Exploring the Impact of AI Value Alignment in Collaborative Ideation: Effects on Perception, Ownership, and Output
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Abstract (arXiv)
AI-based virtual assistants are increasingly used to support daily ideation tasks. The values or bias present in these agents can influence output in hidden ways. They may also affect how people perceive the ideas produced with these AI agents and lead to implications for the design of AI-based tools. We explored the effects of AI agents with different values on the ideation process and user perception of idea quality, ownership, agent competence, and values present in the output. Our study tasked 180 participants with brainstorming practical solutions to a set of problems with AI agents of different values. Results show no significant difference in self-evaluation of idea quality and perception of the agent based on value alignment; however, ideas generated reflected the AI's values and feeling of ownership is affected. This highlights an intricate interplay between AI values and human ideation, suggesting careful design considerations for future AI-supported brainstorming tools.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Feb 2024.
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Citing papers per year: 2024: 4; 2025: 5; 2026: 3.
12 papers.
- 2024PersonaFlow: Designing LLM-Simulated Expert Perspectives for Enhanced Research Ideationcited by 16
- 2025Co-Writing with AI, on Human Terms: Aligning Research with User Demands Across the Writing Processcited by 14
- 2024GPT for Games: An Updated Scoping Review (2020-2024)cited by 10
- 2025Where Do I 'Add the Egg'?: Exploring Agency and Ownership in AI Creative Co-Writing Systemscited by 7
- 2025Beyond One-Way Influence: Bidirectional Opinion Dynamics in Multi-Turn Human-LLM Interactionscited by 5
- 2024Analyzing Multimodal Interaction Strategies for LLM-Assisted Manipulation of 3D Scenescited by 4
- 2024Using Machine Learning to Distinguish Human-written from Machine-generated Creative Fictioncited by 4
- 2025The AI Memory Gap: Users Misremember What They Created With AI or Withoutcited by 2
- 2025Human-AI Interaction Alignment: Designing, Evaluating, and Evolving Value-Centered AI For Reciprocal Human-AI Futurescited by 0
- 2026AI in the Workplace: The Impact of AI on Perceived Job Decency and Meaningfulnesscited by 0
- 2026The New Social Image: How AI Competency and AI Proactivity Influence Self- and Peer-Perceptions in the Workplacecited by 0
- 2026Man, Machine, and Masterpiece: Artistic Ownership in the AI Eracited by 0
- 2026Man, Machine, and Masterpiece: Artistic Ownership in the AI Era16 Jul 2026
- 2026The New Social Image: How AI Competency and AI Proactivity Influence Self- and Peer-Perceptions in the Workplace29 May 2026
- 2026AI in the Workplace: The Impact of AI on Perceived Job Decency and Meaningfulness27 May 2026
- 2025Human-AI Interaction Alignment: Designing, Evaluating, and Evolving Value-Centered AI For Reciprocal Human-AI Futures25 Dec 2025
- 2025Beyond One-Way Influence: Bidirectional Opinion Dynamics in Multi-Turn Human-LLM Interactions22 Oct 2025
- 2025Where Do I 'Add the Egg'?: Exploring Agency and Ownership in AI Creative Co-Writing Systems18 Sep 2025
- 2025The AI Memory Gap: Users Misremember What They Created With AI or Without15 Sep 2025
- 2025Co-Writing with AI, on Human Terms: Aligning Research with User Demands Across the Writing Process16 Apr 2025
- 2024Using Machine Learning to Distinguish Human-written from Machine-generated Creative Fiction15 Dec 2024
- 2024GPT for Games: An Updated Scoping Review (2020-2024)1 Nov 2024
- 2024Analyzing Multimodal Interaction Strategies for LLM-Assisted Manipulation of 3D Scenes29 Oct 2024
- 2024PersonaFlow: Designing LLM-Simulated Expert Perspectives for Enhanced Research Ideation19 Sep 2024