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REVIEW 3 major objections 3 minor 73 references

CreepyCoCreator? Investigating AI Representation Modes for 3D Object Co-Creation in Virtual Reality

T0 review · 3 major / 3 minor · reviewed 2026-08-09 · deepseek-v4-flash

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Pith's one-line read Give the AI a body and VR co-creation feels like teamwork

desk verdict Worth engaging: the embodiment effects on communication and partnership look credible, but the contribution-attribution result is tangled in a user/AI action-share confound the paper doesn't test. read the letter →

arxiv 2502.03069 v3 pith:OGASWLOP submitted 2025-02-05 cs.HC

Julian Rasch , Julia Töws , Teresa Hirzle , Florian Müller , Martin Schmitz This is my paper · ORCID
classification cs.HC
keywords co-creativesystemsgenerativeAIvirtualreality3DobjectcreationembodimentrepresentationWizard-of-Ozstudyuser
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

The paper tests three ways of showing what a generative AI is doing while a user and the AI co-customize a 3D object in virtual reality: giving the AI a body, animating its changes gradually instead of instantly, and outlining the part it is about to change. Using a Wizard-of-Oz setup in which a human experimenter triggered pre-made modifications, the study reports that embodiment is the mode that changes the relationship: with an avatar, users felt communication and partnership were stronger, paid more attention to the AI, and credited the AI with a larger share of the finished object. Highlighting, by contrast, did not make the AI more predictable or easier to communicate with, and it reduced enjoyment, partnership, and satisfaction. Incremental visualization drew attention but also made outputs feel more unexpected and took longer. The authors conclude that designers should use embodiment when they want collaboration to feel like a partnership, but accept that users will feel less ownership of the result, and should avoid combining highlighting with an embodied avatar.

What carries the argument

The central object is the Wizard-of-Oz VR co-creation platform itself, in which a human 'wizard' triggered pre-authored 3D additions and replacements, paired with the 2x2x2 factorial manipulation of three representation modes: highlighting (an outline around the part to be modified), incremental visualization (the new part growing slice by slice, like 3D printing), and embodiment (a caricatured child-like avatar that walks to the object and performs the change). The machinery that carries the argument is the contrast between the same underlying AI behavior and three orthogonal visual framings; any differences in user ratings must be attributed to how the action was represented, since the underlying behavior was identical across conditions.

What would settle it

Run the same 2x2x2 comparison with a real generative model whose outputs vary, fail, and take unpredictable time. If the embodiment effects on communication, partnership, and contribution attribution disappear or invert with real generation latencies, the claim that representation modes drive perceived collaboration would not hold beyond the simulated setup. A cheaper check: ask participants after the session whether they believed the AI generated the modifications; if disbelief is widespread, the measured attribution effects may be artifacts of that belief.

Watch

Extended reading notes

Core claim

The central empirical claim is that representational choices that are purely about how AI actions are shown—not about what the AI can actually do—shift the social and psychological character of co-creation. In a within-subjects VR study with 16 participants, embodiment significantly increased perceived communication (F(1,15)=26.19, p<.001), perceived partnership (F(1,15)=23.5, p<.001), perceived supportiveness (F(1,15)=5.74, p<.05), attention paid to the AI (F(1,15)=9.43, p<.01), and the extent to which users attributed the finished model to the AI (F(1,15)=9.19, p<.01). Highlighting, expected to improve predictability and communication, did neither, while it significantly decreased enjoyment (F(1,15)=7.89, p<.05), partnership (F(1,15)=6.18, p<.05), and satisfaction (F(1,15)=5.06, p<.05). Incremental visualization increased attention and made outputs feel more unexpected (F(1,15)=7.52, p<.05) without improving perceived efficiency or competence. The paper reads these results as evidence that an embodied representation can move a system from being perceived as a tool to being perceived as a collaborator, and warns that designers should treat ownership perception as a design consequence.

Load-bearing premise

The AI's contributions were scripted ahead of time by human 3D artists; everything the study concludes about perceived collaboration rests on participants accepting this pre-programmed agent as a genuine generative AI during the sessions.

