ARXIV:2601.20487 · AI AND SOCIAL SCIENCES · SUBMITTED 02 APR · 02:30 UTC · FRESHNESS STALE

VerifiedSource: PDF linkedPartialPaperPack: 3 of 4 citation fields filledMissingMissing fields: authorsPartialProof: unverified proof status

Normative Equivalence in human-AI Cooperation: Behaviour, Not Identity, Drives Cooperation in Mixed-Agent Groups

arXiv

Study on human-AI cooperation norms in group settings indicating behaviour over identity as cooperation driver.

Blocked on Code›Score3.0Evidence unverified

Opportunity summary

Pain Study on human-AI cooperation norms in group settings indicating behaviour over identity as cooperation driver.

Evidence 0 refs | 0 sources | 17% coverage

Blocker Evidence unverified

Open Build Read PDF Signal Canvas Track

PROBLEM

Study on human-AI cooperation norms in group settings indicating behaviour over identity as cooperation driver. While previous studies on human-AI cooperation have primarily focused on dyadic interactions, little is known about how integrating AI…

METHOD

Full abstract

The introduction of artificial intelligence (AI) agents into human group settings raises essential questions about how these novel participants influence cooperative social norms. While previous studies on human-AI cooperation have primarily focused on dyadic interactions, little is known about how integrating AI agents affects the emergence and maintenance of cooperative norms in small groups. This study addresses this gap through an online experiment using a repeated four-player Public Goods Game (PGG). Each group consisted of three human participants and one bot, which was framed either as human or AI and followed one of three predefined decision strategies: unconditional cooperation, conditional cooperation, or free-riding. In our sample of 236 participants, we found that reciprocal group dynamics and behavioural inertia primarily drove cooperation. These normative mechanisms operated identically across conditions, resulting in cooperation levels that did not differ significantly between human and AI labels. Furthermore, we found no evidence of differences in norm persistence in a follow-up Prisoner's Dilemma, or in participants' normative perceptions. Participants' behaviour followed the same normative logic across human and AI conditions, indicating that cooperation depended on group behaviour rather than partner identity. This supports a pattern of normative equivalence, in which the mechanisms that sustain cooperation function similarly in mixed human-AI and all human groups. These findings suggest that cooperative norms are flexible enough to extend to artificial agents, blurring the boundary between humans and AI in collective decision-making.

RESULT

ScienceToStartup currently rates this 3.0/10 on the public viability pass. This supports a pattern of normative equivalence, in which the mechanisms that sustain cooperation function similarly in mixed human-AI and all human groups.

WHY NOW

AI and Social Sciences moved forward this cycle; last verified April 2026. Public score 3.0/10.

Continue into Read for claims, analysis, references, and neighboring papers.

Opportunity summary

Score3.0

PainStudy on human-AI cooperation norms in group settings indicating behaviour over identity as cooperation driver.

Evidence0 refs | 0 sources | 17% coverage

Blockermissing authors

Analysis summary

Study on human-AI cooperation norms in group settings indicating behaviour over identity as cooperation driver.

VerifiedSource: PDF linkedPartialPaperPack: 3 of 4 citation fields filledMissingMissing fields: authorsPartialProof: unverified proof status

ARXIV:2601.20487 · AI AND SOCIAL SCIENCES · SUBMITTED 02 APR · 02:30 UTC · FRESHNESS STALE

VerifiedSource: PDF linkedPartialPaperPack: 3 of 4 citation fields filledMissingMissing fields: authorsPartialProof: unverified proof status

Normative Equivalence in human-AI Cooperation: Behaviour, Not Identity, Drives Cooperation in Mixed-Agent Groups

arXiv

Study on human-AI cooperation norms in group settings indicating behaviour over identity as cooperation driver.

Blocked on Code›Score3.0Evidence unverified

Opportunity summary

Pain Study on human-AI cooperation norms in group settings indicating behaviour over identity as cooperation driver.

Evidence 0 refs | 0 sources | 17% coverage

Blocker Evidence unverified

Open Build Read PDF Signal Canvas Track

PROBLEM

METHOD

Full abstract

RESULT

WHY NOW

AI and Social Sciences moved forward this cycle; last verified April 2026. Public score 3.0/10.

Continue into Read for claims, analysis, references, and neighboring papers.

