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A Scoping Review of the Ethical Perspectives on Anthropomorphising Large Language Model-Based Conversational Agents

T0 review · 1 major / 6 minor · reviewed 2026-08-03 · deepseek-v4-flash

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Pith's one-line read A review of 22 ethically oriented studies finds that the field agrees on attribution-based definitions of anthropomorphism but lacks shared operationalization, is risk-forward, and has a thin empirical-to-normative bridge.

desk verdict A transparent, well-run scoping review whose mapping and research agenda are genuinely useful, though the headline empirical-governance gap is partially an artifact of its own inclusion criteria. read the letter →

arxiv 2601.09869 v2 pith:HP4U3VDE submitted 2026-01-14 cs.AI cs.HC

Andrea Ferrario , Rasita Vinay , Matteo Casserini , Alessandro Facchini This is my paper · ORCID
classification cs.AIcs.HC
keywords anthropomorphismconversationalagentslargelanguagemodelsAIethicsscopingreviewdeceptiontrustgovernance
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

This paper is a scoping review of 22 ethically oriented studies on anthropomorphizing large language model-based conversational agents, published in the LLM era (2021–2025). It tries to establish that the field has converged on attribution-based definitions of anthropomorphism but diverges sharply in how it operationalizes the concept, is dominated by risk-focused normative analyses, and rarely connects observed interaction effects to concrete governance actions. The authors argue that this fragmented state leaves design and policy recommendations under-specified. For a reader, the review matters because it identifies what would need to be true—shared definitions, validated measures, longitudinal evidence—before responsible anthropomorphic design can be operationalized.

What carries the argument

The analytical engine is the distinction between anthropomorphisation as a psychological attribution and anthropomorphic cues as manipulable design features, together with a three-dimensional taxonomy of attributions (cognitive/epistemic, affective, behavioural/social). This taxonomy organizes the corpus into three risk pathways—epistemic expertise/authority, empathy/care, and relational/normative role attributions—and connects them to normative stakes such as autonomy, dignity, justice, and privacy. The review uses this machinery to diagnose the missing 'empirical-to-normative bridge': observed effects like trust shifts or over-disclosure are rarely tied to testable governance actions such

What would settle it

A reader could audit the 111 excluded full-text records or run a parallel search without the ethics keyword block to check whether a substantial share of empirical studies report anthropomorphic effects plus design recommendations without ever using words like 'ethics' or 'moral.' If such studies exist in numbers, the claim that governance guidance is not empirically grounded would need revision.

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Extended reading notes

Core claim

Across the included corpus, anthropomorphisation is most often defined as the attribution of human-like mental states or social qualities to non-human systems, while anthropomorphic cues are treated as design features that invite such attributions. The review finds three recurring attribution dimensions—cognitive/epistemic, affective, and behavioural/social—and three pathways through which risks arise: attributions of expertise and authority, attributions of care and empathy, and relational/normative attributions such as friend or partner role-play. Ethically, the literature is primarily risk-forward, centering on deception, overreliance, and dependency, with benefits treated as context-depe

Load-bearing premise

The load-bearing assumption is that screening out studies without explicit normative framing does not systematically miss empirical work that links anthropomorphic effects to governance guidance; if it does, the review's headline gap is an artifact of the search.

Editorial extensions

If this is right

  • If the review's synthesis is correct, future work cannot simply add more ethical warnings; it first needs a shared operationalization of anthropomorphism and validated instruments.
  • Governance recommendations—AI-identity disclosure, de-anthropomorphising, sandboxing—need to be turned into testable hypotheses with defined outcome metrics.
  • Ethical permissibility is use-case dependent; low-stakes humanization may be tolerable while simulating complex capacities like empathy or authority is riskier.
  • Longitudinal and interaction-level studies are needed to capture cumulative effects such as reliance trajectories, dependency, and norm displacement.
  • Regulatory frameworks should be lifecycle-sensitive, without assuming anthropomorphisation alone constitutes a high-risk feature.