Editorial extensions

If this is right

  • Adding an embodied avatar to a generative co-creation tool will increase perceived communication, partnership, and support, but will reduce users' felt ownership of the output.
  • Highlighting the area about to be modified should be avoided for single-object co-creation, because it lowers enjoyment, partnership, and satisfaction without improving predictability.
  • Immediate visualization is preferable when the creation process is secondary and time matters; incremental visualization is useful when designers want users to watch the generation closely.
  • Designers should consider that perceived authorship, not just actual functionality, determines how users feel about and attribute co-created artifacts.
  • Because the setup was technology-agnostic and simulated, these design implications can guide future real generative systems regardless of the specific model used.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the authorship-shift effect generalizes to real text-to-3D systems, then the embodiment decision is also an ethical decision: an avatar can quietly change who users believe created the artifact, which matters for ownership and credit debates.
  • The finding on highlighting suggests a possible distraction or error-signal interpretation rather than a transparency benefit; a testable extension would be to measure gaze or physiological arousal during highlighted versus unhighlighted modifications.
  • Since the AI was scripted, the temporal rhythm of a real generative model—latency, failures, iterative refinement—may interact with these representation modes, so a real-system replication could show different attention and partnership effects.
  • The perceived-unexpectedness increase under incremental visualization may imply that slow visualization gives users time to form predictions that the final output then violates; if so, pacing could be tuned to manage surprise, not just to reveal process.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 3 minor

Summary. The paper reports a Wizard-of-Oz VR user study (N=16) using a 2x2x2 within-subjects design to test how three AI representation modes — highlighting of modified areas, incremental versus immediate visualization of changes, and embodiment as an avatar — affect users' perceptions of a co-creative 3D-object generation AI. Outcome measures include interaction logs, a 27-item questionnaire, and semi-structured interviews. The reported findings are that embodiment increases perceived support, communication, partnership, attention to the AI, and attribution of the finished model to the AI; highlighting decreases enjoyment, satisfaction, and partnership; and incremental visualization increases attention and perceived unexpectedness of AI output. Based on these results, the paper derives design implications for co-creative VR object-building systems.

Significance. If the main findings hold, the paper makes a useful empirical contribution to the under-studied area of AI representation in co-creative VR object generation. The study is carefully designed in several respects: it uses a counterbalanced repeated-measures design, appropriate nonparametric procedures (ART/ART-C) for questionnaire data, captures both behavioral and qualitative evidence, and explicitly discusses limitations, including the Wizard-of-Oz nature of the AI. The design implications (avoid highlighting, prefer embodiment for collaborative use cases, use immediate visualization when process is secondary) are actionable and clearly grounded in the reported results. However, the main claim that embodiment changes perceived AI contribution independently of actual contribution shares is weakened by a plausible behavioral confound, and the statistical analysis does not address the large number of questionnaire items tested.