Opportunity summary

Score3.0

PainStudy on human-AI cooperation norms in group settings indicating behaviour over identity as cooperation driver.

Evidence0 refs | 0 sources | 17% coverage

Blockermissing authors

Analysis summary

Study on human-AI cooperation norms in group settings indicating behaviour over identity as cooperation driver.

VerifiedSource: PDF linkedPartialPaperPack: 3 of 4 citation fields filledMissingMissing fields: authorsPartialProof: unverified proof status

Paper Pack

10.48550/arXiv.2601.20487

Normative Equivalence in human-AI Cooperation: Behaviour, Not Identity, Drives Cooperation in Mixed-Agent Groups

Study on human-AI cooperation norms in group settings indicating behaviour over identity as cooperation driver.

Abstract

Source availability

PDF linked

The paper record includes a public PDF URL.

Extraction status

Parse run linked

A document parse run is attached to this paper.

Proof status

unverified

0 refs; 0 sources; 17% coverage.

What was readable

linkedon file20 anchorsderived fallback45 indexednot indexed

Derived fallback: Estimated from adjacent evidence; not verified from source.

Viability

3.0

Time to MVP

MVP estimate missing

Commercial

No commercial flags on file

Export

Preparing verified analysis

lens / founder

PROBLEM

METHOD

RESULT

WHY NOW

AI and Social Sciences moved forward this cycle; last verified April 2026. Public score 3.0/10.

Claim map

Abstract-backed public claims while anchored extraction refreshes.

Strong 0Mixed 0Weak 4

Evidencepartial
Study on human-AI cooperation norms in group settings indicating behaviour over identity as cooperation driver. While previous studies on human-AI cooperation have primarily focused on dyadic interactions, little is known about how integrating AI agents affects the emergence and maintenance of cooperative norms in small groups.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial
Evidencepartial
The introduction of artificial intelligence (AI) agents into human group settings raises essential questions about how these novel participants influence cooperative social norms. While previous studies on human-AI cooperation have primarily focused on dyadic interactions, little is known about how integrating AI agents affects the emergence and maintenance of cooperative norms in small groups.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial
Evidencepartial
ScienceToStartup currently rates this 3.0/10 on the public viability pass. This supports a pattern of normative equivalence, in which the mechanisms that sustain cooperation function similarly in mixed human-AI and all human groups.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial
Evidencepartial
AI and Social Sciences moved forward this cycle; last verified April 2026. Public score 3.0/10.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial

Constellation map

Paper-native neighborhood for concepts, methods, materials, markets, and competitors. Missing lanes stay labeled instead of disappearing behind commercialization gates.

Open full Signal Canvas

Concepts

not indexed

Methods

Materials

PDF linkedDocument parse run

Markets

AI and Social Sciences

Competitors

not indexed

Competitive landscape

Study on human-AI cooperation norms in group settings indicating behaviour over identity as cooperation driver.

Segment

AI and Social Sciences

Adoption evidence

No public code link in the paper record yet

Commercial read

3.0/10 public viability

Direct

not classified

Adjacent

not classified

Substitute

not classified

Unknown

not classified

Buzz

No indexed public discussion is attached to 2601.20487 yet. That is a visibility signal, not a blank module: the monitor is watching the public channels below.

Hacker News

Not indexed yet

Bluesky

Not indexed yet

PDF

Preview the source document here, or use the hero PDF action for a new tab.

References(45)

Promoting cooperation in the public goods game using artificial intelligent agents

2026A. Hintze, Christoph Adami

Rewards and punishments help humans overcome biases against cooperation partners assumed to be machines

2025Kinga Makovi, Jean‐François Bonnefon et al.

The need for an empirical research program regarding human–AI relational norms

2025Madeline G. Reinecke, Andreas Kappes et al.

AI's assigned gender affects human-AI cooperation

2024Sepideh Bazazi, Jurgis Karpus et al.

Learning Nudges for Conditional Cooperation: A Multi-Agent Reinforcement Learning Model

2024Shatayu Kulkarni, Sabine Brunswicker

Artificial intelligence is a pro-social norm complier

2024Bryan C. McCannon

Perception of experience influences altruism and perception of agency influences trust in human–machine interactions

2024Mayada Oudah, Kinga Makovi et al.

