASS was also discovered to give African-American defendants higher recidivism risk scores. Artificial intelligence recruiting tools have been demonstrated to prefer male candidates to female candidates.

Example: Amazon's Al recruitment system was shelved after it was discovered to discriminate against women applicants.

2.Bias in Judicial Decision-Making  

-Judicial AI sentencing tools tend to suggest more severe sentences to minority defendants than white defendants who committed the same offenses.

-Discrimination bias in the training data violates fairness and equal protection since it represents systemic discrimination.

C. Responsibility and Openness

The procedures involved in making an AI-related decision are usually shrouded in a ‘black box’ that is difficult to scrutinize. Al-based decisions hardly provide transparent insights to show who is accountable for the decision and whether the due process is met.

1. Black Box Challenge

-AI technology is built upon the application of intricate neural network structures and machine learning algorithms, which are complex by nature.

-Not being able to examine the process causes the paradox of missing information that is even less favorable than the lack of information itself.

Al decisions are premised on intricate neural networks that cannot be interpreted.Courts and lawyers do not know exactly how Al systems come to a conclusion.

Example: In State of Wisconsin v. Loomis, the defendant was not able to challenge the COMPASS score because the algorithm's insides were proprietary.

2. Judicial and Legislative Supervision

-Merging the contested human characteristics in the judgments of the AI with rigid anthropocentric systems, courts and parliaments encounter some barriers concerning the ability to govern AI.

-AI developers and technology companies have control of almost all AI solutions and systems, and that raises issues of responsibility.

All developers determine the design and functioning of Al systems, with limited judicial control.Regulatory systems for Al in legal practice are not yet fully developed and still need a stringent regulatory framework.

D. Job Dislocation and Other Effects on Economy

The consequences may include the obsolescence of human labor lawyers in fields such as legal research, document examination, and contract review. 

1.Effects on Junior Lawyers and Paralegals

-The majority of low-skilled positions in the legal field are prone to automation.

-The decreased demand for legal services may result in a corresponding decline in law schools and an oversupply to the profession.

2.Changes in the Methods of Work for Legal Practitioners

-Law firms will be forced to implement developments that aim at integrating artificial intelligence with changes in market models and clients’ demands.

-It is possible that lawyers will have to learn and practice some computer science and artificial intelligence.

AI creates both problems and solutions regarding the legal profession. Efficiency and accessibility to the legal system improves with the introduction of AI, which brings cost reduction to the legal sector. There are also significant ethical and legal complications that arise. Lack of transparency with bias and the degradation of human decision making requires stronger checks and balances in AI-operated legal systems. Courts along with regulators and legal practitioners need to learn how to properly utilize its AI abilities in a way that opens up opportunities in the legal profession while protecting foundational principles such as justice, equality, and humanity. Rather than replacing human rationality, AI should be used to issue better tools to lawyers, empower the legal world, and offer better justice to society.