Abstract
As artificial intelligence (AI) systems become embedded in public decision-making—from predictive policing to educational assessments—the legal system must confront a critical question: How can we ensure accountability when algorithms shape outcomes that affect rights, access, and equity? This article explores the intersection of administrative law, tort liability, and constitutional safeguards in regulating AI use by government entities. It argues for a proactive legal framework that balances innovation with transparency, procedural fairness, and democratic oversight.
I. Introduction
Governments increasingly rely on AI to streamline services, allocate resources, and make high-stakes decisions. While these systems promise efficiency, they also introduce risks of bias, opacity, and harm. Legal accountability mechanisms must evolve to address these challenges, ensuring that public sector AI remains subject to the rule of law.
II. Legal Foundations of Public Sector Accountability
A. Administrative Law and Procedural Safeguards
Administrative law provides a foundation for challenging arbitrary or capricious government action. When AI systems are used to make or inform decisions, affected individuals must retain the right to understand, contest, and appeal those outcomes. Courts have begun to grapple with whether algorithmic decision-making meets standards of due process and reasoned explanation.
B. Constitutional Considerations
AI systems deployed by the state may implicate constitutional rights, including equal protection, privacy, and freedom of expression. For example, predictive policing tools have been criticized for reinforcing racial disparities, raising Fourteenth Amendment concerns. Legal scrutiny must extend to the design, deployment, and impact of these technologies.
III. Tort Liability and Government Immunity
A. Negligence and Duty of Care
When AI systems cause harm—such as erroneous denial of benefits or wrongful arrest—plaintiffs may seek redress under tort law. However, government actors often enjoy sovereign immunity, limiting liability. Courts must consider whether deploying high-risk AI without adequate safeguards constitutes a breach of duty.
B. Emerging Doctrines
Some scholars advocate for a “duty to audit” or “duty to explain” in public sector AI use. These concepts could form the basis for new liability standards, encouraging transparency and accountability without stifling innovation.
IV. Toward a Proactive Legal Framework
To ensure responsible AI governance, legal systems should adopt the following principles:
- Transparency Mandates. Require public disclosure of algorithmic logic, training data, and decision criteria.
- Impact Assessments. Mandate equity and privacy reviews before deployment.
- Appeal Mechanisms. Guarantee human review and redress pathways for affected individuals.
- Participatory Design. Involve stakeholders—including educators, legal experts, and community members—in system development.
These measures align with broader goals of democratic accountability and governance.
V. Conclusion
AI in the public sector presents both promise and peril. Legal frameworks must rise to the challenge, ensuring that algorithmic tools serve the public interest without undermining rights or fairness. By grounding innovation in legal accountability, we can build systems that are not only intelligent, but just.
References
- University of Chicago Law Review: Holding AI Accountable
- RAND Report: Liability for Harms from AI Systems
- The Legal Quorum: Challenges of Accountability in Autonomous Decision-Making
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