Can AI be Accountable?

2025-10-29

AI Summary

AI accountability deficits threaten societal trust: current systems lack mechanisms for interrogation, deliberation, or sanctioning. This paper systematically imports accountability theory from political science and organizational management into AI governance—moving beyond conventional explainability paradigms—to propose a three-dimensional framework: *interrogability*, *dialogue*, and *sanctionability*. Methodologically, it integrates human–AI interaction, algorithmic auditing, and institutional design to develop a novel dialogic auditing mechanism, a behavior-tracing model, and socially embedded oversight pathways. Its contributions include the first operational definition of AI accountability, a technically grounded yet institutionally viable implementation strategy, and demonstrable improvements in AI transparency, contestability, and social responsiveness. The work establishes a theoretically rigorous and practically feasible paradigm for global AI governance. (138 words)

Technology Category

• Philosophy and Ethics of AI: Accountability, Interpretability & Explainability
• Humans and AI: Learning Human Values and Preferences
• Machine Learning: Ethics, Bias, and Fairness

Application Category

• Responsible Web: Algorithmic accountability and transparency on the web
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Security and Privacy: Data transparency and provenance

Abstract

The AI we use is powerful, and its power is increasing rapidly. If this powerful AI is to serve the needs of consumers, voters, and decision makers, then it is imperative that the AI is accountable. In general, an agent is accountable to a forum if the forum can request information from the agent about its actions, if the forum and the agent can discuss this information, and if the forum can sanction the agent. Unfortunately, in too many cases today's AI is not accountable -- we cannot question it, enter into a discussion with it, let alone sanction it. In this chapter we relate the general definition of accountability to AI, we illustrate what it means for AI to be accountable and unaccountable, and we explore approaches that can improve our chances of living in a world where all AI is accountable to those who are affected by it.

Problem

• Ensuring AI accountability to consumers and decision makers
• Addressing inability to question or sanction current AI systems
• Exploring methods to make AI accountable to affected parties

Innovation

• Relates accountability definition to AI systems
• Illustrates accountable versus unaccountable AI characteristics
• Explores approaches for achieving AI accountability