A Theory of Appropriateness That Accounts for Norms of Rationality

• URL: http://arxiv.org/abs/2603.14050v1
• Date: Sat, 14 Mar 2026 17:41:18 GMT
• Title: A Theory of Appropriateness That Accounts for Norms of Rationality
• Abstract summary: We propose a society-first theory of normative appropriateness where individuals generate behavior via predictive pattern completion.<n>This sense-making mechanism provides a parsimonious account of the key features of human norms.
• Score: 43.71392927070801
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose a society-first theory of normative appropriateness where individuals, modeled as pre-trained actors with cognitive architectures analogous to Large Language Models (LLMs), generate behavior via predictive pattern completion. Our theory posits that individuals act by completing distributed symbolic patterns based on context, answering questions such as "What does a person such as I do in a situation such as this?". This sense-making mechanism provides a parsimonious account of the key features of human norms: their context-dependence, arbitrariness, automaticity, dynamism, and their support from social sanctioning. It challenges rational-choice theories of social norms by accounting for their key features without needing to exogenously posit scalar rewards or preference relations. By distinguishing between explicit norms, which we associate with in-context adaptation, and implicit norms, which we associate with long-term memory, the theory reconceptualizes several foundational ideas in cognitive science. In particular, it gives an alternative account to the data traditionally seen as supporting dual-process models, and it flips the role of rationality, allowing us to construe it as adherence to culturally-contingent justification standards.

Related papers

• A game theory for foundation models shows new paths to rational cooperation through similarity inference [56.53805518668248]
  We show that foundation model agents engaging in optimal planning consistently converge to stable cooperation.<n>By shifting from decoupled to embedded agency, these agents model themselves as part of the universe they inhabit.
  arXiv  Detail & Related papers  (2026-08-04T17:24:33Z)
• Beyond Rational Illusion: Behaviorally Realistic Strategic Classification [56.458581740660236]
  We propose the Prospect-Guided Strategic Framework (Pro-SF) to address the behaviorally realistic strategic classification problem.<n>Pro-SF is a principled framework grounded in prospect theory to model and learn under behaviorally realistic strategic responses.<n> Experiments on synthetic and real-world datasets establish Pro-SF as a behaviorally grounded approach to strategic classification.
  arXiv  Detail & Related papers  (2026-05-19T11:04:55Z)
• Who We Are, Where We Are: Mental Health at the Intersection of Person, Situation, and Large Language Models [11.875040920985919]
  Building on interactionist and constructionist psychological theories, we develop interpretable models to predict well-being.<n>Our approach integrates person-level psychological traits with language-inferred situational features.<n>Results show that our principled, theory-driven features provide competitive performance while offering greater interpretability.
  arXiv  Detail & Related papers  (2026-03-06T06:37:39Z)
• Cultural Compass: A Framework for Organizing Societal Norms to Detect Violations in Human-AI Conversations [29.660677031436308]
  We introduce a taxonomy of norms that distinguishes between human-human norms that models should recognize and human-AI interactional norms that apply to the human-AI interaction itself.<n>We show how our taxonomy can be operationalized to automatically evaluate models' norm adherence in naturalistic, open-ended settings.
  arXiv  Detail & Related papers  (2026-01-12T20:11:40Z)
• Explainable Ethical Assessment on Human Behaviors by Generating Conflicting Social Norms [25.931377041506455]
  We introduce textitEthic, a novel ethical assessment approach to enhance valence prediction and explanation.<n>Our method outperforms strong baseline approaches, and human evaluations confirm that the generated social norms provide plausible explanations.
  arXiv  Detail & Related papers  (2025-12-16T09:04:42Z)
• Reciprocity as the Foundational Substrate of Society: How Reciprocal Dynamics Scale into Social Systems [0.0]
  We argue that reciprocity is not merely a local or primitive exchange, but a scalable substrate from which large-scale social structures can emerge.<n>We propose a three-stage framework to model this emergence: reciprocal dynamics at the individual level, norm stabilization through shared expectations, and the construction of durable institutional patterns.
  arXiv  Detail & Related papers  (2025-05-13T07:50:01Z)
• EgoNormia: Benchmarking Physical Social Norm Understanding [52.87904722234434]
  EGONORMIA spans seven norm categories: safety, privacy, proxemics, politeness, cooperation, coordination/proactivity, and communication/legibility.<n>Our work demonstrates that current state-of-the-art vision-language models (VLMs) lack robust grounded norm understanding, scoring a maximum of 54% on EGONORMIA and 65% on EGONORMIA-verified.
  arXiv  Detail & Related papers  (2025-02-27T19:54:16Z)
• Are language models rational? The case of coherence norms and belief revision [63.78798769882708]
  We consider logical coherence norms as well as coherence norms tied to the strength of belief in language models. We argue that rational norms tied to coherence do apply to some language models, but not to others.
  arXiv  Detail & Related papers  (2024-06-05T16:36:21Z)
• Regularized Conventions: Equilibrium Computation as a Model of Pragmatic Reasoning [72.21876989058858]
  We present a model of pragmatic language understanding, where utterances are produced and understood by searching for regularized equilibria of signaling games. In this model speakers and listeners search for contextually appropriate utterance--meaning mappings that are both close to game-theoretically optimal conventions and close to a shared, ''default'' semantics.
  arXiv  Detail & Related papers  (2023-11-16T09:42:36Z)
• Sociocultural Norm Similarities and Differences via Situational Alignment and Explainable Textual Entailment [31.929550141633218]
  We propose a novel approach to discover and compare social norms across Chinese and American cultures. We build a high-quality dataset of 3,069 social norms aligned with social situations across Chinese and American cultures. To test the ability of models to reason about social norms across cultures, we introduce the task of explainable social norm entailment.
  arXiv  Detail & Related papers  (2023-05-23T19:43:47Z)
• That's All Folks: a KG of Values as Commonsense Social Norms and Behaviors [0.34265828682659694]
  We propose two ontological modules, FOLK and That's All Folks. FOLK is an ontology for values intended in their broad sense, and That's All Folks is a module for lexical and factual folk value triggers. The resource is tested via performing automatic detection of values from text with a frame-based approach.
  arXiv  Detail & Related papers  (2023-03-01T16:35:46Z)
• Moral Stories: Situated Reasoning about Norms, Intents, Actions, and their Consequences [36.884156839960184]
  We investigate whether contemporary NLG models can function as behavioral priors for systems deployed in social settings. We introduce 'Moral Stories', a crowd-sourced dataset of structured, branching narratives for the study of grounded, goal-oriented social reasoning.
  arXiv  Detail & Related papers  (2020-12-31T17:28:01Z)
• Social Chemistry 101: Learning to Reason about Social and Moral Norms [73.23298385380636]
  We present Social Chemistry, a new conceptual formalism to study people's everyday social norms and moral judgments. Social-Chem-101 is a large-scale corpus that catalogs 292k rules-of-thumb. Our model framework, Neural Norm Transformer, learns and generalizes Social-Chem-101 to successfully reason about previously unseen situations.
  arXiv  Detail & Related papers  (2020-11-01T20:16:45Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.