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arxiv: 2604.27129 · v1 · submitted 2026-04-29 · 💻 cs.HC

What Influences Readers' and Writers' Perceived Necessity of AI Disclosure?

Jingchao Fang , Victoria Xiaohan Wen , Mina Lee This is my paper

Pith reviewed 2026-05-07 08:39 UTC · model grok-4.3

classification 💻 cs.HC
keywords AI disclosurewriting transparencyreaders vs writersvignette studyperceived necessityAI in writingintentionalityprocedural factors
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The pith

Readers consider AI disclosure in writing more necessary than writers do, especially when the AI contribution is irreplaceable, directly incorporated, and not intentionally steered by the writer.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper examines factors shaping judgments about whether writers must reveal AI assistance in their work. Using hypothetical vignette scenarios presented to 727 participants, it compares views from the reader perspective versus the writer perspective and tests how replaceability, directness, intentionality, and effort of AI use affect those views. Readers consistently rate disclosure as more necessary overall. Necessity rises when AI handles tasks the writer could not easily do themselves, when AI text appears directly in the final output, and when the writer did not deliberately guide the AI. Intentionality produces opposite effects for the two groups, while the amount of human effort involved shows no reliable influence.

Core claim

In the vignette study, readers judge disclosure of AI use more necessary than writers judge it. Perceived necessity increases when AI's contribution is irreplaceable by the writer, when the AI output is incorporated directly, and when the writer does not intentionally steer the generation. The intentionality of AI use produces contrasting effects on readers' and writers' perceptions. Writing effort shows no significant effect on necessity ratings. These patterns supply empirical evidence on grassroots attitudes toward transparent AI use in writing.

What carries the argument

Vignette-based survey design that systematically varies the evaluator's perspective (reader or writer), the text's purpose, and four procedural attributes of AI involvement (replaceability, effortfulness, intentionality, and directness) to measure perceived necessity of disclosure.

Load-bearing premise

Judgments collected from responses to hypothetical vignette scenarios accurately reflect the stable real-world views people hold about AI disclosure necessity.

What would settle it

A study using actual AI-assisted writing samples and real reader or writer participants that finds no difference in perceived necessity when AI contributions are irreplaceable versus replaceable, or when use is direct versus indirect.

Figures

Figures reproduced from arXiv: 2604.27129 by Jingchao Fang, Mina Lee, Victoria Xiaohan Wen.

Figure 1
Figure 1. Figure 1: Vignettes from readers’ perspective (left) and writers’ perspective (right) . Both vignettes embed texts that manip￾ulate purpose (evaluation, learning, or entertainment) and four procedural factors: replaceability, effortfulness, intentionality, and directness (high or low for each procedural factor). 4.2 Data collection We deployed the study in August 2025. The study is implemented in Qualtrics.3 The dat… view at source ↗
Figure 2
Figure 2. Figure 2: Study procedure. The green bolded arrows lead to study completion, while the gray arrows lead to quitting due to view at source ↗
Figure 3
Figure 3. Figure 3: A bar graph showing the procedural factors’ differing effects on perceived neces￾sity of AI disclosure based on perspective, according to the logistic regression model shown in view at source ↗
Figure 4
Figure 4. Figure 4: On the left, we show three existing approaches that guide writers’ AI disclosure. Part (a) shows Springer Nature AI authorship policy, with the text directly coming from Nature [84]. Part (b) shows a sample AI disclosure statement structured based on the PaperCard framework, with the text directly coming from Cho et al. [17]. Part (c) shows an example of “Created Using Generative AI” tag (and its variant, … view at source ↗
read the original abstract

The growing capability of artificial intelligence (AI) leads to its increasing adoption in writing, spurring discussions around whether writers should disclose their AI use in writing. What influences the perceived necessity of disclosure? We look into this question from three dimensions: perspective (reader or writer of the text), purpose (the goal of reading or writing), and procedural factors (how AI was used in the writing process in terms of replaceability, effortfulness, intentionality, and directness). In a vignette study (N = 727), we find that readers consider disclosure to be more necessary than writers, and disclosure is regarded as more necessary when AI's contribution in writing is irreplaceable, directly incorporated, and when the writer does not intentionally steer AI generation. To our surprise, the writers' intentionality of AI use produces contrasting effects on readers' and writers' perceived necessity of disclosure. Moreover, the effort of writing shows no significant effect on the perceived necessity. This study contributes to the conversation on transparent AI use by revealing readers' and writers' grassroots judgments, providing a unique angle to reflect on existing regulations, and offering insights into how AI disclosure guidance and tools could be designed to better align with readers' and writers' perceptions.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 2 minor

Summary. The paper reports a between-subjects vignette study (N=727) that examines how perspective (reader vs. writer), purpose, and procedural factors (replaceability, directness, intentionality, and effort of AI use) influence perceived necessity of disclosing AI assistance in writing. It claims readers rate disclosure necessity higher than writers; necessity increases when AI contributions are irreplaceable and directly incorporated and when writers do not intentionally steer generation; intentionality produces opposite effects across perspectives; and effort has no significant effect. The work positions these grassroots judgments as input for regulations and AI tool design.

