Artificial intelligence (AI) has made inroads into almost every sphere of life today. This has led to a paradigm shift in several fields, requiring the reinvention of their operational and business models. Defined as “the science and engineering of making intelligent machines” that employ “cognitive computing” (enabling computers to learn, reason, perceive, infer, communicate, and make decisions as humans do), AI encompasses many branches such as machine learning (ML). ) including deep learning and predictive analytics and natural language processing (NLP).
While AI has had a transformative impact on all sectors and professions, its potential for use in the legal profession has not been adequately explored. The legal services market remains deeply under-digitized, tied to tradition and slow to adopt new technologies and tools. But the future holds extensive use for the application of AI in the judicial domain, thanks to rapid technological progress and computational power that grows at an exponential speed.
Law depends on a system of formal logic based on truisms drawn from precedents, applying this learning to the case at hand and drawing a corresponding inference. This logic-driven approach makes law inherently conducive to the application of machine intelligence.
Moore's Law predicts that the growth in computing power will double approximately every two years, while the cost of computing power will drop considerably. This provides the basis for rapidly increasing AI capabilities and availability. AI processes greatly help lawyers find smart and unique ways of working. They can be effectively applied to many problems that seem difficult for lawyers to solve, either due to the complexity or volume involved in legal practice.
AI in legal informatics
AI is often employed in modeling legal ontologies. It occupies an important place in legal informatics, which applies information technologies in the context of the legal environment. AI tools and techniques developed in the context of legal problems address the need to store and retrieve large amounts of textual data, resulting in the retrieval of conceptual information and intelligent databases.
The application of technological tools such as ML (including deep learning and predictive analytics) and NLP to law covers a wide range of areas including –
- Formal models of legal reasoning
- Computational models of argumentation, decision making and evidentiary reasoning
- Legal reasoning in multi-agent systems
- Executable Models of Legislation
- Automatic classification and summarization of legal texts;
- Automated extraction of information from databases and legal texts
- ML and Data Mining for eDiscovery and Other Legal Applications
- Retrieval of conceptual or model-based legal information
- Lawbots to automate smaller, repetitive legal tasks
- Litigation risk assessment, pricing, and timeline predictions using ML and AI.
Due diligence
Thanks to AI and ML applications, law firms can generate due diligence reports almost automatically, resulting in considerable savings in time and money.
Due diligence can be handled effectively by technology as most of it is very mechanical work that can be done by feeding a set of parameters and documents, after which a reasonably good NLP is able to discover and dissect the data. AI replaces “menial” legal tasks such as reviewing contracts for favorable or unfavorable clauses that can be more easily performed by a system. Additionally, it can review documents, especially when seeking a high level of integrity and confidence in the quality of document review as part of due diligence.
Legal research
Legal research is another area where AI is useful. Today, a judge's considerable time is spent analyzing the case and similar cases that have occurred, calculating the exact amount of damages and the sentences that have been handed down in the past. However, with AI tools, he can quickly find a precedent, make comprehensive analysis and comparisons with the option of a probable judgment which makes his work much easier. AI applications can also help you hand down consistent sentences that reduce human bias, for example, by ruling out different prison sentences for two defendants in similar situations. He can find the most appropriate cases or statutes that can be applied in a specific legal situation. Attempts to create algorithmic models to predict case outcomes are also underway.
ML can lead to a kind of grand pattern recognition, where a lot of hard data and numbers are potentially available. The goal is to reduce user research time and make it more exhaustive and intelligent.
Thanks to the advent of AI tools, legal research is no longer a manual process, as law students and legal associates no longer need to sift through physical volumes of case law to find a relevant precedent.
Document review
Smarter document management solutions can automatically classify, categorize, connect and help you find documents stored on a law firm or company's servers. After lawyers manually analyze and categorize a sample of 1% of documents, the computer, based on this learning, identifies the relevance of the remaining 99% of documents to the case. AI comes armed with the ability to automate this time-consuming process as it can spontaneously ingest the entire contract, analyze it using NLP technology, and determine the acceptable and problematic parts.
