Essay: Felix Dölker
Extended Creativity:
a Human Centered Approach to Working with AI
JUL 2024
In the design field, the integration of Artificial Intelligence (AI) has sparked numerous discussions about its impact on creativity and creative work (Ali & Elzeni, 2024). As AI continues to permeate various industries, including design, it is crucial to explore its significance within specific frameworks such as Andy Clark and David Chalmers’ (1998) “Extended Mind Thesis”. This allows for a re-evaluation of our perspective on AI and its growing role in creativity. The novel concept of “Extended Creativity” briefly explored in this essay aims to offer an interpretation of the potential for Human-AI Co-Creativity to shape the future of design.
In their “Extended Mind Thesis” Andy Clark and David Chalmers suggested that the mind is not solely confined to the brain or body but can extend beyond the body and into the external environment, including tools and technologies that we interact with. As an example, they cite the case of Otto, who suffers from Alzheimer's disease and records new information he learns in a notebook. This notebook acts as an extension of his biological memory, allowing him to supplement his fading internal cognitive abilities with external resources. Clark and Chalmers argue that this external memory is no different, in principle, from biological memory. This idea can be extended to other tools, such as calculators, computers, smartphones or the internet, ultimately leading to transhumanistic ideas of technologically augmenting the human body itself.
In 2019, Alice C. Helliwell took up the original idea of Clark and Chalmers, applied it to artificial intelligence and argued that the extension of the human mind through AI does not contradict the original theory (Helliwell, 2019). Now, as AI begins to serve as a powerful avenue to extend the creative capacity of human designers, it is essential to consider whether it merely functions as a tool (Botha, 2019; Xiao 2024), or if it could indeed represent an extension of the human mind, embodying what we might term Extended Creativity. In 2017 Jonathan Hook and Sebastian Detering proposed the term of Mixed-Initiative Creative Interfaces (MICI) (Deterding et al. 2017) as part of a Workshop in the context of game design but since extended their research to other creative domains (Library of Mixed-Initiative Creative Interfaces). MICIs “[…] put human and computer in a tight interactive loop where each suggests, produces, evaluates, modifies, and selects creative outputs in response to the other.” This results in a process that can be described as Mixed-Initiative Co-Creativity (Liapis et al., 2016): a symbiotic—though arguably not concious on both sides—relationship between humans and computer systems in which humans benefit from the availability of vast cognitive capabilities and the AI by being able to learn and improve. In a more recent article Wu et al. conclude that “[…] focusing on the collaboration with AI will benefit us far more than dwelling on the competing against AI” (Wu et al., 2021). Human-AI Co-Creativity embodies the collaborative partnership between humans and AI in the design process by using AI to assist designers in generating ideas, analyzing data, facilitating decision-making, and tailoring content. This collaboration not only enhances creative output but also democratizes creativity, making it “[…] more accessible and more inclusive than ever.” (Wu et al., 2021)
Human-AI Co-Creativity and Design
The American Psychological Association defines creativity as “The ability to produce or develop original work, theories, techniques, or thoughts.“ By this definition creativity can be seen as merely a tool that is not necessarily linked to humans. While humans may arguably be the most creative species other animals, too, show creative behaviour (Laland, 2020). Thus it can be argued that non biological systems could exhibit creativity.
Amidst the large-scale integration of AI in creative workflows to effortlessly generate text, images, audio and even video, concerns may arise about the relevance of human designers in the future. However, it's essential to recognize that creativity is just one facet of the multidimensional design processes we describe and implement today (Bobbe et. al 2016). Design is inherently holistic and human-centered, emphasizing the importance of human input in understanding context, emotions, and cultural nuances. Moreover, history has shown that design as a discipline evolves alongside technological advancements, constantly adapting and innovating in response to change. As Alfonso Montuori highlights in the Encyclopedia of the Sciences of Learning, “[a] new emphasis on ‘everyday’ and ‘social’ creativity is shifting the focus from individual genius […] to collaborative creativity in everyday life […]” (Montuori &Alfonso, 2012). This makes abundantly clear that it is imperative for the field to understand the role AI can—and will—play in design processes and workflows to be able to define the future roles of human designers. It is important to clearly identify areas of human expertise, develop new skills and competencies, create more efficient workflows, and enhance human-AI collaboration, thereby ensuring that human designers stay relevant in an AI-augmented design landscape.
What do you think about this revision: Human-AI Co-Creativity can be seen as a perspective to holistically integrate the technology into today's processes, creating powerful synergies. For example, AI can aid research, the creation of briefings, customer personas, as well as help with design conception by rapidly generating countless iterations. However, to fully leverage the potential of AI, designers must actively seek out opportunities to tailor these tools to their specific needs and workflows, rather than simply relying on AI products offered by companies thus potentially limiting their scope. By doing so, designers can create customized AI solutions that augment their unique strengths and working styles, unlocking new levels of creativity and productivity.