Significance. If the directional findings prove robust, the study supplies empirical evidence on divergent reader/writer perceptions that is currently scarce in HCI and AI ethics literature. The large sample and multi-factor vignette design allow clean isolation of procedural variables, and the contrasting intentionality result is a potentially novel contribution. These data could usefully inform disclosure guidelines, though the absence of behavioral validation weakens direct policy translation.

major comments (3)
  1. [Methods] Methods section: the vignette construction, pretesting for realism, and checks for demand characteristics or social-desirability bias are not described in sufficient detail to evaluate whether the reported effects (e.g., irreplaceability and intentionality) could be artifacts of the hypothetical framing.
  2. [Discussion] Results and Discussion: the manuscript draws regulatory and design recommendations directly from vignette ratings without behavioral validation, comparison to real AI-assisted writing tasks, or explicit discussion of ecological validity, making the policy claims load-bearing on an untested assumption.
  3. [Results] Results: while directional findings are stated, the text provides no effect sizes, exact statistical tests, exclusion criteria, or control variables, preventing assessment of the practical magnitude of the reader-writer gap and the opposing intentionality effects.
minor comments (2)
  1. [Abstract] Abstract: the phrase 'to our surprise' for the intentionality result is informal; a brief statement of the opposing directions would improve clarity for readers.
  2. [Methods] The paper would benefit from a table summarizing the four procedural factors and their levels to aid quick reference.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for the detailed and constructive comments. We address each major point below and describe the revisions we will make to strengthen the manuscript.

read point-by-point responses

  1. Referee: [Methods] Methods section: the vignette construction, pretesting for realism, and checks for demand characteristics or social-desirability bias are not described in sufficient detail to evaluate whether the reported effects (e.g., irreplaceability and intentionality) could be artifacts of the hypothetical framing.

    Authors: We agree that the Methods section requires greater detail to allow readers to assess potential artifacts from the vignette design. In the revised manuscript we will expand the description of vignette construction, including how the four procedural factors were operationalized and balanced across conditions; report any pretesting or pilot work used to verify realism and comprehensibility; and describe steps taken to check for demand characteristics or social-desirability bias (or, if none were performed, explicitly note this limitation and its implications for interpretation). revision: yes

  2. Referee: [Discussion] Results and Discussion: the manuscript draws regulatory and design recommendations directly from vignette ratings without behavioral validation, comparison to real AI-assisted writing tasks, or explicit discussion of ecological validity, making the policy claims load-bearing on an untested assumption.

    Authors: We accept that the current framing of recommendations overreaches given the vignette methodology. In the revision we will add a dedicated limitations subsection that explicitly discusses ecological validity, the absence of behavioral measures or real-task comparisons, and the hypothetical nature of the scenarios. We will rephrase all regulatory and design implications as preliminary, hypothesis-generating insights rather than direct prescriptions, and we will state that further validation in naturalistic settings is required before these findings can inform policy. revision: yes

  3. Referee: [Results] Results: while directional findings are stated, the text provides no effect sizes, exact statistical tests, exclusion criteria, or control variables, preventing assessment of the practical magnitude of the reader-writer gap and the opposing intentionality effects.

    Authors: We will revise the Results section to report effect sizes (e.g., partial eta-squared or Cohen’s d) for all key contrasts, include the full statistical output (F or t values, degrees of freedom, exact p-values), detail participant exclusion criteria and any data-cleaning steps, and specify whether demographic or other control variables were included in the models. These additions will allow readers to evaluate both statistical significance and practical magnitude of the reported effects. revision: yes

Circularity Check

0 steps flagged

Empirical vignette study with no derivations or self-referential reductions

full rationale

This paper reports results from a between-subjects vignette experiment (N=727) in which independent participant ratings of disclosure necessity are collected and statistically compared across conditions varying perspective, replaceability, directness, intentionality, and effort. All central claims (readers > writers; irreplaceable/direct use increases necessity; intentionality produces opposite effects; effort null) are direct outputs of these participant responses. No equations, fitted parameters, predictions, uniqueness theorems, or ansatzes appear; no self-citations are invoked as load-bearing premises. The derivation chain consists solely of data collection and analysis, making the study self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The paper is an empirical vignette study in human-computer interaction. It relies on standard survey and statistical methods without introducing new free parameters, theoretical axioms beyond domain conventions, or invented entities.

axioms (1)
  • domain assumption Participant responses to hypothetical vignettes reflect genuine perceptions of disclosure necessity that would generalize beyond the study scenarios.
    This is the core premise of vignette methodology; if violated, the reported differences between readers and writers would not hold in real writing contexts.

pith-pipeline@v0.9.0 · 5518 in / 1466 out tokens · 168463 ms · 2026-05-07T08:39:32.950921+00:00 · methodology

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Reference graph

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