• If you are working in a game company you can collaborate with us by allowing us to observe how you collaborate and work together at work, taking part of our survey, and joining us in  

• If you are a student, you can apply to the VIP course or take part in the project as part of your thesis work.

Either way, contact lead of the project Alberto on alberto.alvarez@mau.se

Game design and development is a multidisciplinary field involving a wide range of skills and areas of expertise, making it a great test bed to explore AI supported collaboration given the multifaceted nature of games, and the diverse and heterogeneous skill sets that teams must have.. Game design, for instance, draws on skills and knowledge from fields such as computerscience, art, design, sound, and psychology. The interdisciplinary nature of this project is essential because it brings together a diverse range of perspectives an expertise that are necessary for creating effective and equitable collaborative systems. 

This project focuses on the following research questions:

• RQ1. How does collaboration take place in industry, academic, and casual settings (i.e., which tools are used, organization structures), and how does this differ based on the particular phase of the development process?

• RQ2. How can we develop prototypes to support the needs of users and the overall design process itself, and which slice of the game design and development pipeline will these systems best support?

• RQ3. What roles can the AI take when supporting human collaborative environments and how does it relate to different phases in the design process?

• RQ4. How can these AI-supported systems mesh within existing development

Within the games field, the project will focus on two settings: formal and informal collaboration. Formal collaboration is the main focus of the project, where practitioners are already, to a large extent, collaborating together. Formal collaboration is divided into industry (e.g., AAA game companies, indie dev studios) and academic and learning environments (e.g., classroom settings, conferences). Informal collaboration in casual environments (e.g., game jams, hackathons) will also be explored, as that is an area of collaboration that attracts both industry practitioners and academics/students, but where they do not necessarily have any collaboration already formed. These two settings are interesting to explore since they present distinct but complementary challenges that could inform further solutions.

The project has four phases:

• Phase 1: A comprehensive review to analyse the field and understand how collaboration works in the different target groups. a systematic mapping approach will be utilized to identify and extract themes and concepts from the literature related to human collaboration, and AI- and technology-supported human collaboration in the the area of technology and game design. This phase aims  to provide an overview of the current state-of-the-art on the topic, and to identify particular gaps and opportunities to be explored throughout this project. Further, structured questionnaires will be designed to gather insights on collaborative practices in the aforementioned setups informed by the systematic mapping approach. 

• Phase 2: Co-design workshops will be employed to investigate collaboration within the diverse environments involving academics/students and industry practitioners. This phase aims to continue exploring how collaboration is being conducted and to identify areas where AI can support and enhance the collaborative process. The co-design workshops will be conducted to co-design prototypes that support current collaborative processes and that target different aspects of the design process. The prototypes will be designed in collaboration with the participants to ensure that they meet the specific needs and requirements of the target users. The main goals of the co-design workshops are to design prototypes that enhance current collaborative pipelines, identify which roles AI can take to support collaboration in these environments, and discuss which part of the design and creative process (e.g., ideation, production, prototyping) AI is better suited to assist.

• Phase 3: A set of prototypes will be iteratively developed to support collaboration, and explore the roles of AI as these could be dynamic and changing throughout the use of the prototypes and tools. These prototypes will help to investigate how AI can be leveraged to support and enhance human collaboration. Different AI methods will be explored such as evolutionary computation, ML models, or other rule-based systems. Each would support different goals and employ methods tailored to the group environment and creative process step. These systems incorporating AI will be evaluated through internal assessments to understand the AI behavior when used in-the-wild, and doing multiple user studies and workshop sessions to determine the effectiveness in enhancing collaboration and improving the user experience of the distinct groups. User studies will focus on assessing the usability and expected behavior of the prototypes when designers collaborate together.

• Phase 4: Co-design workshops to discuss the role of AI as mediator and facilitator in group collaboration. The objective of this phase is to explore the potential for enhancing current collaborative pipelines by integrating AI support for human collaboration. Similar to how companies may need to modify their systems and organizations to adopt data-driven solutions, academic and industry environments may also need to adapt their collaboration pipelines to incorporate AI with different roles. The phase aims to identify opportunities to improve productivity and efficiency, as well as foster creativity by exploring and discussing the possibilities of changing collaborative workflows to integrate AI. The co-design workshops will include participants from diverse industries and sectors to ensure that the resulting prototypes are applicable and relevant to a wide range of contexts. Rather than developing prototypes of possible AI systems, the aim is to prototype changes in the collaborative pipeline that can benefit both the AI tool and humans.

Yes!! Our goal is to continuously report our results both at academic conferences, but also to our collaborators and any interested person here in the website!

Our research is open access, meaning that all our publications and outcomes of workshops and studies will be available. We expect to use this website as a hub with all our finding and as a way for others to replicate and better understand how, where, and when to implement AI systems to help in the game design pipeline.