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REVIEW 4 major objections 4 minor 160 references

Humans Coexist, So Must Embodied Artificial Agents

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

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Pith's one-line read The paper argues that embodied AI agents must be designed to coexist with humans through meaningful reciprocal interaction, not merely to perform tasks.

desk verdict Useful design orientation, but the 'prerequisite' claim is overreach and the formal definition rests on an unoperationalized counterfactual quality function. read the letter →

arxiv 2502.04809 v3 pith:NBKRHZNR submitted 2025-02-07 cs.LG

Hannah Kuehn , Joseph La Delfa , Miguel Vasco , Danica Kragic , Iolanda Leite This is my paper · ORCID
classification cs.LG
keywords embodiedartificialagentscoexistencelong-termhuman-robotinteractionsituatednessmutabilityopen-endednessresearchthroughdesignhuman-in-the-looplearning
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 current embodied artificial agents are built to exist, not to coexist: trained on static datasets and then deployed, they cannot meaningfully adapt to the humans and environments they live with. It proposes a formal definition of coexistence as sustained, meaningful, reciprocal interaction that, over a system-dependent horizon, improves the quality of the human-agent-environment system compared with the agent's absence. The paper claims coexistence is a prerequisite for long-term in-the-wild interaction, and that the dominant train-then-deploy paradigm is therefore fundamentally unsuited for it. Drawing on biology and design theory, it offers six research directions organized around mutability, situatedness, and treating the user as a co-designer. A sympathetic reader would care because accepting the claim would reorient robotics and embodied AI evaluation from task performance to long-term systemic co-shaping.

What carries the argument

The load-bearing mechanism is the formal definition of coexistence built around the quality function $Q_O(t)$ and the counterfactual comparison in Eqs. (3)-(4). The paper distinguishes unilateral interaction $X_t \to Y_t$ (one party's next state depends on the other's, but not vice versa) from reciprocal interaction $X_t \leftrightarrow Y_t$ (mutual dependence), and defines meaningful interaction as one that, for all observers $O$ and all times beyond a system-dependent horizon $T_S$, leaves quality no lower than no interaction: $Q_O(t' \mid X_t \to Y_t) \geq Q_O(t' \mid \emptyset)$. A coexisting agent $A^*$ is one that maintains reciprocal, meaningful interactions with the human and environment, formalized in Eq. (4). The two properties, situatedness (Eq. 5) and mutability (Eq. 6), are direct conditions on this quality comparison and carry the argument from definition to design prescription.

What would settle it

Run a matched long-term field study in which a home robot that the paper would classify as coexisting is removed for a period longer than the system's horizon $T_S$ while other conditions are held constant, and measure a proxy quality metric (voluntary user-initiated interactions, task fluency, or self-reported trust) before and during removal; if the metric does not fall after removal, the defining inequality $Q_O(t' \mid A^*) \geq Q_O(t' \mid \emptyset)$ is violated for that agent.

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Extended reading notes

Core claim

The paper's central claim is that an embodied artificial agent coexists in a system only if it sustains meaningful and reciprocal interactions with humans and their environment over time. Formally, a system $S = \{A, H, E\}$ has a quality function $Q_O(t)$ evaluated by every observer $O$; a unilateral interaction changes only one party's future state, while a reciprocal interaction changes both. A meaningful interaction is one whose long-term quality, after a horizon $T_S$, is no worse than if the interaction had not occurred, and a coexisting agent is one whose reciprocal presence is at least as good for the system as its absence. From this the paper derives two properties: situatedness (the agent should improve its own specific system even if the same behavior would harm another) and mutability (the agent and human should mutually shape each other). The paper argues that this definition, if adopted, makes the current stagnant and generic design of embodied agents incompatible with long-term human interaction.

Load-bearing premise

Every definition in the paper rests on there being a quality function $Q_O$ that every observer in the system can evaluate and compare against a counterfactual world in which the agent's interactions never happened; if that comparison cannot be made, whether an agent coexists becomes unverifiable.

Editorial extensions

If this is right

  • Long-term in-the-wild deployment of an embodied agent should be treated as a coexistence problem, not a task-completion problem; evaluation should ask whether the human-agent-environment system is better off with the agent than without it.
  • Agents will need to be mutable: their behavior, objectives, and even morphology should change through reciprocal interaction with the specific human and environment they live in.
  • Situatedness will matter more than generic pretraining: an agent should be evaluated by how much it improves its own system, even if the same behavior would hurt a different household or workplace.
  • Current learning paradigms (offline pretraining, meta-learning, continual learning, standard reinforcement learning) are insufficient on their own, because they assume a predefined distribution of novelty; the paper argues for open-ended, human-in-the-loop evolutionary learning instead.
  • Foundation models should be used as external stores of generic knowledge to bootstrap situated behavior, not as the agent's internal policy, to avoid freezing generic and stagnant behavior into the system.

