Artificial Intelligence And Big Data In Insurance: Legal And Ethical Challenges
- IJLLR Journal
- May 30
- 1 min read
Dr. Kabir Ahmed, Associate Professor, USLR, University of Science & Technology Meghalaya
ABSTRACT
The integration of Artificial Intelligence (AI) and Big Data analytics into the insurance sector has heralded a transformative era in risk assessment, underwriting, and claims management. While these technologies promise unprecedented efficiency, accuracy, and personalization, they simultaneously introduce complex legal and ethical challenges. This paper critically examines the implications of algorithmic opacity, data-driven discrimination, and privacy intrusions that accompany AI deployment in insurance practices. Drawing on contemporary case studies—from wearable- based underwriting models to algorithmic claims denials—it highlights the risks of bias, exclusion, and non-transparent decision-making inherent in AI systems trained on historical or proxy data. The analysis further explores the regulatory landscape, including emerging legal frameworks such as the European Union’s AI Act and data protection regimes like the GDPR and CCPA, which aim to ensure transparency, accountability, and fairness in algorithmic operations. Emphasizing the need for explainable AI, fairness audits, and ethical governance, the paper underscores the imperative for insurers to align technological innovation with principles of justice, consumer autonomy, and regulatory compliance. Ultimately, the study contends that the future of AI in insurance hinges not merely on technical sophistication but on the industry's capacity to harness these tools responsibly and equitably.