AI-based contract review services go a long way in helping legal teams offload the routine aspects of document review and markup so they can focus on higher-value work. AI can make contract review more accurate, allow lawyers to take a more data-driven approach to the practice of law, and make the legal space in general more efficient.
In cases where pre-litigation discovery or disclosure is crucial, “predictive coding” is a great help. This coding is beginning to be used in transactional law, where it is being used to improve document review in mergers and acquisitions (M&A). It leverages small samples to cross-reference similar items, eliminate less relevant documents, allowing lawyers to focus on highly critical, vital documents. Coding produces statistically validated results that are equal to or greater than accuracy and, importantly, human review rate.
Therefore, there is no need for lawyers to manually review, edit and proofread contract documents that are hundreds of pages long. XML encoding is also used in transaction contracts and in increasingly advanced document preparation systems.
Benefits of using AI in the legal field
AI is a significant step towards enabling even a layman to use the right keywords for good research of technical legal questions. This research provides direct answers to complex legal questions. While, of course, it goes beyond ML model-based research, interpreting a judge's observations is the job of a legal professional.
A good lawyer can figure out whether a paragraph in a ruling constitutes good law or binding precedent, or whether another ruling overruled it. Based on this, the BC could help identify similar paragraphs and parameters in other judgments.
The legal profession is faced with a variety of notable problems that AI can solve. Legal practice requires an immense time commitment with tight deadlines. Long work hours are scientifically one of the most significant contributors to poor mental health among lawyers. AI uses a much broader knowledge base and can review millions of documents that a sharp human eye might miss.
The technology developed by companies in the legal-technology sector helps lawyers quickly identify contractual clauses, making repetitive and monotonous work much more efficient and faster. AI automates several high-volume, recurring tasks, such as finding terms in a set of documents or filling out certain forms that would otherwise divert lawyers' focus from more meaningful work.
AI generates more work in less time, allowing companies to increase their productivity. When the AI finishes its processing, the lawyer can quickly review the work and present it to the client in an accessible way. AI nuances the work of a lawyer who can focus on argumentation, presentation and client negotiations rather than boring, mundane work. The AI also calculates the probability of success of the argument. This allows the lawyer to present the most relevant information in court.
Could technology make legal interns or associates redundant?
If the fear of losing relevance keeps legal professionals away from embracing technology, they will only miss being part of the legal revolution happening around the world. They do not need to be threatened by technology as it will not cause job displacement. AI will never be able to replace lawyers and the legal profession will never stop requiring human capital. What AI technology does is free up time for legal professionals so they can dedicate more of their knowledge and intellectual capacity to carrying out more difficult and challenging parts of their work. Expands the task of lawyers from a limited role in risk mitigation to greater involvement in strategic initiatives, freeing up their bandwidth to focus on different and more complex or valuable types of work
AI acts as an enabler to create smarter lawyers and effectively deal with issues such as legal fees and pending issues. What's crucial is the human-machine interaction: lawyers can pitch their pitch first, for example by identifying clauses in pre-existing agreements, so that the AI can identify similar ones in the future, and cases can first be manually categorized under various headings, with algorithms then derived from these databases.
India is yet to fully embrace AI in the legal field
While companies globally are increasingly opting to adopt AI in legal departments, currently, law firms in India use limited analytics and artificial intelligence. Implementing AI in the Indian judicial system is a human and technological challenge.
Few judges are tech-savvy, although most of them profess an interest in reducing overall backlog levels. This is why there has not yet been much innovation in India in legal technology and AI compared to abroad. Companies need to make sufficient investments in R&D in developing AI in the Indian legal space. In the US, there are many large companies on the software side, targeting legal as a potential market. Unfortunately, the corporate legal market is still very small in India, and there are not many corporate lawyers worth their salt. Corporate legal departments, in general, still need to optimize legal IT to manage patent portfolios and for document preparation, customization and management.
