Are you a junior researcher (Master's+) working on #computationalcreativity? I'm organising the Early Career Symposium (ECS) at ICCC2016 - join us to present and discuss your projects and career questions. DL for extended abstract: May 15th. More info: computationalcreativity.net/iccc26/early...
Interested in interpretative qualitative research synthesis as a methodology for HCI research or in GenAI's impact on game development specifically? Seek me out at #chi2026 / presentation Tue morning: programs.sigchi.org/chi/2026/pro...
Interested in applying? Now is the time! DL: Fri 3.4.2026. The job ads have now been updated with a Q&A section, collecting many questions that I've received thus far.
(8/8) Fantastic collaboration with @axternar.bsky.social @aakoo.bsky.social @sevenfridays.bsky.social @jmacunha.bsky.social at universities @aalto.fi @ucoimbra.bsky.social @york.ac.uk . Meet us at CHI!
(7/) We contextualise the adoption of GenAI within larger trends in game industry & provide rigorous methodological detail and reflexivity on meta-ethnography as a yet underexplored method in HCI.
(6/) NB: our findings derive from studies scattered over time -> must not be understood as a snapshot of the present. We recommend using them, combined w the identified research gaps, to guide up-to-date research within the specific context of interest for advancing policy or practice.
(5/) What makes adoption fragile: risks around originality, ownership, labour precarity & need for provenance to be embedded in workflows. We argue governance is not an optional overhead; GenAI reshapes authorship and can drive stylistic convergence if left unchecked.
(4/) Efficiency claims are contested & conditional: speed-ups are task-/phase-dependent, and often eroded by configuration, verification, and integration overhead. Pipeline fit is real bottleneck: current tools rarely fit production requirements w/o adapters, acceptance criteria & evaluation gates.
(3/) Existing qualitative studies suggest that GenAI’s strongest value is upstream: ideation and exploratory prototyping, not end-to-end authorship. Across studies, the shared conclusion is that systems broaden option spaces but humans still frame, judge, and steer what becomes “the work”.
(2/) A consistent finding across the corpus is that human-in-the-loop refinement is the production norm. Generative outputs behave like provisional artefacts: teams iterate, curate, correct, and integrate, and prompting becomes progressive specification work rather than a one-shot query.
(1/) Accepted to CHI’26: 1st qualitative research synthesis on the impact of GenAI - here on game development (2020-25). Core contributions: meta-ethnography integrating 10 studies -> 9 themes + industry context + recommendations for practice, research & governance. doi.org/10.48550/arXiv.2509.11898
The Autotelic Interaction Research Group (AIR; www.autotelic.science) is part of @aalto.fi @csaalto.bsky.social, a unique hub of world-class artistic and scientific research and @ellis.eu institute Finland!
Picture: Tania Candiani - Subterra (Subterranean), 2025. Helsinki Biennial.
A fantastic opportunity to join a creative, open-minded research group just outside Helsinki in the happiest country on earth + to work with fantastic researchers worldwide, e.g. collaborators Tom Froese (OIST), @jon-mcc.bsky.social (Monash University) & Takashi Ikegami (University of Tokyo).
Critical at its core, the ACAI project seeks to identify alternative and sustainable paths to "mainstream" creative AI. Rather than optimizing systems to replicate established human aesthetics or processes, we investigate the conditions under which AI might operate as a genuinely creative agent.
Jobs! The Autotelic Interaction Research Group is looking for (1) creative practitioners and (2) theory researchers to work on "Autotelic Creative Artificial Intelligence" (ACAI):
(1) PhD in Creative Practices (2+2 years): lnkd.in/dPBG47rM
(2) Postdoctoral Researcher (2 years): lnkd.in/dMisM_bf
(6/6) A collaboration with Niki Pennanen and @robinwelsch.bsky.social, complementing our prior work on robots here: dl.acm.org/doi/full/10..... Supported by The Finnish Doctoral Program Network in Artificial Intelligence (AI-DOC) & Research Council of Finland (371202). @aalto.fi @csaalto.bsky.social
(5/) Further analyses in paper + qualitative comments highlight many differences in how the process was perceived. Design implication: process visualizations are not a universal “creativity boost” button. They can backfire for some audiences unless paired with context or adapted to user background.
(4/) The story gets interesting with individual differences: Amongst others, AI literacy moderated the effect with lower literacy -> process tended to lower creativity ratings; higher literacy -> process tended to raise them.
(3/) Prolific participants were UK census-representative (N=298+295). The headline Study 1 result: process visibility did NOT increase perceived creativity on average. Study 2 sought to “help” the process animation by adding a tutorial on diffusion: still no tutorial/PE/interaction effects!
(2/) We studied this in two preregistered online studies with text-to-image outputs (Stable Diffusion), manipulating Perceptual Evidence (PE): Product (final image only) vs Product+Process (30s denoising animation, then the final image).
(1/) Does visualizing an AI’s image generation process make people judge it as more “creative”? Our ACM IUI'26 paper shows that the "who" of the observer can matter more than what the interface reveals. Preprint: doi.org/10.31234/osf...
5/5 Collaboration between @aalto.fi and @oistedu.bsky.social, supported by Aalto Science Institute (ASci) and the Helsinki Institute for Information Technology (HIIT).
4/5 This work contributes to a young research agenda seeking to understand creativity beyond the realm of humans or highly developed animals. We argue for the SO model as a fascinating candidate to study the effect of learning on creativity from the bottom up - in life as it is and as it could be.
3/5 More specifically, we demonstrate that modifying the SO model learning parameters gives rise to four different regimes that can account for both creative products and inconclusive outcomes, thus providing a framework for studying and understanding the creative potential of learning systems.
2/5 Developed to model complex adaptive systems in ALife and advocated as a candidate for minimal agency, the Self-Optimization (SO) model can be considered as the 3rd operational mode of the classical Hopfield Network, leveraging the power of associative memory to enhance optimization performance.
1/5 Now in Artificial Life: our research on the creativity of unsupervised learning! Core finding: a simple model of attractor networks with Hebbian learning is sufficient to constitute a (minimal) creative process, yielding creative products as solutions of the optimization. doi.org/10.1162/ARTL...
Read the blog of the Ethics Advisory Board of Finnish Center for Artificial Intelligence about the need to incorporate training and discussions in AI ethics in the AI-related doctoral student's curriculum. fcai.fi/eab-blog/eth... Written together with colleagues listed in the comments.
4/4 Locally, we're part of a rich AI research ecosystem, including the Finnish Center of AI (FCAI), Helsinki Institute for Information Technology (HIIT) @icthiit.bsky.social and the Finnish @ellis.eu institute, a world-class research hub in AI and machine learning.
3/4 You can work w/travel to our fantastic collaborators Natasha Jaques @natashajaques.bsky.social (Washington U./DeepMind), Sebastian Deterding @codingconduct.cc (Imperial College), Christoph Salge @christophsalge.bsky.social & Daniel Polani (UH), & Julian Togelius @togelius.bsky.social (NYU)!
2/4 The AIR group (www.autotelic.science) embraces diversity in research, thought and identity and has a track record of research on (computational) intrinsic motivation, bridging between AI, Psychology and Cognitive Science. Aalto University is 15 min away from Helsinki and surrounded by nature.