“Technology will be the main driver of this change. And, in the long run, we will neither need nor want professionals to work in the way that they did in the twentieth century and before.” Richard Susskind
The earliest work on Artificial intelligence which one can recall is the development of Turing test by the British logician and computer scientist Alan Turing. The term Artificial Intelligence was coined later after his death in 1956 by John McCarthy an American computer scientist. Since then the artificial intelligence research and its applications have seen many lows and highs. The term AI winter is used to denote the period in which it was even difficult to get funds for AI Research.
With the advent of 1980, the research and development in the related fields once again revived the interest of the market towards the AI – related research. The period of late 1990s to early 20th century witnessed the usage of AI in data mining, logistics and computer gaming and other related services because of its computational powers. And in recent past, AI has evolved as one of the most disruptive technology of the present times. Reason being its applicability to the number of industries be it healthcare, accounting, trade etc.
In 2018 the valuation of the global legal service market was marked at the US $ 794.50 Billion and the same is expected to grow at the CAGR of 4.1% from 2019 to 2025. At the same time the Indian legal services market was valued around the US $ 1.3 Billion in 2017. India, being one of the fastest growing economies with the second largest population in the world, has a significant stake in the AI revolution. Realizing the need of the hour, during the budget speech for 2018 – 2019, the then finance minister proposed the establishment of a National Program on AI, with a view to guiding the research and development in new and emerging technologies.
Understanding Artificial Intelligence
Artificial Intelligence (AI) is “a broad set of methods, algorithms, and technologies that make software ‘smart’ in a way that may seem humanlike to an outside observer” (Noyes 2016). To simply put AI is a branch of computer science which focuses upon building machines to learn from experience and to perform human-like tasks. AI generally can be classified into two categories first is the Narrow AI and second is Artificial General Intelligence. Amazon Alexa and IBM’s Ross fall into the category of Narrow AI as there task is limited. Whereas AGI is identified as strong AI. AGI is a machine with general intelligence and, much like a human being; it can apply that intelligence to solve any problem. AGI for the fact is a hypothesis only and exists in theory.
The term AI describes a set of different technologies for example Machine learning, deep learning and Natural language process (NLP) etc. Machine learning denotes the ability of computers to automatically learn and to improve themselves from experience. Natural Language Processing (NLP) is the capability of computers to understand the meaning of spoken or written human speech and to apply and integrate that understanding to perform human-like analysis. The machine learning and NLP have shown their potential to be used in legal practice as both of these applications are much conducive with the legal practice. As machine learning involves the data analysis, reading out the existing data and the same exercise is undertaken by the legal practitioners. They lookout for the existing legal precedents and application of those precedents to the present factual situation
Application of AI in Practice
A recent ABA Journal cover story explained, “Artificial intelligence is changing the way lawyers think, the way they do business and the way they interact with clients. Artificial intelligence is more than legal technology. It is the next great hope that will revolutionize the legal profession.” Further, The American Bar Association under its model rules of professional conduct now requires that lawyers shall be competent and that they must keep abreast of changes in the law and its practice, including the benefits and risks associated with the relevant technology. In January of 2017, the state of Florida became the first state to require technology training as part of its continuing legal education requirement.
Indian law firms have also started their voyage on the possible applications of AI to enhance their practices. For example, Cyril Amarachand Mangaldas, one of India’s leading law firms has already collaborated with start-ups to adopt AI based solutions.
Technologies currently in use
AI based technologies are already in use worldwide for example; Technologyassisted review (TAR) is the first major application of AI in legal practice, it is used for organizing, analysing and search large data sets for e discovery or record investigations.
Other examples are Lex Machina, which is owned by LexisNexis, it uses legal analytics to predict trends and outcomes in intellectual property litigation. Ravel Law, also uses legal analytics of judicial opinions to predict how specific judge may rules in a case, including providing recommendations on specific precedents and language that may appeal to a given judge.
USA based law firm Baker Hostetler has already employed the world’s first AI lawyer “Ross” which was developed by IBM and runs on the NLP provided by IBM Watson. Casetext’s CARA claims to allow lawyers to forecast an opposing counsel’s arguments by finding opinions that were earlier used by lawyers. Thus these AI run software’s have already been acknowledged as the tools for enhancing efficiency and speeding up the work at law offices.
Application of AI in the Judicial System
AI has presented itself as an efficient tool for legal practice. It implementation and usage in the judicial system can also be pondered upon. Various judicial systems have already implemented the usage of AI with the development of litigation systems as a tool for their justice system reform. Shanghai intelligent assistive case-handling system for criminal cases” (aka “the 206 System 3.0”) has been developed by the Shanghai High People’s Court and is being in use since December 2018.
The system enables the complete case-handling procedures of criminal cases in Shanghai to be dealt with online from case filing, investigation, approval for arrest, review, prosecution, court trial, conviction, to commutation and parole, representing a breakthrough in the deep application of AI technology in the judicial field.
The System creates the evidence standard as well as a guide to evidence rules for case-handling personnel to follow in the process of evidence collecting and fixing in a uniform manner. Both the criminal procedure theory system and criminal evidence system are claimed to be improved and making historic contributions to the judicial reform in China.
Similarly, the Wisconsin Supreme Court recently upheld the use of algorithms in criminal sentencing decisions. While such algorithms represent an early use of primitive AI (some may not consider such algorithms AI at all), they open the door to use more sophisticated AI systems in the sentencing process in the future. A number of online dispute resolution tools have or are being developed to completely circumvent the judicial process.
As on 1st July 2020, 60444 matters are pending before the Hon’ble Supreme Court of India. 4.4 M before the various High courts and 33.8 M are pending before the district courts all over India. Pendency of cases has been a problem for Indian judiciary from a long time. Various reasons were identified for this, one of the major ones was the insufficiency of staff at the court. The development of these kinds of AI systems might help the Indian courts in case management and early redressal of the issues related to filling of case, collection of evidence and investigations etc.
Challenges and Opportunities
There is reluctance on part of Indian lawyers as to the usage of AI or even technologies. These barriers can be overcome by including technological training to the law students at the University itself. There is an emergent need for reskilling the existing and future workforce. This could be done by the adoption of a decentralised teaching procedure working in collaboration with the private sector.
For example Melbourne law school has started an innovative clinical course for its law students. The course requires students to design, build and release a live legal expert system that can provide legal information to people. For training purposes, the university has collaborated with organisations. Students visit organisations to gain understanding and knowledge related to the relevant needs. This course offers students to explore the potential applications of AI in legal field. It also enables students to develop their skills in legal analysis, problem solving and innovation. India can make use of these transformative technologies to ensure social and inclusive growth but that would require the government to play a leading role in developing the roadmap for AI implementation in the country.
Conclusion
AI is here and it will stay, the whole world is embracing AI and becoming technology savvy day by day, there is no reason why Indian legal system shall lag behind. This metamorphosis of the legal domain, and consequently of the legal profession will indeed prove to be profitable for the society in general and help close the gap of access to justice for the civilians. The legal field, as well as the legal professionals, should come forward and welcome the advent of technology in the legal arena and assist to develop itself for the betterment and welfare of society.
Gaurav Goswami is Assistant Professor, School of Law, University of Petroleum & Energy Studies.