M. Madusubaasini & P. Suvarna Durga, SASTRA Deemed University, Tamil Nadu, India
ABSTRACT
The integration of Artificial Intelligence (AI) into family law proceedings and child custody decisions represents a transformative shift in the legal landscape. The Indian child custody cases are notably influenced by sociocultural and familial factors, which can complicate judicial decisions. By analyzing case history, behavioral patterns, and other relevant factors, AI tools can provide insights into the best interests of the child, potentially enhancing decision-making. It examines how AI tools, such as predictive analytics and decision-support systems, are used to assess parental fitness, predict child outcomes, and assist in creating equitable custody arrangements. AI tools can assist in case management, risk assessment, and personalized decision-making, helping to streamline operations and inform custody decisions based on comprehensive data analysis. This paper addresses the ethical and practical aspects associated with AI in family law, including concerns about data privacy, algorithmic bias, and the potential erosion of human judgment. It explores how AI impacts the efficiency and fairness of divorce proceedings in various EU member states. It identifies the ethical dilemmas associated with AI use in a region characterized by diverse cultural and legal landscapes. By employing a combination of qualitative research methods, and case study, this study reveals the intricate dynamics between technological advancements and legal practices in the EU. The role of AI in enhancing the efficiency, consistency, fairness of family law adjudications and the integration of AI-driven support systems in child custody decision-making within the Indian legal framework. By analyzing current applications, legal frameworks, and case studies, this research provides a comprehensive overview of AI's impact on family proceedings and child custody decisions1.
Keywords: Artificial intelligence, Family law proceedings, Child custody, AI tool, efficiency, application of AI, Machine learning, Ethical implications and Fairness.
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