The whole is greater than the sum of its parts

Loosely defined as computer systems performing tasks that typically require human intelligence, AI is developing so fast that within the next 20 years, and according to Geoffrey Hilton, a pioneer on machine learning and neural network algorithms, we’re going to develop AI systems that are smarter than people. Similarly, the historian Yuval Harari, in writing on AI (Nexus, 2024) warns that we have now created a non-conscious but very powerful alien intelligence that, if mishandled, can extinguish the human domination on earth. Tim Berners-Lee, the World Wide Web inventor, is concerned about the impact of big tech and digital media and holds that social manipulation, lack of transparency and surveillance with AI technology could, and should be countered by establishing effective safeguards. Yet while the risk of loss of human influences through algorithms needs to be taken seriously, there are limitations to AI compared to Human Intelligence in terms of creativity, intuition and adaptability let alone ethical and moral values. And so while AI is a powerful tool and an increasingly viable alternative in many areas, design ideation included, it is not yet a complete substitute for human intelligence. Positively, then, AI and human intelligence can complement each other, leveraging the strengths of both to achieve more through collaboration than either alone. That is, together, humans and AI are greater/better/more than the sum of its parts.

AI and human imagination

Artificial intelligence, AI, is increasingly having an impact on the design process, ideation included. Traditional ideation tools such as freehand sketches and sketch modelling have become integrated with computer software. As a result, technology marks a transformative shift in design practice where its integration with digital processes means machines collaborate with designers to generate data-driven ideas and solutions. Yet drawing by hand remains a tool for designers to capture and communicate ideas, as in "thinking with a pencil". Moreover, the immediacy of freehand drawing may encourage constructive in-person discussions with clients and stakeholders. Drawing also help expand designer knowledge of how things work, how things work together and helps to explore alternatives. Drawing by hand, however, is skill-based and needs practising. It is more time-consuming than software supported drawing and poses revision challenges and limited precision. But growing reliance on digital tools, AI included might reduce designers own unique style obscuring the deeply human aspects of design. And so the question remains: 'Will the rise of AI reduce designer capacity for originality and innovation, or will it serve as a catalyst for pushing the boundaries of creativity and expression?

Hands-on ideation

The digital age has transformed many aspects of our everyday experience - not least what we do with our hands when busying ourselves with digital devices. But what function does continual hand activity have? The most obvious answer is that we need our hands to do things. The hand is associated with agency and power. Hands serve us. They are the instruments of executive action, our tools. The idea of the hand as a tool, however, isn't new - it was common also in classical times. Where Anaxagoras had argued that humans are intelligent because they have hands, Aristotle, and many after him, countered that they have hands because they are intelligent, as the hands perpetuate our will instrumentally. In contemporary society, we are encouraged to counter the apparent excesses of the digital world by returning to traditional activities such as knitting, gardening, or general tinkering. Using our hands to make things is a remainder of the grounding, satisfying bodily techniques of the past. And when designers talk about why they practise hands-on skills such as freehand drawing and model making, the answers tend to reflect the importance of discovery, authenticity, and fulfillment. This blog entry inspired by, Leader, D (2016) Hands: What We Do with Them - and Why.

"AI Slop"

GenAI has triggered what has become known as “AI slop” – images and text created using generative AI tools. Coined in the 2020s, the term has a derogatory connotation akin to "spam", "junk" or digital clutter" that signify unwanted, poor quality AI content in social media or in online search results. However, Meta’s chief executive, Mark Zuckerberg, said that new, AI-generated feeds were likely to come to Facebook and other Meta platforms: 'I think we’re going to add a whole new category of content, which is AI-generated or AI-summarised content or kind of existing content pulled together by AI in some way.'  Although AI-generated feeds on social media carries risks and ethical concerns, "spammy content" viewed critically may inspire ideation. Indeed ideation springs from many sources and the more we learn, experience, and try, the better we get at generating creative and meaningful ideas.

