THE LEGAL AND ETHICAL IMPLICATIONS OF AI-DRIVEN DATA BREACHES: CHALLENGES IN ATTRIBUTION AND LIABILITY
AUTHOR – AKANSHA, IILM GREATER NOIDA
BEST CITATION – AKANSHA, THE LEGAL AND ETHICAL IMPLICATIONS OF AI-DRIVEN DATA BREACHES: CHALLENGES IN ATTRIBUTION AND LIABILITY, INDIAN JOURNAL OF LEGAL REVIEW (IJLR), 5 (6) OF 2025, PG. 689-703, APIS – 3920 – 0001 & ISSN – 2583-2344
ABSTRACT
As AI enters and modifies digital disruption, a major impact on cyber security is attributed to analytical capabilities in detecting and responding to threats. Nevertheless, this has caused an infantile upward trajectory in malicious actors using AI tools to induce autonomous attacks. Some pressing issues include AI-assisted data breaches with its major distinguishing feature: unauthorized access to sensitive information accomplished partially or fully by AI systems. With these acts come immense legal and ethical questions: particularly attributing moral and civil responsibility. These pre-established legal frameworks centre more on human intent and liability rather than the complications of autonomous self-learning systems.
Through this research paper, the authors investigate the multifarious challenges of AI-influenced data breaches. The paper navigates the nature of actionable data breaches, the use of AI tools for any slapstick kind of infiltration, exfiltration, or manipulation of data, and complexity and autonomy that make forensic examination very complicated. The laws in plethora of jurisdictions such as the European Union, the US, and India are evaluated, where significant gaps in AI-specific regulation are found. For example, GDPR and California Consumer Privacy Act (CCPA) are robust in respective domains. Still, they do not cover AI-enabled cyberattacks, particularly self-modifying algorithms or cloud-based AI tools working on third-party servers.
From the ethical plane, it would also throw into question moral responsibility while an autonomous data breach is being perpetrated. In a situation where an AI system, on its own, is responsible for a data breach, who then should take the blame? The developer, the deployer, the one making use of it, or the AI itself? Such issues challenge long-established principles of moral agency, intent, and fairness. Its further points to AI and the lack of transparency regarding it, which include the “black box” nature of such processes, resulting in ethical accountability being impeded and legal adjudication being deferred.
Attribution, the identification of the actor behind a breach, becomes notorious with AI. AI can cover up its digital train, traverse multiple jurisdictions, and attack without sustained human monitoring, greatly hampering international cooperation and legal enforcement. The nuance continues with liability: Do we want to regard liability as strict, negligence-based, or vicarious when AI itself becomes the agent of harm? The authors argue for adopting a model of liability that is hybrid, with regard to control, intent, and foreseeability operative of all stakeholders.
To tackle the above challenges, this paper supports a multi-pronged approach operating toward legislative reform, ethical design of AI, and international collaboration. Suggested solutions include framing laws on AI-specific liability, global protocols on attribution, and mandatory/voluntary collaboration involving international stakeholders.