Ethical and Legal Considerations
Beyond technological advancements, it's necessary to address ethical and legal considerations surrounding AI in design. As AI influences decision-making processes and generates content, issues of bias, privacy, and accountability, plagiarism come to the forefront. Designers must advocate for responsible AI usage, championing transparency, fairness, and inclusivity. It is however vital to keep in mind that the ongoing transformation does not only affect the design discipline and needs a much broader discourse, involving policymakers, industry leaders, educators, and the general public to ensure that the development and deployment of AI aligns with societal values and promotes a more equitable and sustainable future.
Regulatory frameworks like the EU AI Act (2024) set a comprehensive framework for the development and deployment of trustworthy AI in Europe. The Act aims to address the risks associated with AI, including bias, privacy, and accountability. By providing clear requirements and obligations for AI developers and deployers, the Act seeks to ensure that AI systems respect fundamental rights, safety, and ethical principles. The Act's risk-based approach categorizes AI systems into four levels of risk, with stricter obligations for high-risk applications, such as those used in critical infrastructures, education, and law enforcement.
Furthermore ethical guidelines like the “Manifesto for Collaboration” proposed by Vinchon et al. (2023) and modeled after Isaac Asimov’s “Three Laws of Robotics” (1950) need to be discussed, ensuring alignment of AI with societal values and ethical principles. In their manifesto, they propose four laws that cover plagiarism, harmful content, human-AI collaboration, and transparency in AI-generated content, thereby promoting responsible AI development and use.
Rethinking the Concept of Creativity
The proposed concept of “Extended Creativity” within the framework of the Extended Mind Thesis (Clark & Chalmers 1998) offers a compelling perspective on the integration of AI in design, emphasizing the importance of keeping the human at the center of the creative process. By viewing AI as an extension of human creativity, rather than a replacement, we preserve the essential role of human agency and ingenuity in design.
AI serves as a powerful tool to augment human cognitive abilities, allowing the exploration of new avenues of creativity and problem-solving. However, it is crucial to recognize that AI today operates within the parameters set by humans, reflecting their intentions, values, and creative vision. In this way, AI becomes a collaborator and enabler, rather than a substitute for human creativity.
The symbiotic relationship between humans and AI, exemplified by concepts such as Mixed- Initiative Creative Interfaces (MICI) (Deterding et al., 2017) and Human-AI Co-Creativity (Liapis et al., 2016), underscores the idea that creativity emerges from the dynamic interaction between human intuition, expertise, and AI-driven insights. Designers can leverage AI to amplify their creative potential, while AI benefits from human guidance and contextual understanding.
Furthermore, by embracing AI as Extended Creativity, designers reaffirm their central role in shaping the design process and outcomes. Human skills such as empathy, intuition, and cultural sensitivity remainin dispensable, guiding the interpretation of AI-generated insights and ensuring that designs resonate with human needs and values.
In conclusion, the concept of Extended Creativity offers a human-centered approach to integrating AI in design, emphasizing the collaborative partnership between humans and technology. By acknowledging AI as an expansion of human creativity, designers can harness its potential to expand their creative horizons while maintaining control over the design process. This perspective reinforces the importance of human agency, intuition, and ethical responsibility in navigating the evolving landscape of AI in design. As we continue to explore the possibilities of AI-enabled creativity, it is essential to remain mindful of the unique contributions that humans bring to the design process and strive towards creating inclusive, meaningful, and ethically responsible designs that enrich the human experience.
BODY OF KNOWLEDGE
Felix Dölker is a designer, university teacher and creative researcher. Together with Florian Schunck he founded the design studio schunck dölker in 2015. He is a board member of the Deutscher Werkbund Hessen e.V. that connects the perspectives of design, architecture, industry and sciences and promotes a focus on quality. In his research Felix Dölker focuses on applications of AI in design workflows with a focus on finding meaningful integrations into a wide range of design processes.
→ felixdoelker.de
→ huggingface.co/414design
→ github.com/414design
→ civitai.com/user/414design
Felix' recommendations for further reading and listening
Aktive Community mit Focus auf Stable Diffusion:
→ reddit.com/r/StableDiffusion/
Hörsaal - Deutschlandfunk Nova: Philosophie – KI kann Kunst! ... oder doch nur Kitsch?
→ deutschlandfunknova.de/beitrag/philosophie-ki-kann-kunst-oder-doch-nur-kitsch
Hörsaal - Deutschlandfunk Nova: Technikphilosophie - Künstliche Intelligenz und Verantwortung
→ deutschlandfunknova.de/beitrag/technikphilosophie-kuenstliche-intelligenz-und-verantwortung
Hörsaal - Deutschlandfunk Nova: Künstliche Intelligenz - Akteur oder Werkzeug?
→ deutschlandfunknova.de/beitrag/kuenstliche-intelligenz-ist-die-ki-akteurin-oder-werkzeug
Lakonisch Elegant: Künstliche Intelligenz - Veränderst Du wirklich die Welt, ChatGPT?
