A Study on Methods of Data Collection in Research vis a vis AI in Legal Research: An Ethical Analysis

Legal research is the systematic process of identifying, locating, and analysing legal information such as statutes, case laws, and scholarly writings to resolve a legal issue or develop legal arguments. The role of legal research in the society is massive, as courts rely on it to interpret law and academics use it to critically evaluate the legal systems. For any legal research to be meaningful, data collection becomes very important as the conclusion is bound to be weak if data collection is incomplete or biased. This paper explores the transition from traditional, human-driven methods of data collection—which prioritised accuracy over efficiency—to the advent of artificial intelligence, which is changing the landscape of data collection through automated scanning and algorithmic filtering. While artificial intelligence definitely saves time and offers a wider database, it carries certain dangers, primarily being that AI can misinterpret the law, carry bias from past data, and lacks transparency. The research examines how AI performs data mining and natural language processing to scan thousands of judgements, providing a scale of research that is humungous. However, a contrast is clear: the traditional method was deeper and the reasoning was transparent, whereas in artificial intelligence, the decision is opaque and the reasoning is not clearly explainable. This nondisclosure of the basis of information is against the principle of natural justice. Ethics is the cornerstone of a legal research, denoting fairness, honesty, and responsibility. This paper highlights serious challenges involved in AI-driven research, specifically the risk of prejudice in data. If the past judgements were biased, then artificial intelligence repeats it at scale and perpetuates it to a larger extent. Along with bias, the problem of accuracy and hallucination creates a question mark on the credibility of the legal research. Furthermore, the biggest challenge identified is the impact on academic integrity, as copying AI output challenges the traditional requirement for original thinking and sufficient reasoning. Ultimately, the paper argues that while AI is powerful, there is no sufficient and clear legal control to regulate it. It concludes that a human must be in the loop whereby artificial intelligence assists and human being decides. By regulating AI to withstand the tests of transparency, accountability, and fairness, the quality of legal research can be increased to better help policymakers and the society.