Reading between the lines

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

  • The counterfactual in the definition suggests a concrete evaluation protocol the paper does not spell out: measure proxy quality metrics (trust, voluntary interaction frequency, task fluency) with the agent present, then again after a removal period exceeding $T_S$; the definition turns coexistence into an empirical, falsifiable property rather than a metaphor.
  • If steamrolling is real, the recursive-data-degradation results cited by the paper imply a technical stability argument for coexistence: a homogeneous fleet of stagnant agents would shrink the distribution of human behavior, degrading future models trained on that behavior, so coexistence would be not only an ethical preference but a way to keep the data ecology healthy.
  • The open-system extension in Appendix B suggests coexistence naturally scales beyond a single human and robot to families, teams, and institutions, making the paper's call for ethical and legal frameworks more pressing because the observers who judge quality may not be the same as those who are shaped by the agent.
  • A testable extension would be matched long-term deployments of a static optimized agent and a mutable co-shaping agent in similar households, comparing voluntary interaction frequency and user-reported quality after the novelty period; the paper predicts the co-shaping agent retains or grows quality while the static one decays.
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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 / 4 minor

Summary. This position paper argues that current embodied artificial agents are 'stagnant' and 'generic' because their knowledge is fixed at deployment and drawn from large pre-collected datasets, and that their widespread deployment will therefore 'steamroll' human cultural and behavioral diversity. The authors propose a new property, coexistence, defined as sustained meaningful and reciprocal interactions between an agent, a human user, and the environment, and claim that coexistence is a prerequisite for long-term, in-the-wild human-agent interaction. The paper formalizes this definition in Section 3, draws parallels from developmental biology and research-through-design, and proposes six research directions centered on open-endedness, user-as-designer, morphology, and human-in-the-loop evolution. Appendices discuss scope, measurement proxies, and limitations.

Significance. If the necessity claim were established, the paper would challenge the dominant train-then-deploy paradigm and reframe embodied-agent design around mutual adaptation and situatedness. The manuscript's strengths are its interdisciplinary synthesis of biology, design theory, and long-term HRI, and the concreteness of several proposed directions, especially treating foundation models as external components and involving users in shaping morphology and sensing. The paper is also candid in its appendices about the open problems in measuring its central quantity. However, the central claim is not currently supported: it is either contradicted by the paper's own examples or reduced to a definitional circularity, and the formal apparatus in Section 3 cannot carry the evidential weight placed on it. The paper would be more defensible as a design manifesto or a set of research hypotheses than as an established prerequisite.

