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arxiv: 2605.24729 · v1 · pith:UCZSVWOZnew · submitted 2026-05-23 · 💻 cs.HC

"It Felt a Bit Eerie": Exploring Humanlike Interactions During Collaborative Writing with an Artificial Agent

Michael Yin , Angela Chiang , Samuel Rhys Cox , Robert Xiao This is my paper

Pith reviewed 2026-06-30 12:06 UTC · model grok-4.3

classification 💻 cs.HC
keywords human-AI collaborationcollaborative writingAI text editorsynchronous suggestionsvisual cursoruser studysocial expectations
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The pith

Synchronous AI suggestions speed up writing but produce contextual misalignment, while a visible cursor improves intent understanding yet creates feelings of surveillance.

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

The paper tests whether making an AI writing partner act more like a human changes how people experience the task. Researchers created three versions of a text editor that differed in suggestion timing and the presence of a visible cursor to represent the AI's activity. In a study of 48 users, real-time suggestions helped complete work faster but often suggested content that did not fit the current paragraph, while the cursor made the AI's actions clearer but left users feeling observed. The work shows that borrowing human collaboration patterns for AI tools brings both efficiency gains and social frictions that do not arise in actual human-human writing.

Core claim

By placing three AI text editor variants along a spectrum from synchronous suggestions with a visual cursor to asynchronous suggestions without one, the study finds that the humanlike features increase efficiency and intent understanding yet also produce contextual misalignment and surveillance sensations, creating social expectations without the mutual alignment found in human collaboration.

What carries the argument

Three variants of an AI-assisted text editor that vary along temporal (synchronous vs asynchronous suggestions) and visual (cursor present vs absent) dimensions to simulate humanlike versus machinelike interaction.

If this is right

  • Synchronous suggestions raise writing speed but increase the chance that suggestions fall out of context.
  • A visible cursor makes the AI's intended edits easier for users to follow.
  • The visible cursor also triggers feelings that the AI is watching the user.
  • Humanlike interaction designs in AI systems can generate social expectations that the agent cannot fully meet.
  • Designers of collaborative AI tools must weigh efficiency and clarity gains against these social costs.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Adding explicit controls for cursor visibility might reduce the surveillance feeling while preserving the intent-understanding benefit.
  • Real-time suggestion systems could incorporate context-checking steps to reduce misalignment without losing speed advantages.
  • The same temporal and visual trade-offs may appear in AI tools for tasks other than writing, such as code or image editing.
  • Longer sessions might show whether users learn to ignore or adapt to the eerie sensation over time.

Load-bearing premise

The three editor versions differ only in suggestion timing and cursor visibility, with no other differences in suggestion quality or interface design that could produce the reported effects.

What would settle it

A controlled replication in which suggestion quality, phrasing, and all other interface elements are held identical across the three variants, after which the differences in efficiency, misalignment, understanding, and surveillance feelings are no longer observed.

Figures

Figures reproduced from arXiv: 2605.24729 by Angela Chiang, Michael Yin, Robert Xiao, Samuel Rhys Cox.

Figure 1
Figure 1. Figure 1: Variant 1 of our text editor. In (1), the author writes out the text that they would like feedback on, and upon pressing a button [PITH_FULL_IMAGE:figures/full_fig_p007_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Variant 2 of our text editor. While the author is writing, as in (1), the AI makes suggestions along the way. These suggestions [PITH_FULL_IMAGE:figures/full_fig_p008_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Variant 3 of our text editor. While the author is writing, as in (1), the AI has an agentic cursor that it moves within the text. [PITH_FULL_IMAGE:figures/full_fig_p009_3.png] view at source ↗
read the original abstract

While human-AI collaboration systems have increasingly been built to increase efficiency or support creativity, little work has examined how the design of interactions shapes the social connection between human and artificial agent. We examine how the temporal and visual dimensions of collaboration shape the experience of a writing task. Specifically, we built three variants of an AI-assisted text editor along a spectrum of simulated humanlike interaction (synchronous and with a cursor) to machinelike interaction (asynchronous and without a cursor), and conducted a comparative user study (n=48). Our exploratory findings suggest that synchronous suggestions increased efficiency but led to contextual misalignment, while a visual cursor increased intent understanding but evoked feelings of surveillance. Taken together, humanlike design of artificial agents can create positive social expectations but also elicit social costs, especially without the alignment present in human-human collaboration. We extend our findings into design implications and ethical considerations when building human-AI collaboration systems.

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

2 major / 2 minor

Summary. The paper reports an exploratory comparative user study (n=48) of three AI-assisted text editor variants spanning a spectrum from humanlike (synchronous suggestions with visual cursor) to machinelike (asynchronous without cursor). The central claims are that synchronous suggestions increase task efficiency but produce contextual misalignment, while the visual cursor improves understanding of AI intent but evokes surveillance feelings; overall, humanlike designs create positive social expectations alongside social costs absent in human-human alignment. The authors derive design implications and ethical considerations for human-AI collaboration systems.

