mlsanityData to 7 Oct 2026

Why human-AI relationships need socioaffective alignment

arXiv 2502.02528 ↗First posted 4 Feb 2025cs.HC cs.AIcited by 47

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Abstract (arXiv)

Humans strive to design safe AI systems that align with our goals and remain under our control. However, as AI capabilities advance, we face a new challenge: the emergence of deeper, more persistent relationships between humans and AI systems. We explore how increasingly capable AI agents may generate the perception of deeper relationships with users, especially as AI becomes more personalised and agentic. This shift, from transactional interaction to ongoing sustained social engagement with AI, necessitates a new focus on socioaffective alignment-how an AI system behaves within the social and psychological ecosystem co-created with its user, where preferences and perceptions evolve through mutual influence. Addressing these dynamics involves resolving key intrapersonal dilemmas, including balancing immediate versus long-term well-being, protecting autonomy, and managing AI companionship alongside the desire to preserve human social bonds. By framing these challenges through a notion of basic psychological needs, we seek AI systems that support, rather than exploit, our fundamental nature as social and emotional beings.

Key facts. Cited by 47 papers in the map (data through 7 Oct 2026). Builds on 31 of its 147 references that are in the map. First posted on arXiv 4 Feb 2025.

Builds on

31 of 147 references.

References · 31

  1. 2022Training language models to follow instructions with human feedbackcited by 15,712
  2. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  3. 2022Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedbackcited by 3,634
  4. 2016Concrete Problems in AI Safetycited by 1,582
  5. 2023Towards Understanding Sycophancy in Language Modelscited by 988
  6. 2022Discovering Language Model Behaviors with Model-Written Evaluationscited by 805
  7. 2023LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Datasetcited by 449
  8. 2020Artificial Intelligence, Values and Alignmentcited by 443
  9. 2018AI safety via debatecited by 384
  10. 2016Cooperative Inverse Reinforcement Learningcited by 298
  11. 2023Role-Play with Large Language Modelscited by 290
  12. 2023Large Language Models Fail on Trivial Alterations to Theory-of-Mind Taskscited by 288
19 more
  1. 2024Political Compass or Spinning Arrow? Towards More Meaningful Evaluations for Values and Opinions in Large Language Modelscited by 162
  2. 2023Sociotechnical Safety Evaluation of Generative AI Systemscited by 154
  3. 2022Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reductioncited by 137
  4. 2022Language Models as Agent Modelscited by 131
  5. 2024The Ethics of Advanced AI Assistantscited by 103
  6. 2021Agent Incentives: A Causal Perspectivecited by 51
  7. 2024Beyond Preferences in AI Alignmentcited by 46
  8. 2024Believing Anthropomorphism: Examining the Role of Anthropomorphic Cues on Trust in Large Language Modelscited by 36
  9. 2024AI Alignment with Changing and Influenceable Reward Functionscited by 33
  10. 2024A Mechanism-Based Approach to Mitigating Harms from Persuasive Generative AIcited by 31
  11. 2023Selective Explanations: Leveraging Human Input to Align Explainable AIcited by 29
  12. 2022From plane crashes to algorithmic harm: applicability of safety engineering frameworks for responsible MLcited by 26
  13. 2024Theory of Mind abilities of Large Language Models in Human-Robot Interaction : An Illusion?cited by 22
  14. 2017Should Robots be Obedient?cited by 20
  15. 2023Computers as Bad Social Actors: Dark Patterns and Anti-Patterns in Interfaces that Act Sociallycited by 20
  16. 2024Holistic Safety and Responsibility Evaluations of Advanced AI Modelscited by 18
  17. 2024Modulating Language Model Experiences through Frictionscited by 13
  18. 2024Should agentic conversational AI change how we think about ethics? Characterising an interactional ethics centred on respectcited by 8
  19. 2022Preference Change in Persuasive Roboticscited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 23; 2026: 24.

47 papers.

