AI Liability and Accountability: A Review of Emerging Legal Frameworks

The abstract of this research paper delves into the evolving legal frameworks that are being established to address issues of liability and accountability concerning artificial intelligence (AI) systems. With the increasing integration of AI technology in various sectors, the question of responsibility for the actions of AI systems has gained significant prominence. The study examines the current landscape of AI regulation and the complexities faced in attributing liability in cases of accidents or errors involving AI technologies. It explores the diverse strategies and approaches being adopted by different jurisdictions to develop legal frameworks that govern the use of AI and determine accountability when unforeseen circumstances arise. Furthermore, the abstract underscores the significance of incorporating ethical considerations into the formulation of AI regulations, as ethical dilemmas often intersect with questions of legal liability. Various ethical frameworks proposed to guide the responsible development and utilization of AI are also discussed within the paper. The research emphasizes the necessity of establishing a robust and adaptable legal framework that can keep pace with the rapid advancements in AI technology while ensuring that appropriate mechanisms for assigning liability and accountability are in place. It advocates for collaborative efforts among policymakers, industry stakeholders, and ethicists to craft effective regulations that safeguard the interests of consumers and the wider society.

Authors

Publication Details

Journal
International Journal of Science and Research (IJSR)
Published
2025-09-22
DOI
https://doi.org/10.21275/sr25918083413
Primary Topic
Law, AI, and Intellectual Property
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI Liability and Accountability: A Review of Emerging Legal Frameworks

Dwiti Gambhir, Raghu Raja Mehra
International Journal of Science and Research (IJSR)
Law, AI, and Intellectual Property
article

AI Liability and Accountability: A Review of Emerging Legal Frameworks

Dwiti Gambhir, Raghu Raja Mehra
article en

Abstract

The abstract of this research paper delves into the evolving legal frameworks that are being established to address issues of liability and accountability concerning artificial intelligence (AI) systems. With the increasing integration of AI technology in various sectors, the question of responsibility for the actions of AI systems has gained significant prominence. The study examines the current landscape of AI regulation and the complexities faced in attributing liability in cases of accidents or errors involving AI technologies. It explores the diverse strategies and approaches being adopted by different jurisdictions to develop legal frameworks that govern the use of AI and determine accountability when unforeseen circumstances arise. Furthermore, the abstract underscores the significance of incorporating ethical considerations into the formulation of AI regulations, as ethical dilemmas often intersect with questions of legal liability. Various ethical frameworks proposed to guide the responsible development and utilization of AI are also discussed within the paper. The research emphasizes the necessity of establishing a robust and adaptable legal framework that can keep pace with the rapid advancements in AI technology while ensuring that appropriate mechanisms for assigning liability and accountability are in place. It advocates for collaborative efforts among policymakers, industry stakeholders, and ethicists to craft effective regulations that safeguard the interests of consumers and the wider society.

International Journal of Science and Research (IJSR)
Openalex Percentile: Top 87%
Law, AI, and Intellectual Property
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.