Fringe ideas

In her book An Anatomy of Inspiration Rosamund Harding (1898-1982), an English musical scholar, sets out to reverse-engineer the mechanisms of creativity through the direct experiences of famous creators across art, science, and literature. In so doing, Harding finds common threads of creativity emphasising its combinatorial nature and its reliance on eclectic knowledge. She holds: 'Originality depends on new and striking combinations of ideas. It is obvious therefore that the more a man knows the greater scope he has for arriving at striking combinations.' Harding continues: ' Success depends on adequate knowledge: that is, it depends on sufficient knowledge of the special subject, and a variety of extraneous knowledge to produce new and original combinations of ideas.' Moreover, she writes: 'The variety of interests tends to increase the richness of these extra ideas — ‘fringe-ideas’ — associated with the subject and thus to increase the possibilities of new and original combinations of thought'. Harding's findings suggest support for knowledge-based ideation while debunking the genius-myth of creativity*. That is, in-born creative ability is not enough by itself without a solid foundation of knowledge obtained by experience or study. But more than this, in the age of artificial intelligence, designers draw inspiration from a raft of genAI applications, such as Dall-E, which, given their combinatorial nature, help produce what Harding calls 'fringe ideas'. *Research trends, originally outlined by Graham Wallace (1926) suggest five major stages of creativity: Preparation (idea generation), Incubation (gestation period), Illumination (the "Aha! moment"), Evaluation (idea development) and Verification (idea communication).

The idea of Now

The concept of now represents the inevitability of transience - the relationship between space and time - a kind of fleeting sense of reality. The space-time reference point of now suggests both spatial and temporal uncertainty as well as subjective experience. That is, the concept is not absolute but is relative to the observer's frame of experience. Yet defining the true nature of now takes on elusive yet provocative and fruitful associations. It has crossed cultures and civilisations, people and places, and countless interpretations have been proposed, as exemplified by Buddhist impermanence, the ‘feeling of things’ of Japanese aesthetics or Picasso's verdict that 'If a work of art does not live in the present it does not live'. The transitory essence of now suggests that ideation is an agent for continuous change where the idea is in the present time or moment yet related to the past pointing to the future. This also suggests that the ideation process can be viewed through a philosophical lens, say, of the ontology of being and becoming, or Hegel's view that everything is in a process of change. And Heraclitus noted the endless flux of existence: 'It is not possible to step twice into the same river.'

GenAI as spectacle

Generative AI enables machines to produce content that appears to mimic human-like creativity. As such GenAI models, as tools are great creative assistants. But while GenAI models excel at mimicking human-like responses, they lack genuine comprehension. That is, GenAI models use complex mathematical and statistical methods to generate responses that appear intelligent but lack genuine understanding or reasoning. The illusion of understanding means that GenAI output is surface, or representation without any deep contextual understanding, as experienced on social media platforms such as Instagram or Copilot. To better grasp the concepts of semantic understanding, reasoning and appearance of GenAI, a philosophical interpretation may help. For example, Guy Debord  (1931-1994), an arch-critic of consumerism and theorist of The society of the Spectacle (1967) - elaborates a system of social relations mediated by images where the totality of social relations becomes mediated by appearances. That is, experience of events is replaced by a passive contemplation of images (which are determined by other people) exemplified by the culture of advertising, consumption, and celebrity. Debord's term spectacle has become widely used for the modern condition. GenAI, then, through Debord's lens of a world mediated by images, may become the new social spectacle. The spectacle, moreover, evokes differences between appearance and reality. Shakespeare's Macbeth, for example, demonstrates how appearances cannot be trusted because they are moldable, meaning they offer no insight into the reality of a person. As spectacle, then, GenAI may alter perceptions of visual representations whereby appearances are based on copies instead of the original, or copies without the original.

Data-driven ideas

In the early days of design research - 1960s, a scientific approach to to the design process was promoted as the result of new technical developments such as computers and automation. Although the design science relationship was, and remains controversial, scientific knowledge, and its application is still relevant to understanding how designers think and work (Nigel Cross, 2023). A recent example is GenAI models trained on terabytes of web crawl data from across the internet to create new content. Being data-driven means that GenAI's output is derived from data analysis, which is part of the scientific method. In the data-driven approach, GenAI represents a break from the more traditional view of design as a creative practice supported by artistic, intuitive processes or personal opinions. Yet GenAI does not exclude the designer from the ideation process because GenAI operates on a probabilistic framework, it does not possess true understanding or consciousness like a human. That is, GenAI is not capable of learning, or understanding the concepts underlying its own responses to human prompts, which are input elements for GenAI to generate results. Indeed to achieve human-centered desired outcomes, writing effective prompts is considered a skillful craft. And so, although GenAI evolved from computer science, the technology is guided by human prompts. GenAI, then, reflects human-machine interaction -  a tool that facilitates ideation.

