Statutory Professions in AI governance and their consequences for explainable AI

AI systems need qualified professionals to explain them: Just as doctors, engineers, and lawyers must meet professional standards and can be held accountable for their work, the paper argues that a new "AI Architect" profession should be established to interpret and explain AI models to stakeholders, ensuring they have the necessary expertise to do so responsibly.

Current regulatory frameworks lack practical compliance mechanisms: While AI regulations are being developed globally, the paper identifies a critical gap—there are no concrete proposals for how to monitor and ensure ongoing compliance with these regulations, particularly regarding the use of explainable AI (XAI) as a compliance tool.

Explainable AI alone is insufficient without accountability structures: The paper suggests that simply making AI systems more transparent through XAI is not enough; these explanations must be provided by qualified, accountable professionals who can be held responsible if harms occur, similar to how licensed professionals in other high-risk fields operate.

Statutory professions can reduce AI-related harms: By drawing parallels to established professions in healthcare, engineering, and law—where statutory requirements have helped protect public safety—the paper proposes that a similar framework could minimize intentional and accidental harms from AI systems affecting health, safety, and individual rights.