There is a pressing need to resolve the problem of India's vast amount of non-digital business documentation so that a legally binding contract can be signed and stamp duty paid electronically on digital contracts. AI can speed up the process of digitizing most of a company's documentation. But before that, companies have to embark on the document digitization process.
More and more IITians need to start taking a serious interest in law and start applying their software knowledge to the legal domain. The judiciary also needs to make the entire process of court records, writ petitions, pleadings, court judgments and orders available online in all judicial establishments across India.
From now on
Technology is poised to transform the legal sector in the future. It is estimated that within a few years we will be able to see better implementation of e-learning software and databases and the automation of legal services, from compliance to the automatic creation of contracts and terms of commitments. These tools can automatically generate large portions of term sheets for potential investments that are automatically turned into checklists to generate standard subscription agreements with the click of a button.
AI can also make legal assistance more accessible. Small businesses can save expensive legal advisor fees for compliance advice thanks to ML. Some start-ups in the legal sector have started offering automatic compliance technologies, where a series of simple questions answered by a company are used to produce compliance checklists and more on all aspects of Indian legislation, be it the Companies Act or the GST Act. Its ML products can predict and further guide SMBs on the types of compliance requirements that would arise in the future if they were in a specific line of business.
AI can potentially make sense of documents and records stuck in bad PDFs in vernacular languages through optical character recognition (OCR). Thanks to sophisticated OCR and advanced language services being developed by companies like Google, digitizing old documents will soon be a reality.
We can expect substantial progress in the coming years with computers capable of imitating intelligent legal reasoning. Lawyers, in turn, need to have an increasing number of skills to make use of technology to remain competitive in the market.
The increased use of AI in the legal space will also lead to the need for more data analysts who can explore legal and business data sets and generate actionable insights to improve legal practice. Law firms will create their engineering departments and product teams.
AI would continue to expand its reach in the coming decades, impacting and expanding the practice of law. It could acquire the ability to generate agreements, mark and negotiate a document, and manage and do appropriate filings automatically.
In the coming years, we will be on the cusp of a revolution in the practice of law led by the adoption of AI that will become ubiquitous – an indispensable assistant for virtually every lawyer who would extract pertinent information by typing a query directly or typing a query. asking the machine to perform a task.
AI is poised to power machines beyond simple keyword search tools, and lawyers can team up with machines to provide better, faster, and cheaper legal services to their clients.
The downside of AI
AI is not 100% accurate; this is partly due to hindsight bias and partly due to limited emotional and social awareness. The AI bot's algorithmic method of processing information cannot take into account the political, moral, or social ramifications of the issue at stake. You cannot, for example, afford to provide any insight into emotive issues such as child custody in a divorce case.
The other impediment is that legal work is less numerical and more linguistic. Therefore, it is very unlikely that ML applications, although they can find patterns even in random data, will understand the actual meaning of words and nuances of language, a task best left to legal eagles.
AI cannot think creatively about all angles of a problem. But an interaction between AI and humans can accomplish more than humans or machines can do on their own.
In short
AI tools help improve efficiency as legal algorithms speed up document processing while detecting errors and other issues. But the role of AI is not limited to eliminating manual (or boring) tasks. The technology-driven law firm can automate the vast majority of its services with NLP and AI tools. They can scale their services with automation, charge low fees, while companies that do not have automatic processes may find themselves relatively overpriced for legal services.
However, AI may be better used as a research tool than as an adjudication tool, as it cannot understand issues of serious social dynamics. You cannot dispense with the need for lawyers. It is beyond imagination that AI will ever make legal acumen and experience obsolete. Still, it may well help lawyers both quantitatively and qualitatively – detecting patterns and correlations between case studies that human eyes might miss.
So the question is not whether AI can replace lawyers, but to what extent it impacts the way a lawyer works. Ultimately, the role of lawyers remains vital in dealing with the complexities of legal work with their unique expertise. But thanks to technology, lawyers are more productive, allowing them to represent more legal matters with greater efficiency and a greater degree of accuracy.