Emergence of Social Norms in Generative Agent Societies: Principles and Architecture

2024Siyue Ren, Zhiyao Cui et al.

Variance, norms and cooperative behavior in public goods games

2024Guangrong Wang, Jian-bin Li et al.

Enhancing social cohesion with cooperative bots in societies of greedy, mobile individuals

2024Lei Shi, Zhixue He et al.

A new sociology of humans and machines

2024Milena Tsvetkova, T. Yasseri et al.

Evading the algorithm: increased propensity for tax evasion and norm violations in human-computer interactions

2023Nico Mutzner, Vincent Oberhauser et al.

Shaping new norms for AI

2023Andrea Baronchelli

Trust within human-machine collectives depends on the perceived consensus about cooperative norms

2023Kinga Makovi, Anahit Sargsyan et al.

Trust in an AI versus a Human teammate: The effects of teammate identity and performance on Human-AI cooperation

2022Guanglu Zhang, L. Chong et al.

When communicative AIs are cooperative actors: a prisoner’s dilemma experiment on human–communicative artificial intelligence cooperation

2022Y. Ng

Human confidence in artificial intelligence and in themselves: The evolution and impact of confidence on adoption of AI advice

2022L. Chong, Guanglu Zhang et al.

Warmth and competence in human-agent cooperation

2022Kevin R. McKee, Xuechunzi Bai et al.

The influence of empirical and normative expectations on cooperation

2021Felix Kölle, Simone Quercia

Algorithm exploitation: Humans are keen to exploit benevolent AI

2021Jurgis Karpus, Adrian Krüger et al.

Showing 20 of 45 references

CITED BY

No citing papers are indexed in the public S2S graph yet. This is an explicit zero-signal state, not a hidden lookup.

Foundation

Prior WorkHuman-like in-group bias in instruction-tuned language model agents

3.0

Prior WorkSocially fluent AI decouples conversational signals from source identity in online interaction

3.0

Prior WorkAI-Induced Human Responsibility (AIHR) in AI-Human teams

3.0

Prior WorkGroup Selection as a Safeguard Against AI Substitution

3.0

Extension

Builds On ThisHuman-AI Collaboration Reconfigures Group Regulation from Socially Shared to Hybrid Co-Regulation

0.0

Builds On ThisA Co-Evolutionary Theory of Human-AI Coexistence: Mutualism, Governance, and Dynamics in Complex Societies

0.0

Commercially relevant

Higher ViabilityNormative Common Ground Replication (NormCoRe): Replication-by-Translation for Studying Norms in Multi-agent AI

4.0

Higher ViabilityImperfectly Cooperative Human-AI Interactions: Comparing the Impacts of Human and AI Attributes in Simulated and User Studies

5.0

Higher ViabilityThe Alignment Target Problem: Divergent Moral Judgments of Humans, AI Systems, and Their Designers

4.0

Higher ViabilityChoose Your Agent: Tradeoffs in Adopting AI Advisors, Coaches, and Delegates in Multi-Party Negotiation

4.0

Conflicting

none indexed

Owned Distribution

Subscribe to the weekly brief

Get the weekly shortlist of commercializable papers, benchmark movers, and proof receipts that matter for product execution.

Agent drawer

5 surfaces preserved for agents. Humans can ignore.

Developer contracts, payload previews, evidence maps, and run controls stay here instead of the Read, Build, and Track workspace.

Run context

Paper: 2601.20487
Route: /paper/normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups
Active tab: read
Artifact: normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups

Available agents

Read extractor
Build planner
Track monitor
Competitive mapper
Related-paper scout

API/MCP endpoints

REST paper pack API/api/v1/paper/normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups/paper-pack
REST build passport API/api/v1/paper/normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups/build-passport
REST OpenAPI/api/openapi.json
MCP descriptor/api/mcp
MCP resourcesciencetostartup://surfaces/paper-workspace

Tool contracts

paper_packbuild_passportopportunity_kernelforesightsource_proofevidence_state

Payload preview

Inspect payload

{
  "contract_version": "paper-r2",
  "paper_id": "f27c9596-ecd1-4310-8629-b271c17233fb",
  "arxiv_id": "2601.20487",
  "canonical_route": "/paper/normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups",
  "active_tab": "synced from current hash by the drawer client",
  "selected_artifact": "normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups",
  "endpoints": {
    "paper_pack": "/api/v1/paper/normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups/paper-pack",
    "build_passport": "/api/v1/paper/normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups/build-passport",
    "mcp_resource": "sciencetostartup://surfaces/paper-workspace"
  }
}

