AI systems increasingly generate and act upon cultural outputs (language, images, narratives) yet often lack frameworks for interpreting the cultural complexity they encounter. As AI enters domains requiring contextual judgement rather than clear ground truth, traditional benchmarking breaks down. This research theme invites you to explore how participatory design, creative practice, and interpretive methodologies can shape AI systems that engage meaningfully with ambiguity, plurality, and diverse human values.
Current AI development risks homogenisation, where similar architectures trained on similar data reinforce narrow models of reasoning and representation. Your research could challenge this by investigating how to design AI systems that preserve multiple valid perspectives rather than producing monolithic outputs, how human-AI ensembles can enhance rather than replace human capabilities, or how communities can collaborate in building AI that serves their needs rather than having solutions imposed upon them.
Potential directions include developing interpretive evaluation frameworks that assess cultural nuance and contextual sensitivity, creating participatory methods that prevent 'participation washing' in AI development, exploring how generative AI transforms creative labour and agency, or designing human-AI collaboration patterns that amplify collective intelligence whilst preserving human autonomy. You might investigate how arts and humanities perspectives can inform AI architecture (not just interface design), how to ensure marginalised communities genuinely influence AI outcomes, or how to build systems where meaning is made collaboratively rather than dictated by algorithmic outputs.
This theme positions design, arts, humanities, and qualitative social sciences as integral to technical innovation. Whether your background is in design, computer science, creative arts, cultural studies, or social sciences, there are opportunities to contribute to AI that reflects the diversity, ambiguity, and richness of human experience rather than flattening it through narrow operational metrics.
Place-based and Regional Context
The North East offers distinctive opportunities for research in participatory AI design and creative industries innovation. The region's creative sector contributes over £1.4 billion annually, with concentrations in screen industries, gaming, and digital media that provide real-world contexts for studying AI's impact on creative work. Newcastle and Gateshead's cultural quarter, including Baltic Centre for Contemporary Art and Sage Gateshead, offers partnerships for exploring AI in arts and cultural production.
Regional challenges around post-industrial transition, digital exclusion, and economic inequality create urgent needs for citizen-centred AI approaches. Projects could engage with Newcastle City Council's digital transformation initiatives, collaborate with Tyne & Wear Archives & Museums on AI for cultural heritage, or work with creative organisations like Wubbleyou on participatory design for diverse communities. The region's strong tradition of participatory design and community engagement, exemplified by Digital Civics work, provides methodological foundations for research that genuinely includes marginalised voices in shaping AI futures.
Relevant Partner Organisations
This theme connects with partners across creative industries, public sector innovation, and community organisations. Creative sector partners including Wubbleyou, Seymour-Powell, and Sunderland Software City offer contexts for studying AI in design practice and digital production. Public sector partners such as Newcastle City Council, Tyne & Wear Archives & Museums, and North of Tyne Combined Authority provide opportunities for participatory AI governance research.
Technology partners including Nokia Bell Labs, Google, and Thoughtworks bring expertise in AI development that can be combined with arts and humanities perspectives. Community organisations like VONNE and Innovation SuperNetwork enable engagement with diverse publics in co-designing AI systems. These partnerships support research spanning from creative AI tools to democratic governance, ensuring your work addresses real-world challenges whilst maintaining academic rigour.
Related Reading
Foundational Vision
- Hemment, D., Kommers, C., et al. (2025). Doing AI Differently: Rethinking the Foundations of AI via the Humanities. White Paper. The Alan Turing Institute.
Participatory AI Design
- Delgado, F., Yang, S., Madaio, M., & Yang, Q. (2023). The Participatory Turn in AI Design: Theoretical Foundations and the Current State of Practice. Proceedings of the 2023 ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization.
- Gautam, A. (2024). Reconfiguring Participatory Design to Resist AI Realism. Participatory Design Conference 2024.
- Zhang, A., Walker, O., Nguyen, K., Dai, J., Chen, A., & Lee, M.K. (2023). Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction, 7(CSCW1), 1-32.
- Zytko, D., Wisniewski, P.J., Guha, S., Baumer, E.P.S., & Lee, M.K. (2022). Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. CHI EA '22.
- Birhane, A., Isaac, W., Prabhakaran, V., Diaz, M., Elish, M.C., Gabriel, I., & Mohamed, S. (2022). Power to the People? Opportunities and Challenges for Participatory AI. EAAMO '22.
Generative AI and Design Practice
- Weisz, J.D., He, J., Muller, M., Hoefer, G., Miles, R., & Geyer, W. (2024). Design Principles for Generative AI Applications. CHI '24.
- Inie, N., Falk, J., & Tanimoto, S. (2023). Designing Participatory AI: Creative Professionals' Worries and Expectations about Generative AI. CHI EA '23.
- Chang, M., Druga, S., Fiannaca, A.J., Vergani, P., Kulkarni, C., Cai, C.J., & Terry, M. (2023). The Prompt Artists. C&C '23.
- GenAICHI Workshop. (2024). Generative AI and HCI at CHI 2024. CHI EA '24.
Value-Sensitive and Stakeholder-Centred Design
- Cenci, A., Ilskov, S.J., Andersen, N.S., et al. (2024). The Participatory Value-Sensitive Design of a mHealth App Targeting Citizens with Dementia in a Danish Municipality. AI and Ethics, 4, 375-401.
