mlsanityData to 14 Oct 2026

Human-AI Interaction Alignment: Designing, Evaluating, and Evolving Value-Centered AI For Reciprocal Human-AI Futures

arXiv 2512.21551 ↗First posted 25 Dec 2025cs.HC cs.AI cs.CLcited by 0

On the map: LLM alignment / RLHF / preference optimisation → Human values and AI feedback alignment

Abstract (arXiv)

The rapid integration of generative AI into everyday life underscores the need to move beyond unidirectional alignment models that only adapt AI to human values. This workshop focuses on bidirectional human-AI alignment, a dynamic, reciprocal process where humans and AI co-adapt through interaction, evaluation, and value-centered design. Building on our past CHI 2025 BiAlign SIG and ICLR 2025 Workshop, this workshop will bring together interdisciplinary researchers from HCI, AI, social sciences and more domains to advance value-centered AI and reciprocal human-AI collaboration. We focus on embedding human and societal values into alignment research, emphasizing not only steering AI toward human values but also enabling humans to critically engage with and evolve alongside AI systems. Through talks, interdisciplinary discussions, and collaborative activities, participants will explore methods for interactive alignment, frameworks for societal impact evaluation, and strategies for alignment in dynamic contexts. This workshop aims to bridge the disciplines' gaps and establish a shared agenda for responsible, reciprocal human-AI futures.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Human values and AI feedback alignment, one of 10 directions in LLM alignment / RLHF / preference optimisation. Builds on 14 of its 31 references that are in the map. First posted on arXiv 25 Dec 2025.

Builds on

14 of 31 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024AI Alignment with Changing and Influenceable Reward Functions28 May

Other references · 13

  1. 2022Training language models to follow instructions with human feedbackcited by 15,971
  2. 2023Whose Opinions Do Language Models Reflect?cited by 773
  3. 2023Co-Writing with Opinionated Language Models Affects Users' Viewscited by 148
  4. 2023Large Language Models can Strategically Deceive their Users when Put Under Pressurecited by 146
  5. 2022Jury Learning: Integrating Dissenting Voices into Machine Learning Modelscited by 118
  6. 2025Mind the Value-Action Gap: Do LLMs Act in Alignment with Their Values?cited by 51
  7. 2023Characterizing Manipulation from AI Systemscited by 43
  8. 2024Large Language Models for Education: A Surveycited by 34
  9. 2023How to Teach Programming in the AI Era? Using LLMs as a Teachable Agent for Debuggingcited by 30
  10. 2023ScatterShot: Interactive In-context Example Curation for Text Transformationcited by 20
  11. 2024Designing for Human-Agent Alignment: Understanding what humans want from their agentscited by 18
  12. 2024Exploring the Impact of AI Value Alignment in Collaborative Ideation: Effects on Perception, Ownership, and Outputcited by 12
1 more
  1. 2025Beyond One-Way Influence: Bidirectional Opinion Dynamics in Multi-Turn Human-LLM Interactionscited by 6

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  1. 2024Position: Towards Bidirectional Human-AI Alignment
  2. 2026Align AI to Dynamic Human-AI Workflows
  3. 2024ValueCompass: A Framework for Measuring Contextual Value Alignment Between Human and LLMs
  4. 2026Toward a Theory of Value in AI Alignment
  5. 2026Co-Constructing Alignment: A Participatory Approach to Situate AI Values ↗
  6. 2024A Moral Imperative: The Need for Continual Superalignment of Large Language Models
  7. 2026Building Intelligent User Interfaces for Human-AI Alignment
  8. 2024Concept Alignment