Creativity: Muses or neurons?

'Every act of creation is first an act of destruction', is a quote attributed to Picasso, words which suggest creating from physical matter, or creatio ex materia . This in contrast to the notion of creating "out of nothing", or creatio ex nihilo. Both assumptions involve the nature of creativity and change, and ego, And Picasso, like the Muses of Greek mythology, had big egos - artistic and Greek deity respectively - all that makes for a good story. But from scientific perspectives, ideas are elements of thought across many levels of physical, chemical, and biological description. Yet neuroscientist Dr. Nancy Andreasen, whose research is about the relationship between creativity and the brain, writes that the brain’s abilities are “near miraculous,” and the process of creating something “is neither easy nor obvious.”. And so, her hypothesis is that the brain begins by disorganising and then making connections between various encoded data which were not previously connected. In other words, our brain is a self-organising system meaning that it could easily be chaos, with quadrillions of living, moving parts (neurons), but it somehow keeps itself in order, not unlike flocks of birds or ant colonies.  Now, if every human being possesses what could be called “ordinary creativity”, which goes back to our basic instincts, then our brains learn, unlearn and relearn to recognise patterns in order to aid in our survival. With "extraordinary creativity", on the other hand, as assumed in the case of Picasso, they well may be operating with substantially enhanced neural processes.  *Andreasen, N. (2005) The Creating Brain - The Neuroscience of Genius. Chicago University Press. 

Unpredictable AI

AI technologies are essentially computational systems and as such fairly well understood among IT professionals. However, from social and cultural perspectives, which necessarily include design processes and outputs, these technologies are poorly understood and, as there is no single definition of AI, have become subject to conjecture, speculation and doublespeak. But there are two primary approaches, probabilistic and deterministic AI with each serve unique functions based on their design and outputs: GenAI systems are probabilistic*. Yet AI's long-term impact on, say, education and the labour market is hard to predict because transformative technologies, such as generative AI, take time to become clear. Moreover, there is uncertainty about how humans, both individually and collectively will respond to AI's societal impact, particularly as the AI industry remains largely unregulated creating vast wealth and power inequalities. Given the unpredictable nature of AI, then, designers need to consider both technology and ethics when applying AI systems. *At a high level, probabilistic AI models uncertainty and provides outcomes based on likelihoods. This means that it doesn’t always offer one definitive answer but instead provides a range of possibilities with associated probabilities. Deterministic AI, on the other hand, is rule-based, designed to yield specific, predictable outcomes without room for variability once given a particular input. https://www.dpadvisors.ca/post/the-basics-of-probabilistic-vs-deterministic-ai-what-you-need-to-know

AI-deation workflow

Artificial intelligence-based software, such as ChatGPT has become an everyday part of designers' workflows, across disciplines and cultures. Using ChatGPT can help generate ideas and develop design concepts and make the ideation process faster and more efficient*. Moreover, AI image generators can save significant amounts of time and money on rendering. Indeed, as the underlying AI technology is getting more powerful exponentially, so are the tools based on the technology. However, ChatGPT responses and outcomes, and the quality of advice and solutions, depend on prompts, custom instructions and context, and while it gets a lot right, it doesn't get everything right. And so, powerful AI tools in the hands of beginners who don't understand what AI is doing are at risk of doing mistakes, and in haste. Therefore, it is good practice to verify anything important before acting on it, especially when it comes to high-stakes decisions. In short, to harness, and fully benefit from the power of AI across design fields require challenging experience and discernment. *Caveat: While complex ideas travel slowly, simple ideas actually travel very fast. However, there's a high amount of variables wrapped up in even the simplest of ideas, if and when we let an idea rest or “sleep on it.”

GenAI and the risk to critical thinking

GenAI, such as ChatGPT, has become immensely popular because the learning models respond to user prompts in a conversational way generating text, images, videos, and so on. That is, GenAI uses machine learning models (LLMs) to learn patterns from existing data, both structured and unstructured, to generate new and innovative content. But innovation needs a critical approach (1), not least in the digital age when transformative or impactful innovation is facilitated if not driven by AI. And so, designers need critical thinking skills in the process of finding a solution to a stated problem (2). But while GenAI is capable of creating new content, can it replace human critical thought and reflection? An online sample study of some 600 participants in the UK, showed that with people employing GenAI tools as substitutes, and not supplements to routine tasks, there is a 'significant negative correlation between the frequent use of AI tools and critical thinking abilities'. Similarly, a US university survey of 1,000 faculty found that GenAI diminishes students’ critical thinking skills and increase over-reliance on AI tools (3). Psychologists call it cognitive offloading when GenAI, offers users "good enough" outcomes that can be attained with minimal effort (4). But such outcome-oriented thinking that focuses on results rather than process may overlook or underestimate human judgement, user education level, design knowledge and experience.   (1) The term critical comes from the Greek word kritikos meaning “able to judge or discern”. (2) https://www.open.edu/openlearn/money-business/making-creativity-and-innovation-happen/content-section-5.2  (3) https://www.universityworldnews.com/post.php?story=20260128145305278  (4) https://www.psychologytoday.com/gb/blog/the-art-of-critical-thinking/202512/is-generative-ai-rewiring-our-brains-heres-how-it-happens

Superior human creativity?

