Phd Position F - M Co-Creating With Ai Using ai As a Creative Partner In Design Teams H/F INRIA
Villeneuve-d'Ascq - 59 CDD- 36 mois
- Bac +2
- Bac +3, Bac +4
- Bac +5
- Service public des collectivités territoriales
Les missions du poste
PhD Position F/M Co-Creating with AI : Using AI as a Creative Partner in Design Teams
Le descriptif de l'offre ci-dessous est en Anglais
Type de contrat : CDD
Niveau de diplôme exigé : Bac +5 ou équivalent
Fonction : Doctorant
A propos du centre ou de la direction fonctionnelle
Created in 2008, the Inria center at the University of Lille employs 360 people, including 305 scientists in 15 research teams. Recognized for its strong involvement in the socio-economic development of the Hauts-De-France region, the Inria center at the University of Lille maintains a close relationship with large companies and SMEs. By fostering synergies between researchers and industry, Inria contributes to the transfer of skills and expertise in the field of digital technologies, and provides access to the best of European and international research for the benefit of innovation and businesses, particularly in the region.
For over 10 years, the Inria center at the University of Lille has been at the heart of Lille's university and scientific ecosystem, as well as at the heart of Frenchtech, with a technology showroom based on avenue de Bretagne in Lille, on the EuraTechnologies site of economic excellence dedicated to information and communication technologies (ICT).
Contexte et atouts du poste
This Ph.D. focuses on designing and taking advantage of AI in professional design teams. In particular, we aim to evaluate the role such AI agents can play in collaborative design ideation and how to understand, support and design the underlying cognitive ability to enable a successful human-computer partnership. IT will extend our previous work on building AI agents for group ideation in design [10], as well as our theoretical work on group cognition for designing collaborative AI systems [9]. We see a large potential of applying a more human-centered design approach to AI agents to identify benefits and address challenges when several stakeholders, intentions and goals are involved.
The Team : Loki is an Inria project team created in January 2018 in partnership with Université de Lille within the Joint Research Unit UMR 9189 CNRS-Centrale Lille-Université de Lille, CRIStAL. Our research aims at producing original ideas, fundamental knowledge, and practical tools to inspire, inform and support the design of human-computer interactions.
Positioning in the PEPR eNSEMBLE program :
This project directly relates to PC 3 MATCHING and in particular to theme 2 (Modelling and understanding collaborative or competitive interactions between two (or more) humans and intelligent systems) and partly theme 3 (Impact of intelligent systems on expertise and the loss of skills).
This project aims to explore how AI agents can BE integrated in human-human ideation practice, that would allow the agent to take part in the ideation practice, express agency through meaningful contributions. This requires the agent to better understand the designers current needs and joint focus, as well as adapt to an evolving and iterative process of ideation itself. Insides will BE applicable beyond ideation practice, but contribute to outline the potential for AI in creative human-human exploration overall (theme 2).
Designers often collaborate on creating physical mood boards, allowing them to express ideas and inspire new ones based on their reactions to emerging visual material. The use of AI in design teams oers a high external validity and therefore the potential for placing our prototypes in design teams for long-term observation. This will allow us to identify the impact of such AI agents on existing workflows, as well as design and team reflections when using such tools for professional means (theme 3).
Mission confiée
Problem and Objective
Most work in human-AI interaction for creative practice focuses on either active participation of artificial agents in dyadic interactions, or help/support tools for collaborative interactions. The objective of this project is to evaluate the role of GenAI agents' in the context of a human-human ideation in design. While our previous work showed how creativity can benefit from human-human-agent interactions, complementing rather than replacing the designers' roles, IT opened up a number of questions.
RQ1 : How can we integrate contributions from intelligent agents seamlessly within a group ideation process?While in dyadic interaction, AI agents can focus and align on human intention, group processes pose an additional challenge, which relates to selecting a target of alignment (i.e. to whom does the agent answer/suggest) as well as when is a good time to explore or exploit ideas within a collaborative ideation process. This requires the interaction paradigm to GO beyond reactive approaches (answering to one user) and instead create a larger context of the task and actions (i.e. ideas) contributed by all participants.
RQ2 : Which kinds of intelligent assistance are appropriate for which types of ideation phase? Our previous work has shown that designers prefer dierent levels of engagement of AI agents depending on the ideation phase. How these levels dier for each designer and how to select, integrate and provide these levels of support for ideation is one of the questions we want to address. This would include the ability to adapt the role of the AI agent between a tool and an engaged partner throughout the process.
RQ3 : How to design the agency of intelligent assistants in design teams, and how can they adapt to each other?Agency is the ability to perform activities in a particular environment in line with a set of goals/objectives that influence and shape the extent and nature of [the agent's] participation" [4]. Within group ideation, we can observe dierent levels of agency, where one participant takes the lead and suggests an idea, and the others exploit this idea further until someone else takes the lead to explore new ideas. How to design AI agents that are able to adapt their level of agency and when this is necessary is an open question.
In order to answer these questions the student will develop systems that help users to interactively explore diverse capabilities of creative systems, such as suggesting, explaining and negotiating contributions on visual creations adapted to several participants.