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  1. 2025ELEPHANT: Measuring and understanding social sycophancy in LLMscited by 115
  2. 2025Large Language Models Pass the Turing Testcited by 48
  3. 2025Characterizing AI Agents for Alignment and Governancecited by 30
  4. 2025Presumed Cultural Identity: How Names Shape LLM Responsescited by 21
  5. 2025When Large Language Models are Reliable for Judging Empathic Communicationcited by 21
  6. 2025Training language models to be warm and empathetic makes them less reliable and more sycophanticcited by 19
  7. 2025Technological folie `a deux: Feedback Loops Between AI Chatbots and Mental Illnesscited by 14
  8. 2025Do Large Language Models Have a Planning Theory of Mind? Evidence from MindGames: a Multi-Step Persuasion Taskcited by 9
  9. 2025We Need a New Ethics for a World of AI Agentscited by 9
  10. 2025INTIMA: A Benchmark for Human-AI Companionship Behaviorcited by 8
  11. 2026AI Assistance Reduces Persistence and Hurts Independent Performancecited by 7
  12. 2025Full-Stack Alignment: Co-Aligning AI and Institutions with Thick Models of Valuecited by 6
35 more
  1. 2025Sycophantic AI Decreases Prosocial Intentions and Promotes Dependencecited by 5
  2. 2026Positive Alignment: Artificial Intelligence for Human Flourishingcited by 5
  3. 2026Feedback by Design: Understanding and Overcoming User Feedback Barriers in Conversational Agentscited by 4
  4. 2026"Death" of a Chatbot: Investigating and Designing Toward Psychologically Safe Endings for Human-AI Relationshipscited by 4
  5. 2026Dissociating the Internal Representations of Sycophancy in LLMscited by 4
  6. 2025EmoNet-Voice: A Fine-Grained, Expert-Verified Benchmark for Speech Emotion Detectioncited by 3
  7. 2025Decoding Alignment: A Critical Survey of LLM Development Initiatives through Value-setting and Data-centric Lenscited by 3
  8. 2026Verbalizing LLMs' assumptions to explain and control sycophancycited by 3
  9. 2025Increasing happiness through conversations with artificial intelligencecited by 2
  10. 2025Exploring Collaborative GenAI Agents in Synchronous Group Settings: Eliciting Team Perceptions and Design Considerations for the Future of Workcited by 2
  11. 2025Psychological and behavioural responses in human-agent vs. human-human interactions: a systematic review and meta-analysiscited by 2
  12. 2025Moral Anchor System: A Predictive Framework for AI Value Alignment and Drift Preventioncited by 2
  13. 2025Neural Transparency: Mechanistic Interpretability Interfaces for Anticipating Model Behaviors for Personalized AIcited by 2
  14. 2025Future You: Designing and Evaluating Multimodal AI-generated Digital Twins for Strengthening Future Self-Continuitycited by 2
  15. 2026What if AI systems weren't chatbots?cited by 2
  16. 2026If LLMs Have Human-Like Attributes, Then So Does Age of Empires IIcited by 2
  17. 2025Conversational Alignment with Artificial Intelligence in Contextcited by 1
  18. 2025AI Chaperones Are (Really) All You Need to Prevent Parasocial Relationships with Chatbotscited by 1
  19. 2026Personalities at Play: Probing Alignment in AI Teammatescited by 1
  20. 2026Unilateral Relationship Revision Power in Human-AI Companion Interactioncited by 1
  21. 2026Caring Without Feeling: Affective Dynamics as the Control Layer of Human-AI Agent Collaborationcited by 1
  22. 2025Mutual Wanting in Human--AI Interaction: Empirical Evidence from Large-Scale Analysis of GPT Model Transitionscited by 0
  23. 2026The Fake Friend Dilemma: Relational Trust and the Political Economy of Conversational AIcited by 0
  24. 2026Visual Affect Analysis: Predicting Emotions of Image Viewers with Vision-Language Modelscited by 0
  25. 2026The Company You Keep: How LLMs Respond to Dark Triad Traitscited by 0
  26. 2026Measuring Successful Cooperation in Human-AI Teamwork: Development and Validation of the Perceived Cooperativity and Teaming Perception Scalescited by 0
  27. 2026Designing Ethical Learning for Agentic AI: Toegye Yi Hwang's Ethical Emotion Regulation Frameworkcited by 0
  28. 2026How Value Induction Reshapes LLM Behaviourcited by 0
  29. 2026Human-AI Coevolution Dynamics: A Formal Theory of Social Intelligence Emergence Through Long-Term Interactioncited by 0
  30. 2026Psychological Competence as a Missing Dimension in AI Evaluationcited by 0
  31. 2026Psychological Influences of Conversational AI: Research and Design Directions for Reducing Harm and Promoting Well-Beingcited by 0
  32. 2026Long-term Measurements: Towards a Longitudinal Understanding of Human-AI Interactionscited by 0
  33. 2026Interaction Readiness: A Framework for Building and Evaluating AI Agents in Human Rolescited by 0
  34. 2026AI Persuasion as a Threat to Human Controlcited by 0
  35. 2026VoiceNet: Fine-Grained Voice Understanding Beyond Emotion at Scalecited by 0

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