Reading between the lines

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

  • Editorial inference: Because the search required explicit normative framing in titles or abstracts, empirical HCI studies that measure anthropomorphic effects without using ethical keywords may have been systematically excluded; including them could narrow or widen the reported 'empirical-to-normative' gap.
  • Editorial inference: The review's implied hierarchy—simple usability cues ethically lighter than virtue-laden role simulation—suggests a concrete design rule: regulators could tier requirements by the complexity of the human capacity being simulated.
  • Editorial inference: The convergence on attribution-based definitions invites a measurement program that adapts existing psychological anthropomorphism scales to LLM interaction, which would directly test the review's claim that operationalization is fragmented.
  • Editorial inference: If the field matures along the suggested lines, one testable extension is a benchmark that evaluates whether de-anthropomorphising interventions actually reduce overreliance and disclosure without reducing usability.
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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

1 major / 6 minor

Summary. The manuscript is a PRISMA-ScR scoping review of ethically oriented research on anthropomorphisation of LLM-based conversational agents published 2021–2025. From 910 records, 22 studies were retained after screening and charted for conceptual definitions, ethical challenges/opportunities, and methodological approaches. The review reports convergence on attribution-based definitions, divergence in operationalization, a predominantly risk-focused normative framing, and limited empirical work connecting observed interaction effects to actionable governance guidance. It closes with design and governance recommendations for future research.

Significance. If accepted, the review provides a useful consolidated map of a fragmented and fast-growing area. Its strengths include a preregistered protocol, transparent database-specific search strings, dual full-text screening with reported inter-rater reliability, and a clear distinction between anthropomorphism as attribution and anthropomorphic cues as design features. The proposed taxonomy of epistemic, affective, and social/relational pathways is a conceptually helpful organizing device. The inclusion of the authors' own study [26] is disclosed and does not appear to structurally determine the synthesis. The paper's main contribution is its governance-oriented synthesis, which identifies the missing empirical-to-normative bridge as a key gap.

major comments (1)
  1. [Abstract and §4.3/Table 3] The Gate C eligibility rule and Table 3's requirement that empirical studies articulate a 'defensible empirical-to-normative bridge' exclude empirical studies that measure anthropomorphic effects without explicit normative framing. The Abstract's finding of 'limited empirical work that links observed interaction effects to actionable governance guidance' is therefore a finding about the explicitly ethics-oriented corpus, not about the broader empirical literature. Section 7 acknowledges the exclusion, but the Abstract wording overstates the result. Please rephrase the finding as limited within the ethically oriented literature, and note in §7 that a separate synthesis of non-ethically framed HCI/consumer empirical studies would be needed to determine whether the empirical base itself is thin or only its normative translation.
minor comments (6)
  1. [Table 1] The row for Dennett's intentional stance lists '[26, 44]' as the included studies citing it, but [44] is the primary source; the text (§5.2.1) correctly names [26,45]. Please correct the inconsistency.
  2. [Table 4] Manzini et al. is listed under year 2025, while reference [43] gives the 2024 AIES proceedings; please align the year and venue across the table and reference list.
  3. [§5.1] The disciplinary percentages sum to more than 100% (59% HCI, 32% social sciences, 23% philosophy, 18% ethics). State explicitly that the categories are not mutually exclusive.
  4. [Figure 4] The 'Frictional design and social transparency methods' entry cites [33,54], but [54] is not among the included studies; distinguish external supporting references from corpus references in the figure caption or legend.
  5. [§5.2.2] The sentence 'See Table 2 in [31] for more details' should be 'Table 2 of [31]' to avoid confusion with the review's own Table 2.
  6. [Abstract / §7] The convergence claim in the Abstract ('convergence on attribution-based definitions') should be qualified, given the finding in §5.2.1/Table 1 that 55% of the included manuscripts provide no explicit theoretical anchor; the convergence appears to hold for the subset of studies that offer a definition, which the paper's own Discussion already notes.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the scoping review's synthesis is not equivalent to its inclusion criteria, and the self-cited included study is not load-bearing.

full rationale

No significant circularity. The paper is a scoping review, not a derivation: the central synthesis is a thematic summary of 22 records selected by explicit PRISMA-ScR criteria. Gate C and Table 3 require explicit normative analysis and, for empirical studies, a defensible 'empirical-to-normative' bridge; the finding that such bridges are under-specified is a qualitative judgment about the included studies, not an identity between the inclusion rule and the conclusion. Section 7 openly acknowledges that the search may exclude adjacent empirical studies without explicit normative framing; this is a scope limitation, and it is weighed in the verdict, but it does not make the headline claim equivalent to the selection criterion. The authors' own paper [26] is included and cited, e.g., in Section 5.4.4, but it is one of 22 inputs and the recurring themes—attribution-based definitions, risk pathways, governance gaps—are corroborated by multiple independent sources such as [29,30,32,38,40,43,45,49]. The working definition of anthropomorphisation as attribution is a stated analytic lens, not a result smuggled in as a finding. No load-bearing step reduces to an input by construction.

