AI Efficiency Can Undermine Accountability Even With Humans in the Loop
US policymakers are rushing to build guardrails for artificial intelligence in government. One safeguard is quickly becoming the default answer: keep a human in the loop. The idea appears across the current wave of public-sector AI governance, from the White House’s recent National Policy Framework for Artificial Intelligence to emerging state legislation requiring human review, impact assessments, and agency oversight structures.
The logic is intuitive and politically reassuring. Let the system assist, let a person review the output, and accountability will remain intact.
But this assumption deserves much closer scrutiny. The real implementation problem is not only whether a human remains somewhere in the workflow. It is whether public institutions are deploying AI in ways that preserve the practical conditions of human judgment—or quietly erode them in the name of efficiency.
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