Abstract
Industry 5.0 seeks to add smart machines, bots, and algorithms working alongside humans with sustainability goals concerning human, environmental, and social aspects. The legal world is no exception to Industry 5.0. New-age technologies such as artificial intelligence (AI), blockchain, internet of things, and cloud computing are making headway into Law. AI is of particular significance as it disrupts the field in multiple ways. It is worth inquiring whether AI is the new-age lawyer. The present chapter seeks to unpack this question in the Indian context by examining AI applications in Law, the dark side of such applications, human-AI interactions, the challenges, and potential solutions of a paradigm shift from machine learning to deep learning-based AI, the impact on sustainable development goals, and the outlook of the Indian Judiciary towards inclusion of new-age technologies. The chapter concludes by advising a cautious approach to including AI in law.
TopAi Applications In Law
The use of technology in Law is not new. Although not as concentrated and advanced as today, its presence can be noticed from as early as 2000, when Google gained traction to become a famous search engine (Mull, 2023). However, with time, technology has developed multifold, and so has its interaction with Law regarding quantity and quality. In today’s day and age, Artificial Intelligence has much to offer. Modern-day Artificial Intelligence (AI), in addition to offering more generic forms of technology and services, also offers services and technology solutions through Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP). These are more detailed and developed forms of technologies that, by using a large set of data, engage in the previously considered non-routine tasks for machines (Brynjolfsson & McAfee, 2014; Frey & Osborne, 2017). ML is centralized in the theory of recognizing patterns in the data made available as a data set and then acting and predicting according to a set of rules (Schatsky et al., 2015). It enables computers to learn themselves and perform tasks that are not explicitly programmed (Kulkarni & Padmanabham, 2017; Ohanian, 2019). DL is a further enhancement of ML. It is a highly layered structure of neural networks capable of working with unstructured data (Chollet, 2021). Similar to ML, DL, based on large amounts of data that it is trained with, can identify patterns, make predictions, and take action (IBM, n.d.). NLP further modifies the available technology by enabling technology to understand human language, both written and spoken (Gillis et al., 2024). It complements ML technology in understanding and processing large amounts of data by converting human input to numeric vectors, which are then worked upon using ML techniques (Armour & Sako, 2020; Martin, 2009).
Key Terms in this Chapter
Deep Learning: It is a subset of machine learning that utilizes neural networks to simulate the complex human decision-making.
Explainable AI (XAI): It is a set of methods and processes that allows humans to comprehend and trust the output of machine learning algorithms.
Uncanny Valley: It can be defined as people’s negative reaction to certain lifelike robots up to a certain point. When robots start resembling people; people like them but only to a certain point beyond which they feel an eeriness/creepiness about the robots. Then, when this resemblance increases, people again start liking the robots. The dip in likeness is defined as the uncanny valley.
Natural Language Processing: It is a technique that combines rule-based modeling of human language with statistics and machine learning to enable digital devices to recognize, understand, and generate speech and text.
Technochauvinism: The belief people hold that the best solution to any problem is technology and neither changing our habits nor mindset.
Industry 5.0: It refers to smart machines, robots, software/algorithms working along-side humans with sustainability goals included. It seeks to add human, environmental, and social aspects beyond Industry 4.0 technologies.
Machine Learning: It is the branch of AI that focuses on utilizing data and algorithms to imitate human learning, gradually improving its accuracy in the process.