major comments (3)
  1. [Sec. 4.1.2 and Sec. 4.2.6] The central claim that embodiment shifts perceived AI contribution is threatened by an action-share confound. Sec. 4.1.2 reports that participants painted significantly less when embodiment was enabled (F(1,15)=9.349, p<.01), yet the paper does not report whether the number of AI modifications actually applied was constant across conditions. If the AI's additions and replacements were similar while users painted less, the final artifact objectively contained a larger AI share in embodied conditions; the single bipolar item 'The finished model was made by only me vs. only the AI' could then track the actual contribution ratio rather than a changed perception. Sec. 5.3 interprets this result as 'factors external to the AI functionality can manipulate users' perceptions of who created an artifact.' To support that interpretation, the authors should report AI-modification counts by condition and either show that the contribution-attribution effect survives controlling for painting time/action share or report a mediation analysis.
  2. [Sec. 4.2] The questionnaire analysis tests 27 items across three main effects and their interactions without any correction for multiple comparisons. The paper states that post-hoc contrasts were corrected with ART-C/Tukey, but it does not mention any adjustment across the 27 dependent variables. With N=16 and many isolated p-values near the .05 threshold, several of the reported effects (e.g., enjoyment, satisfaction, contribution attribution) could be type-I errors. The authors should either apply a family-wise or false-discovery-rate correction across items, or explicitly frame the questionnaire results as exploratory and identify a smaller set of pre-registered primary hypotheses.
  3. [Sec. 3.1 and Sec. 6] The Wizard-of-Oz setup lacks a manipulation check on whether participants believed the AI actually generated the modifications. The authors themselves acknowledge in Sec. 6 that the limited and repetitive set of modifications 'could have led participants to the conclusion that their AI partner did not actually generate object parts.' This is a load-bearing threat to construct validity: if many participants treated the agent as a scripted animation rather than a generative AI, the measured 'perceived AI contribution' may not reflect perception of AI generation at all. The paper should report any questionnaire or interview evidence about perceived authenticity, or add a post-experiment item asking how much participants believed the AI generated the parts.
minor comments (3)
  1. [Sec. 3.2.1] In the embodiment description, the phrase 'If incremental visualization is not disabled' appears to be a double negative; it should probably read 'If incremental visualization is not enabled.'
  2. [Sec. 4.1.2 and Figure 4] The text says painting time results are shown in 'Figure 4a,' but the caption of Figure 4 labels panel (a) as 'Number of Engagements' and panel (b) as 'Painting Time.' Please correct the cross-reference.
  3. [Sec. 4.2.5] The sentence 'the amount of attention participants paid to the AI was more significant with embodiment' should be 'was significantly higher with embodiment'; 'more significant' is not a meaningful comparative for a p-value.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the paper is an empirical user study whose claims rest on new participant measurements, not on fitted parameters, self-citation chains, or definitional reductions.

full rationale

This paper reports a controlled Wizard-of-Oz VR user study with no fitted model parameters, no mathematical derivation, and no prediction computed from prior equations. The central empirical claims — e.g., embodiment increases perceived communication (F(1,15)=26.19, p<.001), partnership (F(1,15)=23.5, p<.001), and AI contribution attribution (F(1,15)=9.19, p<.01) — are new measurements from 16 participants, so they cannot reduce by construction to their inputs. Citations to Rezwana and Maher are used for framing concepts such as provoking agents, for selecting questionnaire items (partnership and communication), and for interpreting ownership ethics; none of these citations supplies the empirical evidence for the paper's findings, so they are not load-bearing in a circular sense. The Wizard-of-Oz simulation is an acknowledged methodological limitation, not a circular argument: the paper explicitly states that AI contributions were pre-made by artists and even discusses in Section 6 that the limited modification set may have led participants to doubt that the AI generated parts. The skeptic's concern that embodiment reduced painting time (F(1,15)=9.349, p<.01) and may thereby have changed the objective user/AI action ratio is a plausible confound or internal-validity critique, but it is not a circularity: the measured outcome is not definitionally identical to the manipulation, nor is it derived from the manipulation's construction. The paper derives design implications from its observed data rather than assuming them. Accordingly, no self-definitional step, fitted-input-called-prediction, uniqueness import, ansatz smuggling, or renaming of a known result is present, and the appropriate circularity score is 0.

Assumptions & free parameters 4 free parameters · 4 assumptions · 0 invented entities

This is an empirical user study, so there are no fitted parameters in the mathematical sense. The free parameters listed are hand-chosen design constants that affect the operationalization of the independent variables. The axioms are the background assumptions about the validity of the Wizard-of-Oz simulation, the avatar design, the measurement instruments, and the generalizability of the controlled task.