- Park, H., Ahn, D., Hosanagar, K., & Lee, J. (2022). Designing Fair AI in Human Resource Management: Understanding Tensions Surrounding Algorithmic Evaluation and Envisioning Stakeholder-Centred Solutions. CHI '22.
- Value-Sensitive Design Guidelines. (2024). Guidelines for Integrating Value Sensitive Design in Responsible AI Toolkits. CHI '24.
- Madaio, M.A., Stark, L., Vaughan, J.W., & Wallach, H. (2020). Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI. CHI '20.
Human-AI Co-creation Frameworks
- Rezwana, J., & Maher, M.L. (2023). Designing Creative AI Partners with COFI: A Framework for Modelling Interaction in Human-AI Co-Creative Systems. ACM Transactions on Computer-Human Interaction, 30(5), 1-28.
- Zhang, A., Boltz, A., Lynn, J., Wang, C., & Lee, M.K. (2023). Stakeholder-Centred AI Design: Co-Designing Worker Tools with Gig Workers through Data Probes. CHI '23.
- Riegelman, A., Pait, S., Kaur, J., Knowlton, A., Trajkova, M., & Magerko, B. (2025). The Co-Creative Design Framework for Hybrid Intelligence. C&C '25.
- Trajkova, M., Kaur, J., Riegelman, A., Maniscalco, E., Pait, S., Knowlton, A., & Magerko, B. (2025). Human-Centered AI Communication in Co-Creativity: An Initial Framework and Insights. C&C '25.
Creative Industries and AI
- Lee, H-K. (2022). Rethinking Creativity: Creative Industries, AI and Everyday Creativity. Media, Culture & Society, 44(3), 601-612.
- Erickson, K. (2024). AI and Work in the Creative Industries: Digital Continuity or Discontinuity? Creative Industries Journal.
- Huang, J., Hitchen, G., & Dogan, S. (2025). Generative AI in the Screen and Live Performance Industries: A Conceptual Framework and Prospects for Future Research. Convergence.
- Anantrasirichai, N., & Bull, D. (2022). Artificial Intelligence in the Creative Industries: A Review. Artificial Intelligence Review, 55(1), 589-656.
Creativity and Authorship
- McGuire, J., De Cremer, D., & Van de Cruys, T. (2024). Establishing the Importance of Co-creation and Self-efficacy in Creative Collaboration with Artificial Intelligence. Scientific Reports, 14, 18525.
- Faiella, F., et al. (2025). Am I Still Creative? The Effect of Artificial Intelligence on Creative Self-Beliefs. The Journal of Creative Behavior, 59(1).
- Watiktinnakorn, C., Seesai, J., & Kerdvibulvech, C. (2023). Blurring the Lines: How AI is Redefining Artistic Ownership and Copyright. Discover Artificial Intelligence, 3.
- Moruzzi, C. (2025). Artificial Intelligence and Creativity. Philosophy Compass, 20(1).
- Tigre Moura, F. (2023). Artificial Intelligence, Creativity, and Intentionality: The Need for a Paradigm Shift. The Journal of Creative Behavior, 57(4).
Public Sector and Civic AI
- Kawakami, A., Coston, A., Zhu, H., Heidari, H., & Holstein, K. (2024). The Situate AI Guidebook: Co-Designing a Toolkit to Support Multi-Stakeholder, Early-stage Deliberations Around Public Sector AI Proposals. CHI '24.
- CHI Workshop. (2025). Emerging Practices in Participatory AI Design in Public Sector Innovation. CHI EA '25.
- Studying Up Public Sector AI. (2024). How Networks of Power Relations Shape Agency Decisions Around AI Design and Use. Proceedings of the ACM on Human-Computer Interaction.
Labour and Platform Economies
- Vallas, S.P., & Schor, J.B. (2020). What Do Platforms Do? Understanding the Gig Economy. Annual Review of Sociology, 46, 273-294.
- Dedema, S., et al. (2024). Socio-technical Issues in the Platform-mediated Gig Economy: A Systematic Literature Review. Journal of the Association for Information Science and Technology, 75(4).
- Frost, S., et al. (2024). Cultural Work, Wellbeing, and AI. Frontiers European Journal of Cultural Management and Policy.
Cultural Policy and Governance
- Caramiaux, B. (2020). The Use of Artificial Intelligence in the Cultural and Creative Sectors. European Parliament Policy Department for Structural and Cohesion Policies.
- UNESCO. (2024). AI in the Cultural and Creative Industries. UNESCO Germany.
- Guadamuz, A. (2025). The EU's Artificial Intelligence Act and Copyright. Journal of World Intellectual Property, 28(1).
- Drott, E. (2021). Copyright, Compensation, and Commons in the Music AI Industry. Creative Industries Journal, 14(2), 190-207.
UK and European Policy
- AHRC. (2022-2025). Strategic Delivery Plan. UK Research and Innovation.
- UK Government. (2024). Copyright and Artificial Intelligence. GOV.UK consultation.
- UK Government. (2023). A Pro-innovation Approach to AI Regulation: Government Response. GOV.UK.
- European Commission. (2024). Artificial Intelligence Act. Regulation (EU) 2024/1689.
A complete bibliography file will be provided separately.
