aiqbench analysis
This paper addresses the philosophical and procedural foundations of transparency when using AI in scholarly ethical research, proposing a framework that prioritizes documenting human agency over simple output evaluation. By grounding disclosure requirements in "agent-integrity," it offers a structured approach for researchers to maintain meaningful control while utilizing LLMs as tools within their inquiry process.
The Journal of Prompt-Engineered (Moral) Philosophy Or: Why AI-Assisted Ethics Research Requires Process Transparency
arXiv:2511.08639v4 Announce Type: replace-cross Abstract: Existing AI disclosure mandates in scholarship require that AI assistance be reported but leave transparency philosophically unspecified: they fix the duty without explaining what the duty serves. We argue that ethical inquiry is essentially contested at two independent levels -- about what it is, and about what it demands of the inquirer -- defeating output-only evaluation and welfare-economic dismissal of the transparency question, and, by extension, reproducibility framings imported from the empirical sciences. The transparency duty is grounded instead in agent-integrity: the legibility, before a community of inquiry, of the identity-constituting commitments that the author's mode of philosophising expresses. Because the standards for evaluating such work are not communally settled, the achievable goal for transparency is not evaluation against agreed criteria but tracking -- accumulating the evidentiary record that lets each tradition assess the work on its own terms and makes future normative judgments possible. We develop a documentation-adequacy framework that operationalises Meaningful Human Control through five transparency elements -- declaration, navigation, documentation account, process documentation, and development records -- demonstrated by the paper itself, whose full documentation record is archived at a persistent identifier. The framework is a first iteration subject to revision, not a settled standard.
arXiv:2511.08639 (cs)
Abstract:Existing AI disclosure mandates in scholarship require that AI assistance be reported but leave transparency philosophically unspecified: they fix the duty without explaining what the duty serves. We argue that ethical inquiry is essentially contested at two independent levels -- about what it is, and about what it demands of the inquirer -- defeating output-only evaluation and welfare-economic dismissal of the transparency question, and, by extension, reproducibility framings imported from the empirical sciences. The transparency duty is grounded instead in agent-integrity: the legibility, before a community of inquiry, of the identity-constituting commitments that the author's mode of philosophising expresses. Because the standards for evaluating such work are not communally settled, the achievable goal for transparency is not evaluation against agreed criteria but tracking -- accumulating the evidentiary record that lets each tradition assess the work on its own terms and makes future normative judgments possible. We develop a documentation-adequacy framework that operationalises Meaningful Human Control through five transparency elements -- declaration, navigation, documentation account, process documentation, and development records -- demonstrated by the paper itself, whose full documentation record is archived at a persistent identifier. The framework is a first iteration subject to revision, not a settled standard.
Computers and Society (cs.CY); Artificial Intelligence (cs.AI); Digital Libraries (cs.DL)
K.4.2; H.3.7; I.2.7
arXiv:2511.08639 [cs.CY]
(or arXiv:2511.08639v4 [cs.CY] for this version)
From: Michele Loi Dr. [view email] [v1] Mon, 10 Nov 2025 08:56:21 UTC (654 KB) [v2] Tue, 6 Jan 2026 17:29:26 UTC (746 KB) [v3] Mon, 18 May 2026 11:23:04 UTC (226 KB) [v4] Fri, 12 Jun 2026 15:50:54 UTC (357 KB)
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Full text under the publisher's open licence · 335 words