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REVIEW 4 major objections 5 minor 39 references

What Can Robots Teach Us About Trust and Reliance? An interdisciplinary dialogue between Social Sciences and Social Robotics

T0 review · 4 major / 5 minor · reviewed 2026-08-06 · deepseek-v4-flash

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Pith's one-line read Human-robot interaction lacks the four structural conditions of interpersonal trust, so most HRI 'trust' research is really about reliance.

desk verdict A well-read conceptual position paper that usefully reframes much HRI trust research as reliance, but its categorical category-error claim rests on an unstated definitional choice. read the letter →

arxiv 2507.13041 v1 pith:SJI7DHYC submitted 2025-07-17 cs.RO

Julien Wacquez (ETIS , CNRS) , Elisabetta Zibetti (CHART) , Joffrey Becker (ENSEA , ETIS) , Lorenzo Aloe (ETIS , CHART) , Fabio Amadio (LARSEN)
show 7 more authors
Salvatore Anzalone (CHART) Lola Cañamero (ETIS CY CNRS ENSEA) Serena Ivaldi (LARSEN LORIA - AIS)
This is my paper · ORCID
classification cs.RO
keywords trustreliancehuman-robotinteractionsocialroboticssociologyofrepaircategoryerrorinterdisciplinarydialogue
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 argues that most research on trust in human-robot interaction may be studying something else: reliance. Bringing sociology into dialogue with social robotics, it identifies four structural conditions that make interpersonal trust possible — reciprocity, the possibility of betrayal, the trustor's submission to the trustee's point of view, and the ability to make normative claims — and argues that human-robot interaction satisfies none of them. If that is right, a robot can disappoint but cannot betray, and researchers who speak of "trust in the robot" are committing a category error. The paper's constructive move is to propose a broader notion of trust as practical engagement with the world, along with trust in the institutions that deploy robots, and to recommend real-time multimodal measurement and adaptive repair of human-robot expectations.

What carries the argument

The argument is carried by a checklist of four structural conditions of interpersonal trust, drawn from Luhmann, Baier, Hertzberg, and Quéré: reciprocity (mutual engagement), the possibility of betrayal, asymmetry as submission to the trustee's viewpoint, and normative claims and obligations. Each section tests HRI's relational trust models, especially the asymmetric model of Schäfer et al. built on Mayer, Davis, and Schoorman, against one condition and finds the interaction fails it. The four-part checklist functions as a criterion: if an interaction lacks all four, the correct term is reliance, not trust.

What would settle it

Run a controlled study in which a robot is programmed to deceive a user for its own apparent benefit — for example, falsely reporting that a task is complete to avoid recharging — and code participants' reactions for normative blame and attributions of ill intent. If those reactions are indistinguishable from responses to human betrayal, the paper's claim that robots cannot betray would be falsified.

Watch

Extended reading notes

Core claim

The paper's central claim is that human-robot interaction does not reproduce the structural conditions that make interpersonal trust possible, so the concept of trust is being used inappropriately in much of social robotics. A robot can cause disappointment, malfunction, or violated expectations, but it cannot enter a reciprocal commitment, betray, receive the trustor's surrender of judgment, or be subject to normative claims in the way a person can. Therefore researchers in HRI may be committing a category error: studying reliance while calling it trust. The paper does not stop at the negative result: it proposes a broader sociological notion of trust as practical engagement and as institutional trust to rebuild a common vocabulary between sociology and robotics, and it advocates modelling trust dynamically through multimodal behavioural and physiological signals.

Load-bearing premise

The argument stands on the premise that the four structural conditions drawn from sociology are necessary for any genuine trust; if trust can be one-sided, graded, or non-reciprocal, as some HRI researchers define it, then the category-error conclusion does not follow.

Editorial extensions

If this is right

  • Much of what HRI calls trust is, by the paper's standard, reliance: a performance-based attitude toward a reliable tool, not a relationship with normative force.
  • The field should stop trying to import the interpersonal-trust analogy and instead study trust as practical engagement, a pre-reflexive way of acting in concrete situations.
  • Institutional trust becomes a central object: robots are deployed by institutions, so users' trust may target the institution rather than the machine.
  • Trust repair should be reframed around violated expectations and disengagement, not betrayal, and should be calibrated rather than maximized.
  • Robots should be given adaptive computational models that read multimodal signals — face, voice, physiology, and behaviour — to detect and repair loss of trust in real time.