Theoretical foundations
The student will build on theory-based interaction approaches informed by previous work of the supervisors and the lab. This includes principles such as instrumental interaction [1] and co-adaptation [16] to create interactive systems that are discoverable [5], appropriable [14], and expressive [18], that grow with the user to enhance rather than replace the users skills.
Of particular relevance will BE our work on facilitating human-GenAI interaction for creative exploration in design practice [17, 18] (RQ1); expanding our insights from our previous work on human-human-agent interaction in design ideation [10, 22] (RQ2); and our work on group cognition for collaborative AI [9] and how to design dierent levels of initiative in human-AI games [15] (RQ3).
Principales activités
Application Domain
This PhD focuses on collaborative AI agents for design ideation, particularly in design teams. Ideation is a dynamic process involving divergent thinking (generating many ideas) and convergent thinking (narrowing down to the best ones) [7]. Designers draw inspiration from multiple sources, including collaboration, self-reflection, and serendipitous encounters [25]. Such ideation techniques for generating, evaluating, and refining ideas are the foundation for people's creative endeavors ranging from art to design to problem-solving. Research has shown that the quality of ideas oen increases when people collaborate with each other [23, 24]. This is due to the fact that group members can express diverse viewpoints that individuals may not consider otherwise and collaborate on ideation eorts by building on each other's contributions [2, 3, 11]. This human-human collaborative ideation can BE observed in diverse contexts such as when individuals with shared interests seek better ideas or when groups with conflicting needs seek to formulate satisfying solutions for everyone [22].
As a use case we will focus on mood boards, which are visual collages composed of images, text, and objects, that express concepts, ideas and emotions. Commonly used in creative fields such as design or fashion, they stimulate the perception and interpretation of more ephemeral phenomena such as color, texture, form, image and status [6]. Designers oen collaborate in the design of physical mood boards, where the act of finding, choosing and curating visual material not only helps designers express ideas they already have, but also inspires new ideas based on their reactions to the images that emerge [8]. Exploring the potential of GenAI in design teams hence provides a high level of external validity and opens up the possibility to deploy our work in design teams for long-term observation.
Contribution to digital collaboration : Expected results and Impact
The goal of this Ph.D. is to design and develop a novel form of human-computer partnership in the context of professional design teams.
The student will develop novel interactive systems that enable eective human-human-agent interaction, to :
- Investigate how humans in a design team could actively take control and collaborate with a GenAI agent.
- Provide a better understanding how users directly and indirectly communicate while creating visual designs and how these diverse signals can BE interpreted by an AI agent
- Develop working prototype(s) that demonstrate these methods in realistic design practice.
- Develop and apply evaluation methods to determine the ecacy of the interaction from a human point of view
References
[1] Michel Beaudouin-Lafon and Wendy E. Mackay. Reification, polymorphism and reuse : Three principles for designing visual interfaces. In Proceedings of the Working Conference on Advanced Visual Interfaces, AVI'00, page 102109, New York, NY, USA, 2000. Association for Computing Machinery.
[2] Vincent R. Brown and Paul B. Paulus. Making group brainstorming more eective : Recommendations from an associative memory perspective. Current Directions in Psychological Science, 11(6) :208-212, 2002.
[3] Hernan Casakin and Georgi V. Georgiev. Design creativity and the semantic analysis of conversations in the design studio. International Journal of Design Creativity and Innovation, 9(1) :61-77, 2021.
[4] Vegard Engen, J Brian Pickering, and Paul Walland. Machine agency in human-machine networks; impacts and trust implications. In International Conference on Human-Computer Interaction, pages 96-106. Springer, 2016.
[5] Géry Casiez Eva Mackamul and Sylvain Malacria. Clarifying and dierentiating discoverability. HumanComputer Interaction, 0(0) :1-26, 2024.
[6] Steve Garner and Deana McDonagh-Philp. Problem interpretation and resolution via visual stimuli : the use of mood boards' in design education. Journal of Art & Design Education, 20(1) :57-64, 2001.
[7] Milene Gonçalves, Carlos Cardoso, and Petra Badke-Schaub. Inspiration choices that matter : the selection of external stimuli during ideation. Design Science, 2, 2016.
[8] Nanna Inie and Peter Dalsgaard. A typology of design ideas. In Proceedings of the 2017 ACM SIGCHI Conference on Creativity and Cognition, pages 393-406. ACM, 2017.
[9] Janin Koch and Antti Oulasvirta. Group cognition and collaborative ai. Human and Machine Learning : Visible, Explainable, Trustworthy and Transparent, pages 293-312, 2018.
[10] Janin Koch, Nicolas Tan, Michel Beaudouin-Lafon, Markku Laine, Andrés Lucero, and Wendy Mackay. ImageSense : An Intelligent Collaborative Ideation Tool to Support Diverse Human-Computer Partnerships. Proceedings of the ACM on Human-Computer Interaction, 4(CSCW1) :1-27, May 2020.
[11] Nicholas W. Kohn, Paul B. Paulus, and YunHee Choi. Building on the ideas of others : An examination of the idea combination process. Journal of Experimental Social Psychology, 47(3) :554-561, 2011.