→ deutschlandfunkkultur.de/lakonisch-elegant-kulturpodcast-164.
Lakonisch Elegant: Algorithmen, KI & Co. - Geht das Internet gerade kaputt?
→ deutschlandfunkkultur.de/geht-das-internet-gerade-kaputt
Design Better: Bonus: AI and the Creative Process
→ designbetterpodcast.com/p/bonus-ai-and-the-creative-process
KI – und jetzt? Wie wir Künstliche Intelligenz leben wollen: Desinformation als Risiko – Demokratie und Künstliche Intelligenz
→ rbb-online.de/ki-und-jetzt/episoden/ki-und-jetzt
Die sogenannte Gegenwart: Ich bin doch selber nur Software
→ zeit.de/serie/die-sogenannte-gegenwart
Künstliche Intelligenz: Kreativität braucht weiterhin Menschen hinter der KI
→ kuenstlicheintelligenz.podigee.io/20-neue-episode
References
Ali, Basma Nashaat & Elzeni, Mostafa (2024) Ai-Acd: A Proposed Workflow of Ai-Powered Architectural Computational Design Process. Available at
→ SSRN: https://ssrn.com/abstract=4691649 or
→ https://dx.doi.org/10.2139/ssrn.4691649
Botha, Marc (2019, January 21). Artificial Intelligence is just a Tool, accessed 28 February 2024,
→ Artificial Intelligence is just a Tool | by Marc Botha | Towards Data Science
Xiao, L., Wu, Q. (2024). From Auxiliary Design Tools to Intelligent Collaborative Partners: The Transformation of the Relationship Between Design and Computing. In: Stephanidis, C., Antona, , Ntoa,S., Salvendy, G. (eds) HCI International 2023 – Late Breaking Posters. HCII 2023. Communications in Computer and Information Science, vol 1958. Springer, Cham.
→ https://doi.org/10.1007/978-3-031-49215-0_12
Deterding, S., Hook, J., Fiebrink, R., Gillies, M., Gow, J., Akten, M., Smith, G., Liapis, A., & Compton, K. (2017). Mixed-Initiative Creative Interfaces. In Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors inComputing Systems (CHI EA '17). Association for Computing Machinery, New York, NY, USA, 628–635.
→ https://doi.org/10.1145/3027063.3027072
Library of Mixed-Initiative Creative Interfaces, accessed 28 February 2024,
→ http://mici.codingconduct.cc/
Liapis, A, Yannakakis, G.N., Alexopoulos, C., & Lopes, P.L. (2016). Can Computers Foster HumanUsers’ Creativity? Theory and Praxis of Mixed-Initiative Co-Creativity. Digital Culture & Education, 8.
Wu, Zhuohao & Ji, Danwen & Yu, Kaiwen & Zeng, Xianxu & Wu, Dingming & Shidujaman, Mohammad. (2021). AI Creativity and the Human-AI Co-creation Model.
→ https://doi.org/10.1007/978-3-030-78462-1_13.
American Psychological (n.d.). Creativity. In APA Dictionary of Psychology, accessed June 17, 2024, from
→ APA Dictionary of Psychology
Laland, Kevin (2017, April 20) These amazing creative animals show why humans are the most innovative species of all. The Conversation.
→ https://theconversation.com
Bobbe, T., Krzywinski, J., & Woelfel, C., (2016). A Comparison of Design Process Models from Academic Theory and Professional Practice.
→ https://www.designsociety.org/download-publication/38931
Montuori, Alfonso (2012). Creativity and Its In Encyclopedia of the Sciences of Learning (1st ed., p. 837). Springer New York.
→ https://doi.org/10.1007/978-1-4419-1428-6
Vinchon, F., Lubart, T., Bartolotta, S., Gironnay, V., Botella, M., Bourgeois-Bougrine, S., Burkhardt, -M., Bonnardel, N., Corazza, G.E., Glăveanu, V., Hanchett Hanson, M., Ivcevic, Z., Karwowski, M., Kaufman, J.C., Okada, T., Reiter-Palmon, R. & Gaggioli, A. (2023), Artificial Intelligence & Creativity: A Manifesto for Collaboration. J Creat Behav, 57: 472-484.
→ Artificial Intelligence & Creativity: A Manifesto for Collaboration - Vinchon - 2023 - The Journal of Creative Behavior - Wiley Online Library
Asimov, Isaac (1950). “Runaround“. I, Robot (The Isaac Asimov Collection ed.). New York City: Doubleday. p. 40.
→ ISBN 978-0-385-42304-5.
Sabeth's podcast recommendation
Sabeth first came into contact with the idea of a symbiosis between AI and humans in the podcast "Search Engine". The episode "Who should be in charge of AI?" is about OpenAI and - of course - also briefly features Elon Musk, who touches on the concept.
→ https://open.spotify.com/episode
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