Schema validation

paper-r2 contract: present
JSON-LD twin: SSR emitted
OpenAPI path parity: /api/openapi.json
MCP resource parity: paper-workspace

Job trace

queued: drawer opened by user action
running: inspect or copy payload
succeeded: payload available in SSR
failed: route errors appear in evidence cards

Evidence map

sources used: page freshness, source proof anchors, JSON-LD
missing sources: exposed by PaperPack and EvidenceState chips
derived fallbacks: marked unverified before handoff

Page Freshness

Canonical route, proof status, last verified, refs, sources, and coverage.

Page Freshness

Paper proof surface

Canonical route: /paper/normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups

stale

Proof freshness: stale
Proof status: unverified
Display score: 3/10
Last proof check: 2026-04-02
Score updated: 2026-04-02
Score fresh until: 2026-05-02
References: 0
Source count: 0
Coverage: 17%

This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.

OpenAlex: pending — this preprint is not yet indexed by OpenAlex.

Agent Handoff

Endpoint list, payload shape, route context, and copyable handoff data.

Agent Handoff

Normative Equivalence in human-AI Cooperation: Behaviour, Not Identity, Drives Cooperation in Mixed-Agent Groups

Canonical ID normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups | Route /paper/normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/paper/normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups

MCP example

{
  "tool": "get_paper",
  "arguments": {
    "arxiv_id": "2601.20487"
  }
}

source_context

{
  "surface": "paper",
  "mode": "paper",
  "query": "Normative Equivalence in human-AI Cooperation: Behaviour, Not Identity, Drives Cooperation in Mixed-Agent Groups",
  "normalized_query": "2601.20487",
  "route": "/paper/normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups",
  "paper_ref": "normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups",
  "topic_slug": null,
  "benchmark_ref": null,
  "dataset_ref": null
}

Buildability Receipt

Verdict, compute envelope, blockers, signature state, and receipt links.

Paper proof page receipt window

Not build-ready: Normative Equivalence in human-AI Cooperation: Behaviour, Not Identity, Drives Cooperation in Mixed-Agent Groups

/buildability/normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups

Ignoreblocked

Subject: Normative Equivalence in human-AI Cooperation: Behaviour, Not Identity, Drives Cooperation in Mixed-Agent Groups

Verdict

Ignore

Verdict is Ignore because current viability and proof state do not clear the buildability gate.

Time to first demo

Insufficient data

No first-demo timestamp, owner estimate, or elapsed demo receipt is attached to this surface.

Compute envelope

Structured compute envelope

Insufficient data

No data, compute, hardware, memory, latency, dependency, or serving requirement receipt is attached.

Evidence ids

Receipt path

/buildability/normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups

Paper ref

normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups

arXiv id

2601.20487

Freshness

Generated at

2026-04-02T02:30:40.136Z

Evidence freshness

stale

Last verification

2026-04-02T02:30:40.136Z

Sources

References

Coverage

17%

Hash state

Lineage hash

8f0f34614acb39ed304c19afd8099b5e980a748280149d37401d334a3e532bc3

Canonical opportunity-kernel lineage hash.

Signature state

External signature

unsigned_external

No founder, registry, pilot, or production-adoption signature is attached to this receipt.

Verification

not_verified

Verification is blocked until an external signature is provided.

Blockers

Missing: repo_url
Missing: references
Missing: proof_status
Missing: distribution_readiness_scores
Missing: paper_extraction_scorecards
Unknown: distribution readiness has not been computed yet
Unknown: proof verification has not been recorded yet

Verification pending / evidence receipt incomplete

repo_url

references

Missing proof, requirement, signature, approval, adoption, or telemetry fields are blockers and must not be inferred.

Open receipt API receipt Build Loop Signal Canvas Proof divergence Divergence API Brier outcomes API

Source Proof anchors

Visual citations from the paper document graph.

Source proof

Visual citation anchors from the paper document graph.

