Faculty Seminar | Presentations by Sidharth Chauhan and Dr. Rahul Hemrajani

There will be two presentations by NLS Faculty in this week’s seminar by Sidharth Chauhan and Dr. Rahul Hemrajani.

Presentation 1

Title: “Juridical Engagement with Electoral Reservations in India” by Sidharth Chauhan.

Abstract

The Constitution of India enables reservations for historically marginalized groups designated as Scheduled Castes (SCs) and Scheduled Tribes (STs) in three domains of public life, namely in admissions to higher education institutions, recruitment to public sector jobs and the directly elected chambers of the Union Parliament as well as the State Legislatures. In the context of higher education and public employment, the ambit of reservation policies has been progressively extended to intermediate castes designated as ‘Other Backward Classes’ (OBCs), initially through laws made by State Governments and subsequently through laws made by the Central Government. Significant constitutional amendments enacted in 1993 obligated the State Governments to provide gender-based quotas in local elected bodies such as ‘Panchayats’ (Village Councils) and Municipal Corporations. There are also some other distinctive examples of electoral apportionment such as the provision for nomination of two Lok Sabha members from the Anglo-Indian Community (discontinued after 2020), the nomination of twelve Rajya Sabha members from different fields of work and a seat reserved for a religious group in the Sikkim Legislative Assembly. When compared with reservation policies in the domains of higher education and public employment, quotas in elected bodies have not attracted a similar degree of scrutiny, be it in judicial decisions or in doctrinal legal scholarship. The aim of this dissertation is to draw attention to the patterns of juridical engagement with electoral reservations in the post-independence period. The hypothesis is that so far the courts have not sufficiently explored or articulated the distinctive justifications that can be mustered in support of electoral reservations. Instead, they have frequently conflated their presumptive justifications with arguments that are better suited for defending distributive measures in other spheres of public life. This dissertation argues that these special provisions for enabling the political representation of historically marginalised communities should not be narrowly viewed as methods for redistributing material resources. This leads us to the conceptual mistake of concentrating on the performance of representatives elected through reserved seats in the short-run and diverts attention away from their normative purpose. We should look at these provisions through a constructive interpretation of phrases such as ‘equality of status and opportunity’ and ‘fraternity’ which appear in the Preamble to the Constitution of India. Such a moral reading better reflects notions of collective responsibility that are needed to address historically entrenched forms of inequality. To develop this argument, this dissertation concentrates on a chosen set of judicial decisions that have touched on arguments for and against the continuance of electoral reservations at different levels of government. After examining these decisions, it demonstrates how future adjudication in this area can benefit from a serious engagement with the scholarly literature that advances the analytical understanding of ‘political equality’. With respect to explanations for democratic authority, the key idea is that electoral quotas incrementally contribute to ‘recognitional legitimacy’, a concept that transcends the immediate pursuit of political integration and the pragmatic accommodation of group differences.

Presentation 2

Title: “Evaluating the Role of Large Language Models in Legal Practice in India: Performance, Challenges, and Practical Guidelines” by Dr. Rahul Hemrajani.

Abstract

The integration of Artificial Intelligence (AI) into the legal profession raises significant questions about the capacity of Large Language Models (LLMs) to perform key legal tasks. In this paper, we empirically evaluate how well LLMs, such as GPT-4, Claude, and ChatGPT, perform key legal tasks in the Indian context, including issue spotting, legal drafting, advice, research, and reasoning. Through a survey experiment, we compare outputs from LLMs with those of a junior lawyer, with advanced law students rating the work on helpfulness, accuracy, and comprehensiveness. LLMs excel in drafting and issue spotting, often matching or surpassing human work. However, they struggle with specialised legal research, frequently generating hallucinations—factually incorrect or fabricated outputs. We also highlight differences in AI model performance and provide practical guidelines for crafting effective prompts for legal tasks, with examples. We conclude that while LLMs can augment certain legal tasks, human expertise remains essential for nuanced reasoning and the precise application of law.