There is an intensive demand in applying Artificial Intelligence in legal research and therefore slowly transforming the legal profession in education and practice. In this changing time of evolution in the field of Artificial Intelligence, its interface with the legal education system is a big debate. Few believe that bringing the efficient option of AI will not just boost up the quality of the legal education but also helps in maintaining proper data storage of the law student development by continually tracking and examining with Artificial Intelligence. However, opposing to such argument, few find it not so effective methodology legal fraternity should opt for.
One of the recent developments in this area is in regards to placing Law Professors/Faculty with AI. This idea brings mixed reactions amongst different stakeholders of legal education. The most common stand taken was in regards to the very nature and purpose of education itself. It argues that the law schools will always be about learning from experienced Advocates and Law Faculties. To think like Law-experts, with all the imagination and appropriate practical examples, empathy and versatility to suit individual law student by AI is hard to imagine and create. Technologies cannot substitute the expertise and experience of the human being as a professor.
On the other hand, many law professors are heard complaining about law schools, converting them into clerks with tons and tons of paperwork. Bringing Artificial Intelligence has lots of favourable results in the sense of bringing synchronised data-keeping, record-holding which help to derive more accurate data from evaluating the growth of law students. Also, to impart various technical dimensions of law will not just help the law students to learn more and more but it shall also act as a means to connect traditional knowledge system with upcoming requirements of the legal field for students and as well as for professionals. For Instance, in case of reviewing documents, Artificial Intelligence can review a particular document and tag the same if it is relevant to the case. Once the document is tagged and seems relevant then machine learning algorithms can get to work to find other documents that are similarly relevant. This mechanism will reduce the load of work from students as well as professionals.
As the cliché goes: every coin has two sides. In the case of AI and Legal Education, firstly, it needs to be ensured that students are psychologically adaptive to this new approach where they should feel comfortable and mentally connected to this new system of learning. Secondly, there should be some specific boundaries or principles needs to be formulated to bring out the best result out of this process. The purpose is to prepare law students to be “future-ready” advocates. However, there is still no common understanding or philosophy in this regard. Nevertheless, a broad range of ideas is taking root, somewhat experimentally, across the law school community.