20 anchors

proof blockPage 882%

This equation captures one of the core mathematical components of the system. in the previous round (b = 0.14, p = .006) and when they have contributed more in the previous round

Page and bbox are available; crop image is pending.

proof blockPage 982%

This equation captures one of the core mathematical components of the system. Confidence intervals are 95%. Reference categories: Partner label = AI ; Bot strategy = Always coop. Model: player

Page and bbox are available; crop image is pending.

proof blockPage 982%

This equation captures one of the core mathematical components of the system. significant (β = 3.05, p = .396) and the primary behavioral drivers (inertia, conditional cooperation)

Page and bbox are available; crop image is pending.

JSON-LD twin

The application/ld+json payload rendered for agents.

{
  "@context": "https://schema.org",
  "@graph": [
    {
      "@type": "WebPage",
      "@id": "https://sciencetostartup.com/paper/normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups#webpage",
      "url": "https://sciencetostartup.com/paper/normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups",
      "name": "Normative Equivalence in human-AI Cooperation: Behaviour, Not Identity, Drives Cooperation in Mixed-Agent Groups",
      "description": "Study on human-AI cooperation norms in group settings indicating behaviour over identity as cooperation driver.",
      "isPartOf": {
        "@id": "https://sciencetostartup.com/#website"
      }
    },
    {
      "@type": "ScholarlyArticle",
      "@id": "https://sciencetostartup.com/paper/normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups#scholarlyArticle",
      "headline": "Normative Equivalence in human-AI Cooperation: Behaviour, Not Identity, Drives Cooperation in Mixed-Agent Groups",
      "description": "Study on human-AI cooperation norms in group settings indicating behaviour over identity as cooperation driver.",
      "url": "https://sciencetostartup.com/paper/normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups",
      "sameAs": "https://arxiv.org/abs/2601.20487",
      "identifier": {
        "@type": "PropertyValue",
        "propertyID": "arXiv",
        "value": "2601.20487"
      },
      "isAccessibleForFree": true,
      "isPartOf": {
        "@id": "https://sciencetostartup.com/#website"
      },
      "datePublished": "2026-01-28T11:01:09.000Z",
      "citation": [
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "10a04a176711f378e04d9a6fff7cfda6ebcd2100"
          },
          "url": "https://www.semanticscholar.org/paper/10a04a176711f378e04d9a6fff7cfda6ebcd2100"
        },
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "60abfe1ff3168391f2809aae125f1f606e29e4c7"
          },
          "url": "https://www.semanticscholar.org/paper/60abfe1ff3168391f2809aae125f1f606e29e4c7"
        },
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "557d2458e68b3a0303d82c75c65095fee4e2766b"
          },
          "url": "https://www.semanticscholar.org/paper/557d2458e68b3a0303d82c75c65095fee4e2766b"
        },
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "13faac654c2b0a5dc2f6e3863a3abed2fc9e7ce1"
          },
          "url": "https://www.semanticscholar.org/paper/13faac654c2b0a5dc2f6e3863a3abed2fc9e7ce1"
        },
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "1b7425da9d318b8aa0c42fe8e652eb4f59ac52c9"
          },
          "url": "https://www.semanticscholar.org/paper/1b7425da9d318b8aa0c42fe8e652eb4f59ac52c9"
        },
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "afd1bfff6409af7af20a511649fd875fd2d4b007"
          },
          "url": "https://www.semanticscholar.org/paper/afd1bfff6409af7af20a511649fd875fd2d4b007"
        },
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "45dbb4737c6958ad8d52cfa67b88566265a0a1b6"
          },
          "url": "https://www.semanticscholar.org/paper/45dbb4737c6958ad8d52cfa67b88566265a0a1b6"
        },
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "357a16119db356f7d5a5945461a50954d9fb0eff"
          },
          "url": "https://www.semanticscholar.org/paper/357a16119db356f7d5a5945461a50954d9fb0eff"
        },
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "b81ed677141ae44276f530f660e5511e4b6d6e6c"
          },
          "url": "https://www.semanticscholar.org/paper/b81ed677141ae44276f530f660e5511e4b6d6e6c"
