The dynamic of AIdeation

While current AI systems are heralded as collaborators, they are fundamentally short-sighted – optimised for providing instant and complete responses. Similarly, idea generation powered by AI chatbots, is capable of providing diverse and innovative outcomes at speed. But what are the consequences of this dynamic?  That is, the rapid rise of AI chatbots, promises immediate and effective help with a range of cognitive tasks, from studying and writing to image generation and brainstorming. But what happens to users’ own abilities when the AI is not available? A study* provided causal evidence for two key consequences of AI assistance: reduced persistence and impairment of unassisted performance. Across a variety of tasks, including mathematical reasoning and reading comprehension, the research found that although AI assistance improves performance in the short-term, people perform significantly worse without AI and are more likely to give up. Notably, these effects emerge after only brief interactions with AI (∼10 minutes). These findings are particularly concerning because persistence is foundational to skill acquisition and is one of the strongest predictors of long-term learning. This goes for creativity too, which is a skill that can be learned and developed. The study submits that persistence is reduced because AI conditions people to expect immediate answers, thereby denying them the experience of working through challenges on their own. These results suggest the need for AI model development to prioritise long-term competence alongside immediate task completion. *https://arxiv.org/pdf/2604.04721

GenAI bias

The learning objective of the workshop is to raise awareness of design ideation and provide participants with an opportunity to reflect on their own design practice through the use of ideation tools, including ChatGPT, a generative AI tool. GenAI visual and textual output, however, tends to downplay bias embedded in the content absorbed from its training data which reflect mainly western cultural, scientific and political contexts. Indeed, such bias reflects how design, as discipline, is drawing predominantly from western, educated, and democratic societies. Moreover, GenAI input, or prompts often reveal users own cultural assumptions and biases. That is, assumptions and biases can be hidden in the written prompts. The interactions between users and GenAI tools, then, highlight the need for users to critically interrogate the diversity of GenAI output, that is, question its trustworthiness. Practising ideation, then, calls for cultural sensitivity and critical intelligence.

Places and spaces for ideas

Although ideation is situated not only in the design studio, but in many "other places", the traditional studio represents a place, space and setting where designers typically ideate through sketching, building physical models and proposing projects in a shared creative environment. Indeed, in the context of education, the studio embodies the creative learning process where, moreover, there is no clear border between theory and practice. But in the digital age, designers, both in professional practice and education are experiencing how studio practices are changing effected by hardware and software choices and the use of online platforms and AI technologies. And so, the concept of the studio is changing too, including both physical and virtual settings. However, designers, as problem solvers, are apt at adjusting to new materials and technologies, changing conditions and methods resulting in the networked, hybrid design studio that bridges the physical and virtual worlds of creativity.

Human-AI symbiosis

Generative AI, such as ChatGPT, opens up new perspectives for designers by offering them unprecedented technical, performative and aesthetic possibilities. Indeed, GenAI is transforming design ideation and communication. But how does GenAI differ from classic human creativity? Research suggests that the answer lies not so much in difference as in symbiosis*. That is, designers and GenAI work together to jointly solve problems and perform specific tasks. That is, by facilitating ideation and broadening the field of possibilities, GenAI provides designers with a creative platform to more quickly produce, say, sketches, prototypes or different strategies to develop a given theme↟. Human - AI symbiosis, then, has the advantage of combining the power of AI with the human domain expertise to improve performance and create added value, particularly for commercial purposes. But more than this, GenAI can hallucinate and create things that do not exist beforehand. GenAI, then, as an agent for change, raises important concerns, such as the question of the originality and authenticity of the works generated, the question of responsibility and transparency in the creative process, copyright and intellectual property, or even the risks of manipulation. * https://dl.acm.org/doi/10.1145/3542698  ↟ https://www.sorbonne-universite.fr/en/news/when-art-meets-artificial-intelligence

Generating ideas with everyday materials

In the context of design ideation, an 'idea' is understood as a basic element of thought that can be either visual, concrete or abstract. An example of a designer who thinks in terms of concrete ideas is Philippe Malouin, who is experimenting and making things out of any available everyday material. Taking an instinctive approach to design, that is, not to think too much in front of a computer, the London-based designer lets the function and the materials influence the creative process. For example, on the theme of sustainability, and based on his salvaging practice, Malouin looks at the waste streams and modify them in order to make a new product, In this way, he has created 68 design products from junk steel. Also, starting with a very open project brief, and with a minimum of intervention, Malouin says he is trying to demystify the creative process.  https://philippemalouin.com/

The shape of things: AI in design

AI is becoming an essential part of designers' tool set in generating images, models, design options and other forms of data. And this often by just a few keyboard prompts and clicking the AI button. However, the ease and flexibility of using AI, from the perspective of individualism and psychology, can be either positive, that is, it enhances creativity with less mental stress (cognitive offloading), or negative, that is, it risks over-reliance on algorithmic feedback (cognitive overloading). This paradox suggests the need to fully consider the design process - from first thoughts to final outcome - as a human experience while acknowledging that AI is both co-creator and design material in the process - not just a tool. That is, as our tooling shapes us, so does AI. Over-dependence on AI, then, may privilege the finished product over the design process. This highlights designer responsibility to think critically of the ethical, cultural, and creative implications of AI.  https://www.riba.org/work/insights-and-resources/professional-features/ai-professional-features/what-can-architects-learn-from-an-ai-in-education-report/

Design and artificial creativity

As AI infiltrates the world, design, as a discipline stands at the threshold of yet another paradigm shift. That is, can AI-driven ideation not only compete with but exceed human ideation, particularly for "routine" problem solving?* In this challenge, designers are exploring multiple directions and pathways while considering AI's creative role as well as its societal impact. It is a hybrid (analogue-digital) creative process which largely simulates human creativity although lacking several characteristics of it.† The design studio, then, is not a confined physical space for drawing and model making but a hybrid practise which blends traditional in-person studio experiences and computer simulations. The hybrid model, moreover, overcomes disciplinary boundaries using combinations of data (structured and unstructured), culture (man-made and biological), matter (organic and inorganic) and technology (analogue and digital) that stimulate and generate new creative perspectives which, in turn, impact ideation itself. Indeed, a paradigm shift. *‘Aha, I know what is going on here and this is what I need to do to figure out the answer.’ reaction to the problem. †AI does not use the same process as a human does when that human is thinking creatively. https://www.sciencedirect.com/science/article/pii/S2713374523000225