major comments (4)
  1. [Abstract and Section 3 vs. Appendix A] The abstract and Section 3 assert that coexistence is 'a prerequisite for long-term, in-the-wild interaction with humans.' Appendix A, however, cites Sung et al. [130] and Fink et al. [38] as documenting households that use robot vacuum cleaners daily over months, with users rearranging furniture, installing threshold ramps, and changing tidying routines, and then states that these effects 'do not, by themselves, constitute coexistence, but only entanglement.' Under the paper's own criteria, these are long-term, in-the-wild interactions with stagnant, generic agents, which directly contradicts the necessity claim. If the authors reply that these are not 'interactions' in the intended sense, the claim becomes true only by definition, since 'interaction' has been narrowed to mean coexisting interaction; either way, the substantive empirical assertion is lost. The manuscript should either weaken the claim to a design preference or testable hypothesis, or provide an independent characterization of interaction that excludes these cases and explains why that narrower notion is the relevant one.
  2. [Section 3, Eqs. (3)-(4); Appendices B-C] Equation (3) defines meaningful interaction by comparing Q_O(t' | X_t → Y_t) with Q_O(t' | ∅), where ∅ denotes the absence of interaction. This counterfactual baseline is never defined: there is no specification of how Q_O is evaluated under a counterfactual in which a past interaction did not occur, nor how Q_O is measured and compared across different observers O. Appendix B states that credit assignment is 'an open research problem,' and Appendix C concedes that 'measuring precisely how a user may change as a result of an interaction can be intractable.' Since Eq. (4) inherits these quantities, the formal definition cannot, as it stands, support the claim that coexistence is a prerequisite. In addition, in Eq. (4) the counterfactual term Q_O(t' | H_t ↔ E_t) is evaluated for O = A*, but A* is absent in that counterfactual, so the quantity is undefined for that observer. The authors need to specify an operational or at least well-defined evaluation procedure, or explicitly treat the formalism as illustrative rather than as evidence for the necessity claim.
  3. [Section 3, Definition of coexistence] There is a definitional circularity in the central claim. Section 3 defines a coexisting agent as one that 'maintain(s) reciprocal and meaningful interactions in the long-term' (Eq. 4), and the abstract then concludes that coexistence is required for long-term, in-the-wild interaction. This makes the conclusion close to analytic: the only interactions counted in the conclusion are those already defined as coexistence. The vacuum-cleaner examples in Appendix A show that the paper needs an independent notion of 'interaction' to make the claim substantive. The authors should either state which observable behaviors count as interaction independently of the Q_O criterion, or explicitly restrict the claim to 'meaningful and reciprocal interaction' and provide an independent justification for why that restricted class is the one that matters for the field's goals.
  4. [Section 2.3, Steamrolling] Section 2.3 argues that stagnant, generic agents 'will steamroll' human cultures and workflows, and this alleged harm is part of the argument that coexistence is necessary. The supporting evidence is analogical: LLM-style abstracts [44], reduced diversity in LLM-assisted brainstorming [94], and model collapse on recursively generated data [126]. None of these involve embodied agents or long-term human-robot interaction, and the paper acknowledges that direct empirical evidence is limited. Because steamrolling is load-bearing for the normative conclusion, the authors should either present direct empirical evidence from embodied deployments, or explicitly frame steamrolling as an untested risk and derive the recommendation from that weaker, hypothesis-like premise.
minor comments (4)
  1. [Section 5, direction 4] In the sentence describing the drone study, 'based on its the shape and size' should read 'based on the shape and size.'
  2. [Appendix D] In the 'Please, just turn on the light' paragraph, 'we are argue that such situated interactions' should read 'we argue that such situated interactions.'
  3. [References [72] and [73]] References [72] and [73] are identical duplicate entries for Krogh, Markussen, and Bang; one should be removed or the two should be differentiated by content.
  4. [Acknowledgments] The acknowledgments state 'the Swedish Research Council Swedish Research Council'; the duplicate phrase should be removed.

Circularity Check

1 steps flagged · score 6.0 of 10

The headline 'prerequisite' claim reduces to the paper's own definition; the supporting examples are independent, but the central necessity claim is not derived.

  1. self definitional [Abstract and Section 3 (Definition, Eqs. 1-4); see also Section 7 Conclusion]
    "Abstract: 'This paper introduces the concept of coexistence for embodied artificial agents and argues that it is a prerequisite for long-term, in-the-wild interaction with humans.' Section 3: 'An embodied artificial agent is coexisting in a system if it sustains meaningful and reciprocal interactions with humans and their environment over time.' Section 7: 'We proposed coexistence as a new paradigm for the design of embodied agents that emphasizes meaningful, reciprocal interactions sustained over time.'"

    Coexistence is defined as sustaining meaningful and reciprocal interactions over time. The central thesis then asserts that coexistence is a prerequisite for long-term, in-the-wild interaction with humans. Read as the same notion, the thesis is true by stipulation: long-term interaction is said to require meaningful, reciprocal, sustained interaction, which is exactly what 'coexistence' was defined to mean. The formal inequality in Eq. 4 restates this condition as QO(t' | A*<->(H,E), H<->E) >= QO(t' | H<->E) without operationalizing QO or the counterfactual baseline; Appendices B and C concede that credit assignment is open and that measuring how a user changes can be intractable.

full rationale

The paper is a position paper, not an empirical derivation, and most of its content is independent of the formal apparatus: the biology and design-theory discussions in Section 4 and the six research directions in Section 5 stand on their own as a design proposal. There is no fitted parameter renamed as a prediction, no imported uniqueness theorem, and the self-citations (e.g., La Delfa et al. [77,78], Leite et al. [84,85]) are used as illustrative examples rather than as load-bearing proofs. The circularity is concentrated in the headline necessity claim: because 'coexistence' is defined as sustaining meaningful and reciprocal interactions over time, the assertion that coexistence is a prerequisite for long-term in-the-wild interaction reduces to the definition if 'interaction' is read narrowly, and it is contradicted by the paper's own vacuum-cleaner examples if read broadly. The formal definition's QO and counterfactual baseline are acknowledged in Appendices B and C to be unoperationalized, so they do not supply independent content. This partial definitional circularity affects the central claim, but the rest of the paper retains independent value, yielding a score of 6.