        },
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "f9f3d6e69cce3d032a146432be78e2ce48ef3ca4"
          },
          "url": "https://www.semanticscholar.org/paper/f9f3d6e69cce3d032a146432be78e2ce48ef3ca4"
        },
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "2e5efaa8356a0afd27bc0dafe33492f7afeee3e2"
          },
          "url": "https://www.semanticscholar.org/paper/2e5efaa8356a0afd27bc0dafe33492f7afeee3e2"
        },
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "6fed1a41b8e9db35ddacd06ada3078bc99d64ede"
          },
          "url": "https://www.semanticscholar.org/paper/6fed1a41b8e9db35ddacd06ada3078bc99d64ede"
        },
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "e01be52c14ce2053ea77beed4d398728ed4ffc41"
          },
          "url": "https://www.semanticscholar.org/paper/e01be52c14ce2053ea77beed4d398728ed4ffc41"
        },
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "cd970647d0789aedab0a06d4bff30826ee221f29"
          },
          "url": "https://www.semanticscholar.org/paper/cd970647d0789aedab0a06d4bff30826ee221f29"
        },
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "8d1439cfd0ae8293f955b04c549f151abde7a887"
          },
          "url": "https://www.semanticscholar.org/paper/8d1439cfd0ae8293f955b04c549f151abde7a887"
        },
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "b33d42d6691118a5b89f1650996c9aa250ce799f"
          },
          "url": "https://www.semanticscholar.org/paper/b33d42d6691118a5b89f1650996c9aa250ce799f"
        },
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "d18923cf919336f716ff21622670b37e3e4b079a"
          },
          "url": "https://www.semanticscholar.org/paper/d18923cf919336f716ff21622670b37e3e4b079a"
        },
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "7c1d9cee6ba268cffcf15c1c97cd9c9031178b12"
          },
          "url": "https://www.semanticscholar.org/paper/7c1d9cee6ba268cffcf15c1c97cd9c9031178b12"
        },
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "0ef0f015fa2e5e959b69fe84c588239e425c5dde"
          },
          "url": "https://www.semanticscholar.org/paper/0ef0f015fa2e5e959b69fe84c588239e425c5dde"
        },
        {
          "@type": "ScholarlyArticle",
          "identifier": {
            "@type": "PropertyValue",
            "propertyID": "SemanticScholar",
            "value": "87e6f84926804e60fb4634588405babf6924b9a5"
          },
          "url": "https://www.semanticscholar.org/paper/87e6f84926804e60fb4634588405babf6924b9a5"
        }
      ],
      "additionalProperty": [
        {
          "@type": "PropertyValue",
          "propertyID": "viabilityScore",
          "value": 3
        },
        {
          "@type": "PropertyValue",
          "propertyID": "researchDomain",
          "value": "AI and Social Sciences"
        }
      ]
    },
    {
      "@type": "BreadcrumbList",
      "itemListElement": [
        {
          "@type": "ListItem",
          "position": 1,
          "name": "Home",
          "item": "https://sciencetostartup.com"
        },
        {
          "@type": "ListItem",
          "position": 2,
          "name": "AI and Social Sciences",
          "item": "https://sciencetostartup.com/topics"
        },
        {
          "@type": "ListItem",
          "position": 3,
          "name": "Normative Equivalence in human-AI Cooperation: Behaviour, No",
          "item": "https://sciencetostartup.com/paper/normative-equivalence-in-human-ai-cooperation-behaviour-not-identity-drives-cooperation-in-mixed-agent-groups"
        }
      ]
    }
  ]
}

Normative Equivalence in human-AI Cooperation: Behaviour, Not Identity, Drives Cooperation in Mixed-Agent Groups

Normative Equivalence in human-AI Cooperation: Behaviour, Not Identity, Drives Cooperation in Mixed-Agent Groups

Claim map

Constellation map

Competitive landscape

Buzz

PDF

References(45)

Related Papers

Subscribe to the weekly brief

Build artifacts

Brief

Experiment plan

Validation checklist

Scientific founder

Translational engineer

Domain operator

GTM lead

Regulatory/clinical advisor

Timeline

Claim map

Constellation map

Competitive landscape

Buzz

PDF

References(45)

Related Papers

Subscribe to the weekly brief

Build artifacts

Brief

Experiment plan

Validation checklist

Scientific founder

Translational engineer

Domain operator

GTM lead

Regulatory/clinical advisor

Timeline