free parameters (4)
  • highlight display duration = 3 seconds when no other modes are enabled
    In Section 3.2.1, the highlight outline is displayed for three seconds in the non-incremental, non-embodied cases, a hand-chosen duration that could influence the perceived usefulness of highlighting.
  • session duration = 5 minutes
    Each modeling session was timed at five minutes (Section 3.4), a design choice that limits the number of interactions and could affect engagement and satisfaction measures.
  • number of starting objects = 4
    The study used four objects (dinosaur, chair, pickup truck, house), see Section 3.1, a hand-picked set that may not represent the range of co-creative 3D tasks and limits generalizability.
  • number of AI modifications per object = 7
    Each object allowed exactly seven pre-scripted modifications (Section 3.1), a hand-chosen number that affects how often users encounter AI actions and their impression of the AI's competence.
assumptions (4)
  • domain assumption Wizard-of-Oz simulation is a valid proxy for generative AI
    Section 3.1 states the AI contributions are pre-made by human artists; the study assumes participants respond to this simulated agent as they would to a real generative system, which Section 6 acknowledges may not hold.
  • domain assumption The chosen avatar design is representative of embodied AI
    The embodiment condition uses a single cartoon avatar designed to be friendly and caricatured (Section 3.2.1 and 5.3); the effects measured may be specific to this appearance and not to other embodied representations.
  • domain assumption Questionnaire items validly measure the intended constructs
    The paper adopts items from MICSI, CSI, UEQ, IOS, and SPGQ (Section 3.2.2), some with minor modifications, assuming these measure the intended perceptions of creativity, partnership, communication, and closeness.
  • domain assumption Lab behavior reflects real-world co-creative use
    The controlled task with a timer and artificial setting (Section 3.4) may not capture genuine co-creation, a limitation acknowledged in Section 6 under external validity.

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Cite this review

Pith. "Pith review of CreepyCoCreator? Investigating AI Representation Modes for 3D Object Co-Creation in Virtual Reality." pith.science (2026). https://pith.science/paper/OGASWLOP

@misc{pith2026250203069,
  author       = {Pith},
  title        = {Pith review of: CreepyCoCreator? Investigating AI Representation Modes for 3D Object Co-Creation in Virtual Reality},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/OGASWLOP}},
  note         = {Machine review of arXiv:2502.03069}
}
read the original abstract

Generative AI in Virtual Reality offers the potential for collaborative object-building, yet challenges remain in aligning AI contributions with user expectations. In particular, users often struggle to understand and collaborate with AI when its actions are not transparently represented. This paper thus explores the co-creative object-building process through a Wizard-of-Oz study, focusing on how AI can effectively convey its intent to users during object customization in Virtual Reality. Inspired by human-to-human collaboration, we focus on three representation modes: the presence of an embodied avatar, whether the AI's contributions are visualized immediately or incrementally, and whether the areas modified are highlighted in advance. The findings provide insights into how these factors affect user perception and interaction with object-generating AI tools in Virtual Reality as well as satisfaction and ownership of the created objects. The results offer design implications for co-creative world-building systems, aiming to foster more effective and satisfying collaborations between humans and AI in Virtual Reality.

Figures

Figures reproduced from arXiv: 2502.03069 by the authors.

Figure 1
Figure 1. In this paper, we explore VR interaction with an object-generating co-creative AI via a Wizard-of-Oz study on how the [PITH_FULL_IMAGE:figures/full_fig_p001_1.png] view at source ↗
Figure 2
Figure 2. Steps during the collaboration creation at the example of a chair: (a) The chair at the center of the room on a podium [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. We vary three different independent variables: (1) whether the AI has an embodied representation or is disembodied, [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: The number of engagements and painting time in our experiment. All error bars depict the standard error. [PITH_FULL_IMAGE:figures/full_fig_p007_4.png]
Figure 5
Figure 5. Figure 5: Significant effects of embodiment on attributing contributions to the AI, perceived communication and partnership, [PITH_FULL_IMAGE:figures/full_fig_p008_5.png]
Figure 6
Figure 6. Figure 6: The four modifiable objects in their default form before any modifications. Figure 6: The four modifiable objects in their default form, before any modifications. [PITH_FULL_IMAGE:figures/full_fig_p010_6.png]
Figure 7
Figure 7. Figure 7: A selection of finished models designed by participants, each influenced in different ways by the AI or its contributions. Figure 7: A selection of finished models designed by participants, each influenced differently by the AI or its contributions. [PITH_FULL_IMAGE:f…

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Pith tools

Reviewed August 9, 2026 · model on record in the stance chip above.