Assumptions & free parameters 0 free parameters · 6 assumptions · 0 invented entities

The paper introduces no numerical fitted parameters; the time horizon T_S and quality function Q_O are symbolic placeholders rather than fitted constants. The central argument rests on several unproven empirical and philosophical premises about human-robot interaction, system quality measurement, and the transferability of biological and design analogies.

assumptions (6)
  • domain assumption In-the-wild interaction is co-constructed with humans, so it cannot be treated as a static optimization problem.
    Invoked in Section 1 citing Frauenberger [42]; this premise motivates the need for reciprocal, co-constructed interaction.
  • domain assumption Current embodied agents are stagnant and generic because their knowledge is fixed at training time and derived from large pre-collected datasets.
    Section 2.1 and 2.2 state this as the problem; it is not established by a survey or field study.
  • domain assumption Steamrolling, the convergence of human culture and workflows toward homogeneous agent-dictated behavior, will occur for embodied agents.
    Section 2.3 supports this only with analogies from LLM-style writing and brainstorming diversity.
  • ad hoc to paper A quality function Q_O can be defined, measured, and compared across observers and under counterfactual absence of interaction.
    Section 3, Eq. 3; the definition of meaningful interaction depends on Q(t'|∅), which Appendices B and C admit is not operationalized.
  • domain assumption Analogies from biology (genetic drift, HSP90, digit patterning) and design (double diamond, research through design) transfer to artificial agents.
    Section 4 uses these to justify mutability and situatedness in artificial agents; no mechanism ensures transferability.
  • domain assumption Human goals and preferences are formed through interaction with the agent rather than known a priori.
    Section 6 argues against unidirectional alignment; this is a philosophical claim without empirical support.

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Cite this review

Pith. "Pith review of Humans Coexist, So Must Embodied Artificial Agents." pith.science (2026). https://pith.science/paper/NBKRHZNR

@misc{pith2026250204809,
  author       = {Pith},
  title        = {Pith review of: Humans Coexist, So Must Embodied Artificial Agents},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/NBKRHZNR}},
  note         = {Machine review of arXiv:2502.04809}
}
read the original abstract

This paper introduces the concept of coexistence for embodied artificial agents and argues that it is a prerequisite for long-term, in-the-wild interaction with humans. Contemporary embodied artificial agents excel in static, predefined tasks but fall short in dynamic and long-term interactions with humans. On the other hand, humans can adapt and evolve continuously, exploiting the situated knowledge embedded in their environment and other agents, thus contributing to meaningful interactions. We take an interdisciplinary approach at different levels of organization, drawing from biology and design theory, to understand how human and non-human organisms foster entities that coexist within their specific environments. Finally, we propose key research directions for the artificial intelligence community to develop coexisting embodied agents, focusing on the principles, hardware and learning methods responsible for shaping them.

Figures

Figures reproduced from arXiv: 2502.04809 by the authors.

Figure 1
Figure 1. Embodied artificial agents must coexist. Current agents exist in the real-world, leveraging knowledge obtained from large-scale datasets and specific expert-level datasets to interact. We argue that embodied artificial agents must not only adapt to scenarios such as the ones pictured above but participate in their continual evolution. To do so, they must coexist, establishing meaningful and reciprocal relationships … view at source ↗
Figure 2
Figure 2. The evolution of coexisting embodied agents: a) The double diamond process, with its distinct problem/solution-focused beginning and end; b) Removing the head and tail off the double diamond reveals a continuous and reflective engagement with technology as demonstrated by the field of research through design; c) Revisiting [PITH_FULL_IMAGE:figures/full_fig_p007_2.png] view at source ↗
Figure 3
Figure 3. Fink et al. [38] and Sung et al. [130] highlight the various ways users modify their behaviors and living spaces to integrate autonomous robot vacuum cleaners into daily life. A Additional Notes on Coexistence Interaction with humans in coexistence When discussing coexistence, one might ask about embodied agents that are not directly interacting with humans. Does coexistence apply to them as well? Why would an embod… view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: Self recovering locomoting voxels [71]: by virtue of an evolutionary algorithm, the agent is relearning how to walk by changing the inflation patterns of its individual cells. Each change to the physical body is likened to a divergent search for a new and unique locomo…
Figure 5
Figure 5. Figure 5: Yamaha’s “MOTOROiD” is a shape changing, self-balancing motorcycle [ [PITH_FULL_IMAGE:figures/full_fig_p025_5.png]
Figure 6
Figure 6. Figure 6: “How to Train Your Drone” [78]: depicted here in orange, clear and blue are the sensory fields of the drones. By interacting with the drone, its sensory field can be changed with human intention. However the consequences of such changes are not always predictable. This…
Figure 7
Figure 7. Figure 7: “Blo-Nut” is a silicone doughnut that affords the user a blank slate to interact with [ [PITH_FULL_IMAGE:figures/full_fig_p026_7.png]

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Pith tools

Reviewed August 8, 2026 · model on record in the stance chip above.