Significance. If the isolation of temporal and visual factors holds, the work adds empirical grounding to HCI discussions of social connection in human-AI writing tools. The controlled between-subjects design and mixed-methods exploration of both efficiency and experiential costs provide a concrete basis for future interface guidelines, particularly as generative writing assistants proliferate.

major comments (2)
  1. [Methods] Methods, Study Design and Procedure sections: The manuscript must report quantitative metrics (e.g., suggestion frequency, average length, relevance scores, or generation latency) demonstrating that suggestion content and quality were statistically equivalent across the three editor variants. The skeptic concern is load-bearing because any systematic difference in backend prompting or caching between synchronous and asynchronous modes would provide an alternative explanation for the reported efficiency and misalignment effects, undermining attribution to the temporal dimension alone.
  2. [Results] Results section: The abstract states directional effects (efficiency increase, misalignment, intent understanding, surveillance) without accompanying statistical details, effect sizes, or exclusion criteria. The full paper must include the exact analysis methods (quantitative tests, qualitative coding scheme, inter-rater reliability) and report whether the n=48 sample was powered or whether any participants were excluded, as these details are required to evaluate whether the data support the stated claims.
minor comments (2)
  1. [Abstract] Abstract: Replace the vague phrase 'increased efficiency' with the concrete operationalization used in the study (e.g., 'reduced task completion time' or 'higher words-per-minute output').
  2. Figure captions and interface descriptions: Ensure that screenshots or diagrams of the three variants clearly label the presence/absence of the cursor and the timing of suggestion delivery so readers can visually verify the intended manipulations.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive and detailed feedback on our exploratory study. We address each major comment below, clarifying our approach and indicating planned revisions where appropriate.

read point-by-point responses

  1. Referee: [Methods] Methods, Study Design and Procedure sections: The manuscript must report quantitative metrics (e.g., suggestion frequency, average length, relevance scores, or generation latency) demonstrating that suggestion content and quality were statistically equivalent across the three editor variants. The skeptic concern is load-bearing because any systematic difference in backend prompting or caching between synchronous and asynchronous modes would provide an alternative explanation for the reported efficiency and misalignment effects, undermining attribution to the temporal dimension alone.

    Authors: We agree that equivalence of suggestion content is necessary to isolate the effects of the temporal and visual manipulations. All three variants were implemented with the identical backend model, prompt template, and generation parameters; the only differences were in the timing of when suggestions appeared to the user and whether a cursor visualization was shown. We did not collect post-hoc metrics on suggestion frequency, length, or relevance because the experimental focus was on interface factors rather than model output variation. In revision we will add an explicit Methods subsection describing the shared backend implementation and confirming that no condition-specific prompting or caching was used, thereby strengthening the attribution to the manipulated dimensions. revision: partial

  2. Referee: [Results] Results section: The abstract states directional effects (efficiency increase, misalignment, intent understanding, surveillance) without accompanying statistical details, effect sizes, or exclusion criteria. The full paper must include the exact analysis methods (quantitative tests, qualitative coding scheme, inter-rater reliability) and report whether the n=48 sample was powered or whether any participants were excluded, as these details are required to evaluate whether the data support the stated claims.

    Authors: The study is framed as exploratory, so we reported directional patterns supported by mixed-methods data rather than formal hypothesis tests. In the revised manuscript we will expand the Results section to include: the precise quantitative analysis procedures and any statistical tests applied (with effect sizes where computed); a full description of the qualitative coding scheme together with example codes; inter-rater reliability statistics; explicit confirmation that no participants were excluded; and a note that sample size was chosen to align with comparable prior HCI studies rather than an a-priori power calculation. These additions will increase transparency while remaining consistent with the exploratory design. revision: yes

Circularity Check

0 steps flagged

Empirical user study with no derivation chain or fitted predictions

full rationale

The paper reports results from a comparative user study (n=48) on three AI text editor variants. No equations, parameters, or derivations appear anywhere in the manuscript. Claims rest on direct participant observations and qualitative/quantitative measures from the experiment. No self-citations are used to justify uniqueness theorems or ansatzes, and no fitted inputs are relabeled as predictions. The design choices (synchronous vs asynchronous, cursor presence) are described as experimental manipulations without reducing to self-referential definitions. This is a standard empirical HCI study whose central claims do not reduce to their own inputs by construction.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

This is an empirical user study paper with no mathematical model, free parameters, axioms, or invented entities; all claims rest on the study design and participant reports.

pith-pipeline@v0.9.1-grok · 5693 in / 1001 out tokens · 31018 ms · 2026-06-30T12:06:56.649960+00:00 · methodology

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