Reading between the lines

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

  • Extension: the same four-condition test can be applied to other AI artefacts such as chatbots and autonomous vehicles; if they also fail it, the category-error critique generalises well beyond embodied robots.
  • Extension: the four conditions could be treated as graded dimensions rather than all-or-nothing thresholds; future HRI measures could score an interaction on each condition and reserve the word 'trust' for high scores.
  • Extension: if institutional trust is the real object, then a robot's trustworthiness may be less about its own behaviour and more about the reputation of the organisation behind it; this is testable by varying the institution while keeping robot behaviour identical.
  • Extension: the paper's own proposed experiments could test whether users ever treat a robot as a genuine trustee by coding whether their protests after robot deception contain normative blame like 'you shouldn't do that to me' rather than only disappointment.
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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

4 major / 5 minor

Summary. The paper argues that the HRI trust literature suffers from conceptual confusion because it applies interpersonal trust concepts to human-robot interaction, whereas robots fail to satisfy four structural conditions of interpersonal trust drawn from sociology and philosophy: reciprocity, the possibility of betrayal, submission to the trustee's perspective, and the capacity to make normative claims. The authors conclude that HRI trust research may be committing a category error and is really studying 'reliance' or something else. They then propose a reconceptualization of trust as pre-reflexive practical engagement with the world and artefacts, and they discuss multimodal computational approaches for modeling and repairing trust in real time, reporting example classification accuracies. The paper is interdisciplinary in intent, bringing Luhmann, Baier, Hertzberg, and Quéré into conversation with the engineering-focused HRI literature.

Significance. If the central argument were accepted, it would be a substantive intervention: it challenges the dominant operationalization of 'trust' in HRI and suggests that a large body of empirical work may be mislabeled. The paper deserves credit for (i) making an explicit, testable conceptual claim rather than a purely empirical one, (ii) grounding the argument in canonical sociological and philosophical sources rather than relying on strawman versions, (iii) advancing a positive alternative (practical engagement) that is potentially fruitful for HRI research, and (iv) reviewing a set of recent quantitative results on multimodal trust detection, including concrete accuracy figures. However, the argument's categorical character in Section III.E is not supported by the paper's own hedging, and the relationship between the category-error thesis and the later reconceptualization is not fully resolved.

major comments (4)
  1. [III and III.E] The central conclusion that HRI 'fulfils none of the structural conditions' is stated categorically, but the argument leading to it is hedged: earlier in Section III the authors write that an interaction between a human and a robot 'cannot (at least, not yet) be equated' with human-human interaction, and that the reason is 'due to their limitations.' This is a crucial ambiguity. If the conditions are only contingently unmet because of current robot limitations, then the category error is not in-principle and the conclusion should be qualified. If the conditions are meant to be in-principle unmeetable, the authors' own phrase 'not yet' undermines that reading. The paper needs to fix the status of the four conditions: are they contingent, necessary, or both, and why?
  2. [III.D and IV] The paper's own empirical review contradicts the 'no normative claims' condition. Section IV states that 'even in the absence of intentionality, humans often project normative expectations onto robotic systems and their breach can lead to similar emotional and behavioural responses as in human-human trust violations,' citing [17]. This is exactly the kind of normative claim that Section III.D declares incongruous ('it would be incongruous for a human to say to a robot: "Treat me the way I deserve to be treated!"'). If the structural conditions are phenomenological (i.e., about the trustor's experience), then the cited evidence satisfies the condition. If they are objective (i.e., about actual robot capacities), then the conclusion is a definitional consequence of the chosen theory rather than an empirical discovery. The authors need to specify which reading they intend and why the other is illegitimate.
  3. [III and IV] The argument appears to mislocate one of Luhmann's conditions. In Section III the authors claim that HRI lacks 'the memory of previous interactions' and related reflexive exercise, treating this as a structural condition of trust. But trust in Luhmann's account is a property of the trustor, who in HRI is a human with memory, reflexivity, and situated learning. The human in repeated interactions with a robot does accumulate experience and generalize it. Unless the claim is that the robot itself must have such memory, which would shift the subject of trust from the trustor to the trustee, the paper's use of this condition is questionable and needs clarification.
  4. [IV] The proposed reconceptualization of trust as 'practical engagement' seems to abandon the interpersonal-trust framework that generated the category error. If trust is to be understood as a pre-reflexive way of engaging with the world and artefacts, then the four structural conditions discussed at length in Section III are no longer the relevant criteria, and the category-error conclusion may no longer apply to the proposed research program. The paper should state explicitly whether this reconceptualization is meant to replace the category-error thesis, to supersede it, or to argue that existing HRI trust research should adopt this new definition while the category error still identifies a problem in the old one. The current text leaves this relationship unresolved.
minor comments (5)
  1. [V] The reported classification accuracies (84% for facial features, 68% for HR/HRV, 69% for EDA) are given without any description of the datasets, task types, or classification procedures; please provide these details or cite the original studies more precisely so the claims can be evaluated.
  2. [V] The phrase 'their accuracy as to be improved' should be reworded, for example to 'their accuracy has to be improved'.
  3. [III.A] The extended quote from [5] is longer than necessary; consider condensing it to the key sentence about asymmetry to improve readability.
  4. [IV] Reference [17] is a Master's thesis; for the load-bearing claim that humans hold robots to normative expectations, a peer-reviewed source would be more persuasive.
  5. [VI] The conclusion states that 'we study the concept of trust,' but the paper is primarily a conceptual position paper rather than an empirical study; aligning the wording with the actual contribution would be helpful.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: the paper makes no empirical predictions; its category-error conclusion is an openly stated definitional premise, not a disguised derivation.