Easy Aideas

Design ideas typically are about incremental change or improvement over something that already exists rather than about something that is truly original or radically different. For incremental innovation, then, generative artificial intelligence has emerged as a powerful ideation tool that facilitates a seemingly endless flow of creative content. But how does GenAI tools like ChatGPT and Copilot compare with human ideation without GenAI? GenAI foremost advantage is it generates huge amount of diverse content - both text and images using pre-existing data from across the internet. Then there is the ease of use of GenAI as it responds to written prompts in a conversational style and in multiple languages - and at great speed. More, as GenAI is going mainstream it has the potential of facilitating problem solving on a global scale. But there are weaknesses with GenAI models.. For example, writing effective prompts may seem simple but rests on prerequisite knowledge, language skills and, yes human imagination. Even so, the user friendliness of GenAI and the creative and original appearance of its output carry the risk of over-reliance on GenAI. Indeed users might find themselves having more ideas than they know what to do with. Also, it is not transparent what data GenAI models are trained on - raising ethical or copyright issues. Or, the self-referential loop of GenAI data might, paradoxically result in more similar output over time narrowing the scope for plurality or novelty. But values, assumptions and biases are embedded in GenAI tools, and so more empirical evidence is needed to fully evaluate the pros and cons of GenAI systems. Yet the appeal of GenAI is overwhelming and by fusing AI-generated ideas with human judgement and refinement, it is fair to say that GenAI is enhancing human creativity, including ideation.

Ideator roles

Design ideation can be seen as generating, developing and communicating ideas, and so the corresponding roles of the ideator would be that of generator, developer and communicator of ideas. And one may add a fourth role, that is, that of critic, or rather inner critic. For the designer as ideator, these roles often role into one. That is, the designer generates the idea, from a great variety of (re)sources, then develops the idea, that is, grow, evolve or expand the idea, and finally communicates, or shares the idea with others.The fourth role, that of inner critic, may run throughout the ideation process, a balancing role as the ideator should manage their self-criticism so as not harm the desire to succeed. However, there is potentially a fifth role for the ideator, that is, the role of realising, or implementing the idea to what then becomes a working idea. And to execute the idea would be either on the ideator's own accord or with the help of others. The designer-maker would exemplify the ideator playing all the roles whereas the "Jack-of all ideas" may typify the ideator as foremost generator and communicator of ideas.

Daydreaming

Daydreaming or mind-wandering is often seen as a spontaneous, unfocused mental state without deliberate direction - in contrast to imagination regarded as a more focused, structured, and purposeful cognitive process. And so, if you get stuck on a particular problem, say, it may be a good thing to take a break from the problem and allow the mind to wander and daydream for a time, to let your subconscious work the problem. Moreover, by stepping away from the task in front of you, chances are you may generate creative ideas that help solve the problem at hand. Although daydreaming may at first be seen as distraction from the present, that is, inattention - and daydreaming does not necessarily lead to creative manifestations - it may nevertheless help problem-solving as it frees up space for the mind to rest and wander. Allowing daydreaming then, can be intentional, also known as "positive constructive daydreaming". Deliberate daydreaming may sound counter-intuitive but in practice may take the form of finding space and time for sketching or doodling to allow the mind to roam or wander. Doodling then becomes a technique, a tool, or practice that supports daydreaming, or out-of-the box, creative thinking. In addition, daydreaming through doodling may give a sense of professional identification with the work - particularly when generative AI may reduce the capacity to daydream.

Participatory ideation

Digitisation of design (converting analogue data into digital format), or digitalisation (turning analogue processes into digital ones) are not only driving mundane or routine aspects of the design process (such as rendering, drawing a plan or elevation) but also influencing design thinking and ideation. And so designers are being challenged by algorithms and corresponding software structures to focus their efforts on things that humans are better at than machines. Or rather, when challenged, how designers who embrace AI may do better than those who do not.  That is, designers need to engage in the evolving computer-human mind relationship. For example, AI is moving in the direction of becoming closer to a super-competent assistant, a virtual team member or co-pilot in the design process. That is, using AI tools in an enhancing role. Moreover, digitisation of visualisation has transformed the way designers communicate with non-expert clients shifting the balance of power in favour of the client - clients who, through their own digital experiences are better equipped to engage in the design process and consequently more demanding in their design requirements. This development highlights how the designer-client relationship is an ever closer cooperation, collaboration or partnership. In other words, digitisation is enabling a multi-level participatory design process where the client and other stakeholders are effectively becoming co-designers.

Performative ideas

Design ideation is a purposeful activity with a performative function in that the idea amounts to a proposal, plan or promise to be acted on. Moreover, the performative function of ideation relates to the semantics of ideas. That is, semantics is concerned with linguistic meaning that takes the idea beyond the visual expression of the material content (material culture). Verbal language, then, can enhance the meaning of the idea and help explain why some ideas are, or at least appear better than others. The reason for this is that ideas are sometimes just informed or reasoned guesses that designers present to their target audience, say a client. Designers, then, move about and develop the idea till they are satisfied that the idea would meet  the expectation of the client brief. In this pursuit, generative AI, as ideation tool and learning model, has a performative function and a performative capacity too. That is, AI offers support to designers to improve their performance in generating, developing and communicating ideas.

