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 which proposes creation by some divine act. Both assumptions involve the nature of creativity and change, and ego, And Picasso, like the Muses of Greek mythology, had big egos, all that makes for a good story. But from a scientific perspective, creative 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 Picasso, they well may be operating with substantially enhanced neural processes. Still, for inspiration, a quote from Plato may be valid: 'At the touch of love, everyone becomes a poet'.  *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.”