The intelligence may be artificial but the liability is real: the golden age of AI and the three hidden risks

Agentic AI promises significant gains in speed, scale, and discovery, yet ultimate liability remains human. Drawing from epistemology, this paper outlines two core principles for responsible AI adoption: Human Epistemic Sovereignty: People must retain final authority over consequential judgments and justified beliefs; Calibrated Epistemic Humility: Users and institutions must right-size confidence to match uncertainty, evidence weight, and potential harm. Rapid AI deployment without mature governance leads to three hidden liabilities: cognitive debt, technical debt, and governance debt. Examining these risks across healthcare, education, information, and professional services, the paper proposes a governable AI architecture that embeds uncertainty signaling, provenance, escalation, review, and accountability directly into operational workflows. This work summarizes the panel “The Intelligence May Be Artificial But the Liability is Real” from the 2026 Midwest Association for Information Systems (MWAIS) Conference at Ohio University.

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Publication Details

Journal
Journal of Information Technology Case and Application Research
Published
2026-08-17
DOI
https://doi.org/10.1080/15228053.2026.2709270
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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The intelligence may be artificial but the liability is real: the golden age of AI and the three hidden risks

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Journal of Information Technology Case and Application Research
Artificial Intelligence in Healthcare and Education
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The intelligence may be artificial but the liability is real: the golden age of AI and the three hidden risks

Lari B. Masten, Sridhar Ramamoorti, Madison Doty, Robert Miller, Salem Boumediene, Bobby Koritala
article en

Abstract

Agentic AI promises significant gains in speed, scale, and discovery, yet ultimate liability remains human. Drawing from epistemology, this paper outlines two core principles for responsible AI adoption: Human Epistemic Sovereignty: People must retain final authority over consequential judgments and justified beliefs; Calibrated Epistemic Humility: Users and institutions must right-size confidence to match uncertainty, evidence weight, and potential harm. Rapid AI deployment without mature governance leads to three hidden liabilities: cognitive debt, technical debt, and governance debt. Examining these risks across healthcare, education, information, and professional services, the paper proposes a governable AI architecture that embeds uncertainty signaling, provenance, escalation, review, and accountability directly into operational workflows. This work summarizes the panel “The Intelligence May Be Artificial But the Liability is Real” from the 2026 Midwest Association for Information Systems (MWAIS) Conference at Ohio University.

Journal of Information Technology Case and Application Research
University of Dayton (US), Mayo Clinic (US), Nodality (United States) (US), University of Illinois at Springfield (US)
Openalex Percentile: Top 13%
Artificial Intelligence in Healthcare and Education
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