An idea is an idea is an idea

Some design ideas have a direct relationship to an actual object where ideation is pragmatically pursued through the interaction with the physical environment. But there are also designer who seek the highest level of abstraction, or the purity of a concept where, for example, a building is conceived as an abstraction. Yet both pragmatic and rational attitudes and approaches to ideation are expressed in language; verbal, visual or abstract (numeric). But language is embedded in culture and represents meanings. For example, the concept of a house may differ from one culture to another, and from one era to another. Is there then a common language for expressing ideas that bridges such differences? If not, how is communication between designers and stakeholders possible? And how is change possible, for example, in designing homes, if change of the concept of home isn't changed, altered or modified, say, through working from home or multi-generational living? And so, with ideation begins responsibility because the successful idea must meet stakeholders' values and expectations.

Flying ideas

AIdeation happens where human creativity and generative AI work together. Such collaborative creation between human, here the designer and machine, here AI systems can be likened to how air pilots, typically the captain and first officer, are co-piloting the flight - an interaction in which, moreover, the pilots are assisted by an autopilot. An autopilot, however, doesn't replace human pilots but rather allow them to focus on broader aspects of the flight. And so, generative AI does not replace designers but help them generate, refine and modify ideas. In this way, designers, while "letting AI fly for a while" add their unique touch to AI generated outputs while maintaining oversight of the ideation process, similar to how pilots are responsible for critical decision-making, from take-off and landing to situations in between. The interaction, then, between co-piloting and an autopilot, suggests a similar approach to how designers and AI systems can work together which, moreover, may help improve transparency and accountability in AIdeation.

Kafkaesque ideation

Franz Kafka (1883-1924), the writer known for his aversion to noise, joked that a living typist was much less intimidating than a machine: 'A machine with its serious, silent demands strikes me as exercising a greater, more cruel compulsion on one's capacities than any human being.' In Kafka's case, the machine was the typewriter (he claimed he was even afraid of the telephone). Today that machine is the computer. It operates silently but does it make silent demands? While there are those who depreciate the use of the computer for ideation, the fact that you can type a request into a machine, in normal conversational language, and it outputs something close to what you asked for, is pretty remarkable. Yet AI can give users false confidence, giving them the sense that if AI - with access to billions of data points - can come up with new ideas, they must somehow be better. But then ideas have never been in short supply. The problem for most designers, and their clients, is the uncertainty - which ideas are best, which ones are worth investing in? So will human creativity always prevail? But with humans in competition with AI, how can we tell?

Generative AI systems - the new art factory?

Art and technology, throughout the ages have had a close relationship whereby technology has influenced and facilitated works by artists and designers. The new materials of twentieth-century technology, for example, provided both the means and the inspiration for the three-dimensional works of the Russian Constructivists. László Moholy-Nagy, the painter and photographer of Bauhaus fame, argued for the integration of industry and art and suggested it would be ideal to ring up a factory and order one's art according to specifications. Andy Warhol, known for The Factory (his studio), created works using Amiga computers in the 1980s and is quoted saying, 'I want to be a machine, and I feel that whatever I do and do machine-like is what I want do to. I think everybody should be a machine.' And now, text-to-image generators built on huge data sets - and whether Open Source or Closed Source LLMs - search for images not yet created. changing how today’s creatives will likely produce, or co-produce their work. So there's a long history of artists inspired by and adapting to technology and even led by technology. But when art is reduced to a use case (list of actions) for technology, are we bound to a proliferation of shallow artistic engagement, asks Simon Kenny, an independent researcher and educator. https://medium.com/@skenwrites/the-art-of-ai-prompt-engineering-dd4f23138f7a.

AI facilitates ideation across cultures

Generative artificial intelligence, such as ChatGPT can help designers not only generate but also communicate ideas and whether in spoken, written or visual forms, or combinations thereof. Moreover, chatbots can be particularly helpful to designers for whom English is a second language and so enabling them to focus on the creative content of their idea. That is, human language (spoken and written), although supple and flexible, does not always fully capture the richness of ideas while remaining mindful of the interrelationship between concepts and lived experience. So the original state of the idea might get diffused, distorted or lost in translation from one language to another, notably when it comes to cultural nuances or idiomatic expressions. This highlights why spoken or written words need to be supplemented or supported by images in the ideation process (multi-modal communication). Generative artificial intelligence, then, is becoming an influential and practical design tool in the development of ideas and ideas communication.