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

The review's conclusions rest on methodological choices (search window, gate criteria, interpretive synthesis) rather than mathematical or empirical derivations. These choices are reasonable for a scoping review but are assumptions that shape the findings.

assumptions (4)
  • domain assumption The time window 2021–2025 captures the LLM era and pre-2021 conversational agents are irrelevant to the review's scope.
    Section 4.2 assumes that the rise of LLM-based CAs is after 2021 and that earlier chatbot research would not inform the ethical analysis of LLM-era systems.
  • domain assumption Explicit ethical framing (Gate C) is a necessary condition for a study to be ethically relevant.
    Section 4.3 excludes empirical studies that do not make normative claims explicit, which may omit relevant evidence, as the authors acknowledge in Section 7.
  • domain assumption The chosen search terms (anthropomorph*, personif*, humaniz*, etc.) and the 'technology' and 'ethics' blocks adequately capture the ethically oriented literature on anthropomorphisation.
    Section 4.2 describes the search design; the adequacy of these terms is an untested assumption about how the literature self-describes.
  • standard math PRISMA-ScR is an appropriate framework for a scoping review and does not require quality appraisal or effect-size pooling.
    Section 4.1 follows PRISMA-ScR [25]; this is a methodological standard for scoping reviews, not a mathematical axiom.

how reviews work

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Cite this review

Pith. "Pith review of A Scoping Review of the Ethical Perspectives on Anthropomorphising Large Language Model-Based Conversational Agents." pith.science (2026). https://pith.science/paper/HP4U3VDE

@misc{pith2026260109869,
  author       = {Pith},
  title        = {Pith review of: A Scoping Review of the Ethical Perspectives on Anthropomorphising Large Language Model-Based Conversational Agents},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/HP4U3VDE}},
  note         = {Machine review of arXiv:2601.09869}
}
read the original abstract

Anthropomorphisation -- the phenomenon whereby non-human entities are ascribed human-like qualities -- has become increasingly salient with the rise of large language model (LLM)-based conversational agents (CAs). Unlike earlier chatbots, LLM-based CAs routinely generate interactional and linguistic cues, such as first-person self-reference, epistemic and affective expressions that empirical work shows can increase engagement. On the other hand, anthropomorphisation raises ethical concerns, including deception, overreliance, and exploitative relationship framing, while some authors argue that anthropomorphic interaction may support autonomy, well-being, and inclusion. Despite increasing interest in the phenomenon, literature remains fragmented across domains and varies substantially in how it defines, operationalizes, and normatively evaluates anthropomorphisation. This scoping review maps ethically oriented work on anthropomorphising LLM-based CAs across five databases and three preprint repositories. We synthesize (1) conceptual foundations, (2) ethical challenges and opportunities, and (3) methodological approaches. We find convergence on attribution-based definitions but substantial divergence in operationalization, a predominantly risk-forward normative framing, and limited empirical work that links observed interaction effects to actionable governance guidance. We conclude with a research agenda and design/governance recommendations for ethically deploying anthropomorphic cues in LLM-based conversational agents.

Figures

Figures reproduced from arXiv: 2601.09869 by the authors.

Figure 1
Figure 1. High-level search string structured into four blocks. [PITH_FULL_IMAGE:figures/full_fig_p005_1.png] view at source ↗
Figure 2
Figure 2. PRISMA-ScR flow diagram of this scoping review. [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗
Figure 3
Figure 3. Answering RQ1. A scheme summarizing the conceptual foundations of anthropomorphisation from the [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figures from the paper (1 more)
Figure 4
Figure 4. Figure 4: Answering RQ3. Methods and strategies for anthropomorphisation governance across the deployment [PITH_FULL_IMAGE:figures/full_fig_p010_4.png]

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Reference graph

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Pith tools

Reviewed August 3, 2026 · model on record in the stance chip above.