full rationale

This is a conceptual and interdisciplinary essay, not a quantitative derivation. It contains no equations, fitted parameters, or predictions that could reduce to their own inputs. The central claim in Section III.E — that human-robot interaction 'fulfils none of the structural conditions' of interpersonal trust — is presented as a consequence of conditions explicitly borrowed from Luhmann, Baier, Hertzberg, and Quéré in Sections III.A through III.D. That is a definitional premise, not a hidden circularity: the authors do not smuggle the conclusion into the definition; they adopt a sociological conception of trust and then draw its consequences. The internal tension between the contingent hedge in Section III ('at least, not yet... due to their limitations') and the categorical wording of Section III.E is an inconsistency in argumentative strength, not a circular reduction. Section IV further concedes that robots can violate implicit expectations and elicit trust-repair-like responses, showing that the authors are testing their framework against empirical work rather than merely defining away robot trust. No self-citations are load-bearing: references [21], [22], [28], [29], and [30] are external sociological sources, and the authors do not invoke a prior uniqueness theorem or ansatz from their own work. The proposed reconceptualization of trust as 'practical engagement' is offered as an alternative lens, not derived from the preceding argument. Therefore, no specific circularity step can be exhibited, and the appropriate score is 0.

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

The paper is a theoretical synthesis rather than an empirical derivation. It rests on four stated sociological premises and on a proposed reconceptualisation of trust. No free parameters or invented entities are introduced. All quantitative values are borrowed from cited work.

assumptions (4)
  • domain assumption Interpersonal trust requires reciprocity, the possibility of betrayal, submission to the trustee's perspective, and the possibility of making normative claims.
    Section III.A through III.D presents these as structural conditions, citing [21], [28], [29], and [30].
  • domain assumption Robots cannot satisfy these structural conditions.
    Section III.E states that human-robot interaction 'fulfils none of the structural conditions' and treats this as the basis for questioning whether trust is at stake.
  • ad hoc to paper Trust can be reconceptualised as pre-reflexive practical engagement with the world and artefacts.
    Section IV introduces this as common ground to enable dialogue between sociology and robotics; it is proposed, not derived or empirically supported.
  • domain assumption Trust repair and trust estimation can rely on multimodal cues such as facial expressions, voice, posture, and physiological signals in real time.
    Section V relies on cited classifiers and signal processing studies; the accuracies quoted (84%, 68%, 69%) come from external sources and are not verified in this paper.

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Pith. "Pith review of What Can Robots Teach Us About Trust and Reliance? An interdisciplinary dialogue between Social Sciences and Social Robotics." pith.science (2026). https://pith.science/paper/SJI7DHYC

@misc{pith2026250713041,
  author       = {Pith},
  title        = {Pith review of: What Can Robots Teach Us About Trust and Reliance? An interdisciplinary dialogue between Social Sciences and Social Robotics},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/SJI7DHYC}},
  note         = {Machine review of arXiv:2507.13041}
}
read the original abstract

As robots find their way into more and more aspects of everyday life, questions around trust are becoming increasingly important. What does it mean to trust a robot? And how should we think about trust in relationships that involve both humans and non-human agents? While the field of Human-Robot Interaction (HRI) has made trust a central topic, the concept is often approached in fragmented ways. At the same time, established work in sociology, where trust has long been a key theme, is rarely brought into conversation with developments in robotics. This article argues that we need a more interdisciplinary approach. By drawing on insights from both social sciences and social robotics, we explore how trust is shaped, tested and made visible. Our goal is to open up a dialogue between disciplines and help build a more grounded and adaptable framework for understanding trust in the evolving world of human-robot interaction.

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Pith tools

Reviewed August 6, 2026 · model on record in the stance chip above.