Professor of Creative and Entertainment Games @ Breda University of Applied Sciences (BUas)
My professorship and team work on topics related to the content, creation, and cultural context of artistic and commercial video games. Within this broad range, we typically address topics related to narrative, intersectional themes (including accessibility, gender, and more), user interface, and how game tech contributes to other industries, such as with game engines driving virtual production filmmaking.
In the AICI project, my team is looking at the intersection between AI and storytelling tools, specifically at the storyboarding stage. There are many challenges, both technical and ethical, to consider when attempting to make generative AI a responsible tool in assisting (not replacing) storyboard artists. We’re primarily diving into the technical side, but always driven by ethical considerations, such as sourcing of training data with respect for copyright and energy usage.
As a writer across several forms of media, I’m both excited and cautious about generative AI. Finding ways that it can serve storytelling industries and artists could improve the on ramp for new creators and optimize the workflow for existing creatives. There are numerous limitations to generative AI, and explicitly confronting these is a fascinating challenge. As with all research, the driving question is ‘is this even possible at the moment?’, and I’m very curious to see the results from the approach we’re taking.
Graduate of the ArtFX school
Graduate of the ArtFX school, Nicolas Counil has made Unreal Engine his tool of choice. A lover of new technologies, his already rich career path has led him to work on projects ranging from video games to series and virtual production.
He has worked on Constellaiton on Apple TV+ and Mario + Rabbids: Sparks of Hope for Ubisoft and Fortnite for Epic Games.
Nicolas now works freelance, dividing his time between production and teaching, currently at ArtFX and main developer at Maboroshi Artworks.
As an independent game developer in AICI project, leveraging generative AI has become an essential aspect of my workflow, allowing me to push creative boundaries, optimize development processes. Generative AI accelerates the prototyping phase of development. I can create concept art by transforming simple sketches into polished visuals, refine character designs and iterate quickly based on AI-generated suggestions.
While generative AI has significantly enhanced my capabilities, it also comes with challenges. Ethical considerations like ensuring the originality regarding art and copyright of AI-generated content and avoiding unintentional biases in AI-driven narratives are critical. I actively work to strike a balance between leveraging AI’s potential and maintaining creative integrity.
Professor of Creative and Entertainment Games @ Breda University of Applied Sciences (BUas)
My professorship and team work on topics related to the content, creation, and cultural context of artistic and commercial video games. Within this broad range, we typically address topics related to narrative, intersectional themes (including accessibility, gender, and more), user interface, and how game tech contributes to other industries, such as with game engines driving virtual production filmmaking.
In the AICI project, my team is looking at the intersection between AI and storytelling tools, specifically at the storyboarding stage. There are many challenges, both technical and ethical, to consider when attempting to make generative AI a responsible tool in assisting (not replacing) storyboard artists. We’re primarily diving into the technical side, but always driven by ethical considerations, such as sourcing of training data with respect for copyright and energy usage.
As a writer across several forms of media, I’m both excited and cautious about generative AI. Finding ways that it can serve storytelling industries and artists could improve the on ramp for new creators and optimize the workflow for existing creatives. There are numerous limitations to generative AI, and explicitly confronting these is a fascinating challenge. As with all research, the driving question is ‘is this even possible at the moment?’, and I’m very curious to see the results from the approach we’re taking.