GenAI models, such as ChatGPT use algorithms trained on vast amounts of data from existing work, and then generating their own novel content (texts, images, software code, and music). But are the models really creative in a human sense? Because the models don't "understand" the meaning or context of their creations directly, unlike humans who, generally speaking, show a greater ability to generate and evaluate ideas with great variations due to their unique and detailed training and experiences. For example, research suggests that generative AI–enabled stories are more similar to each other than stories by humans alone (1). That said, GenAI , as a tool, can support and augment human creativity acting as an "intelligent tutor" or "co-creator". So, what's the difference between GenAI and human creativity? Or, do people assume human creativity as being superior to GenAI? (2) Because if creativity is largely remixing parts and recombining thoughts, in which human language plays a major role, GenAI generates content in response to human-written prompts. That is, GenAI generates its outputs by statistically analysing the distribution of words or pixels or other elements in the data that it has been fed. And so, GenAI outcomes are based on likelihoods, hence probabilistic AI. But while GenAI in this manner "mimics" human creativity, it is not an original source of information and doesn't have the same kind of complex directionality as humans with their memories, intuitions, dreams and wishes. In short, GenAI is not an individual being (3). This highlights the ethical and social costs of GenAI harvesting human knowledge from often unidentified sources, that is, without consent or respect for privacy and copyright boundaries. That is, GenAI doesn't give credit to human creativity.  (1) https://pmc.ncbi.nlm.nih.gov/articles/PMC11244532/ (2) Traditionally, the study of the creative person focused on personality traits of creators with different level of achievement and in different domains.  (3) Cf. In the 1999 science fiction film "The Matrix," hacker Neo is faced with a decision. Resistance fighter Morpheus presents him with two pills. If Neo swallows the blue one, everything will remain the same — a comfortable life in a fantasy world. If he swallows the red pill, he will see "true reality" — a dystopian world in which humans are enslaved by machines. 

Choreographing ideas

The word choreography comes from Greek and most commonly refers to dance movement (in the sense, 'written notation of dancing'). Conceptually speaking, choreography is about symbolically designing movement in time and space. But what does it mean in practice? Can the notion of choreography be applied to design and, more specifically to ideation, as in idea sketching? While choreographers often “invent” new ways of moving, choreography transcends movements, and gives them meaning. Similarly, sketching is a performative process and practice that expresses and communicates ideas and give them meaning. And so, designers, like choreographers typically think about the various aspects of the task in hand and whether guided by improvisation or based on a brief. In this pursuit, designers and choreographers alike use a broad and varied range of means, from traditional techniques to experimenting with AI technologies. Regarding choreography as the art of designed movement, choreography is everywhere where movement happens. That is, choreography, in the digital age embraces places, spaces and settings thereby reinventing stage performance and so extending the audience experience. Indeed, theatrical experiences are a classic happening. And so, in its many forms and iterations, choreography - and sketching - can be conceived both as dialectical practice and performance that, though disruptive in character, is constructive in outcome gesturing towards a state of being-without-limit.  https://www.dance-masterclass.com/blog/what-does-a-choreographer-do

 

Dialogic ideation

One of the many approaches to design ideation takes the form of dialogue, or interactive communication between two or more designers, or between the designers, clients and users (co-design). The dialogue, or conversation, however, as an experience of human interaction, is rarely just a rational exchange of ideas. More often than not it involves the participants' attitudes, motivations and feelings when faced with, and responding to a given situation or problem as typically articulated in the design brief.. The dialogue, or exchange of first thoughts and ideas, then, creates and presents scenarios or narratives that triggers emotional responses in the stakeholders. Moreover, in AI-facilitated design, the dialogue highlights the role of designers to take responsibility and accept accountability for limiting any negative impact of AI, notably in terms of AI ethics. Additionally, the emotional content in what may called dialogic ideation, may act as a prologue to designing for emotion when, as in, say, product design, the user experience is core.