[12] Tomas Lawton, Francisco J Ibarrola, Dan Ventura, and Kazjon Grace. Drawing with reframer : Emergence and control in co-creative-ai. In Proceedings of the 28th International Conference on Intelligent User Interfaces, IUI'23, page 264277, New York, NY, USA, 2023. Association for Computing Machinery.
[13] Q. Vera Liao, Hariharan Subramonyam, Jennifer Wang, and Jennifer Wortman Vaughan. Designerly understanding : Information needs for model transparency to support design ideation for ai-powered user experience. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, CHI'23, New York, NY, USA, 2023. Association for Computing Machinery.
[14] Inês Lobo, Janin Koch, Jennifer Renoux, Inês Batina, and Rui Prada. When should i lead or follow : Understanding initiative levels in human-ai collaborative gameplay. In Proceedings of the 2024 ACM Designing Interactive Systems Conference, DIS'24, page 20372056, New York, NY, USA, 2024. Association for Computing
Machinery.
[15] Inês Lobo, Janin Koch, Jennifer Renoux, Inês Batina, and Rui Prada. When should i lead or follow : Understanding initiative levels in human-ai collaborative gameplay. In Proceedings of the 2024 ACM Designing Interactive Systems Conference, pages 2037-2056, 2024.
[16] Wendy Mackay. Responding to cognitive overload : Co-adaptation between users and technology. Intellectica, 30, 07 2000.
[17] Xiaohan Peng, Janin Koch, and Wendy Mackay. FusAIn : Composing generative ai visual prompts using pen-based interaction. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems.
ACM, 2025.
[18] Xiaohan Peng, Janin Koch, and Wendy E Mackay. Designprompt : Using multimodal interaction for design exploration with generative ai. In Proceedings of the 2024 ACM Designing Interactive Systems Conference, pages 804-818, 2024.
[19] Jeremy Roschelle, Stephanie D Teasley, et al. The construction of shared knowledge in collaborative problem solving. In Computer-supported collaborative learning, volume 128, pages 69-197, 1995.
[20] R Keith Sawyer. Group creativity : Music, theater, collaboration. Psychology Press, 2014.
[21] R Keith Sawyer and Stacy DeZutter. Distributed creativity : How collective creations emerge from collaboration. Psychology of aesthetics, creativity, and the arts, 3(2) :81, 2009.
[22] Joon Gi Shin, Janin Koch, Andrés Lucero, Peter Dalsgaard, and Wendy E Mackay. Integrating ai in human- human collaborative ideation. In Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, pages 1-5, 2023.
[23] Pao Siangliulue, Kenneth C. Arnold, Krzysztof Z. Gajos, and Steven P. Dow. Toward collaborative ideation at scale : Leveraging ideas from others to generate more creative and diverse ideas. In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work; Social Computing, CSCW'15, page 937945, New York, NY, USA, 2015. Association for Computing Machinery.
[24] James Surowiecki. The wisdom of crowds : Why the many are smarter than the few and how collective wisdom shapes business. Economies, Societies and Nations, 296(5), 2004.
[25] Kai Wang and Jerey V Nickerson. A literature review on individual creativity support systems. Computers in Human Behavior, 74 :139-151, 2017.
[26] Blake Williford, Samantha Ray, Jung In Koh, Josh Cherian, Paul Taele, and Tracy Hammond. Exploring creativity support for concept art ideation. In Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, CHI EA'23, New York, NY, USA, 2023. Association for Computing Machinery.
[27]J.D. Zamfirescu-Pereira, Richmond Y. Wong, Bjoern Hartmann, and Qian Yang. Why Johnny Can't Prompt : How Non-AI Experts Try (and Fail) to Design LLM Prompts. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, CHI'23, pages 1-21, New York, NY, USA, April 2023. Association for Computing Machinery.
Avantages
- Subsidized meals
- Partial reimbursement of public transport costs
- Leave : 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
- Possibility of teleworking and flexible organization of working hours
- Professional equipment available (videoconferencing, loan of computer equipment, etc.)
- Social, cultural and sports events and activities
- Access to vocational training
- Social security coverage
Rémunération
2200 € per month
Bienvenue chez INRIA
A propos d'Inria
Inria est l'institut national de recherche dédié aux sciences et technologies du numérique. Il emploie 2600 personnes. Ses 215 équipes-projets agiles, en général communes avec des partenaires académiques, impliquent plus de 3900 scientifiques pour relever les défis du numérique, souvent à l'interface d'autres disciplines. L'institut fait appel à de nombreux talents dans plus d'une quarantaine de métiers différents. 900 personnels d'appui à la recherche et à l'innovation contribuent à faire émerger et grandir des projets scientifiques ou entrepreneuriaux qui impactent le monde. Inria travaille avec de nombreuses entreprises et a accompagné la création de plus de 200 start-up. L'institut s'eorce ainsi de répondre aux enjeux de la transformation numérique de la science, de la société et de l'économie.
- Villeneuve-d'Ascq - 59
- CDD
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