TikTok ideation tool

TikTok, the short-form video platform, has, in its latest iteration, added the notion of ideation to its new Creative Assistance. That is, in TikTok's marketing jargon: 'Creative Assistance is an AI-powered virtual assistant designed to intelligently collaborate with brands and creators throughout their creative journey on TikTok  ... through never-ending ideation and brainstorm sessions'. As with generative AI in general, TikTok's Creative Assistance works through prompts input to generate or refine scripts and images. That is, creative prompts yield creative outputs. Creativity, however, in its deeper sense often requires a more open and explorative approach than AI algorithms can offer. That is, to use generative AI effectively, and ethically human involvement is needed at both the beginning and the end of the process involving not only prompting, editing and iteration but also curiosity and compassion. In other words, it is human creativity that is giving shape to AI systems, not the other way around. Yet AI is already embedded in everyday software and so, like all technology, what matters is how AI is put into practice.

Sketch, ideate, communicate

One of the main benefits of the sketch, and whether drawn on paper or e-tablet is that it gives full play to the imagination that is foundational to creativity. It captures the essence of the idea, helps clarify design intention both in the sketcher's own mind and that of their audience (colleagues, clients etc). Sketching, then, is a fast and efficient way of communicating first thoughts and ideas. And so sketching helps conceive, elucidate and articulate design ideas, and whenever there's a need to quickly "sort things out" in the design process. As a thinking tool, sketching encourages the freedom of simplicity and helps develop a sense of creative self. And the iterative nature of sketching, going backwards and forwards channels new thoughts and ideas. And although ideas are either endorsed, rejected or modified, in their sketchiness they are often adaptable to new, different or emergent contexts.

The Magician

On a lighthearted, and imaginative note, let's draw, interpret and reflect on a single Tarot card. And so, the Magician - a beautiful card signalling a magical, creative, inspiring times ahead. Make something! Design or invent something! Pitch an idea! People will listen to what you have to share, and they will love  your ideas. You will get the green light during this period if you make the proposal now. The Magician shows you stepping into your power, feeling like you’ve got talent and skill, and wanting to manifest something with it. You want to make a living based on what you’re uniquely good at. It’s time to shine! The Magician, then, like the ideator, is interested in new ways and finding solutions that are not yet imagined, as well as products not yet built. They are an idea-driven powerhouse, thriving on vision and intuition - a force for transformation and innovation through ideas.- everywhere, anytime.

Chatbot creativity

Web-based search engines are commonly used as an ideation tool. Yet their longtime dominant position has attracted sponsored content fuelled by "search engine optimisation" techniques which are pushing down genuinely useful results. In response, chatbots, such as ChatGPT and Google Gemini are poised to shake up how traditional online search works. That is, rather than typing in a string of keywords, chatbots are conversational or interactive agents using natural language that provide instant response to the user. But there's a catch. Whereas most of these chatbots have free versions, they typically limit the number of queries that can be made. So, chatbot platform providers offer premium levels that provide smarter chatbots with additional features which, however, have to be paid for. A usage-paid pricing model, however, and particularly in education, raises the question of users' equal access to chatbots, as paid versions unlock privileged access. Another concern with the use of chatbots is that, and unlike conventional online search producing matter-of-fact results, they have been known for providing deceptively convincing responses, known as “hallucinations". In fact, chatbot generated content may be inaccurate or false. The new generative AI tools, then, open a can of worms regarding accuracy, trustworthiness, bias, hallucination and plagiarism - ethical issues that pose risks to human interaction, performance and equality. But used responsibly, chatbots can assist in stimulating, provoking, and reviewing thoughts and ideas. In short, the extensive knowledge base that chatbots build upon can be a very useful ideation tool. Indicative source:https://www.sciencedirect.com/science/article/pii/S2713374523000250

The medium is the message?

'In a culture like ours,' wrote Marshall McLuhan (1964) 'long accustomed to splitting and dividing all things as a means of control, it is sometimes a bit of a shock to be reminded that, in operational and practical fact, the medium is the message.' That is to say, the medium that is used for communication is more important than the actual message itself. More important?, or rather that the value of any message should be viewed through the medium by which it is communicated? What ,then, does McLuhan's expression mean for ideation in the digital age? Is the idea the medium, or the message? Or, both? In human-technology relationships, does ideation reflect the ethos of modernity to transform ourselves, our ideas and the material world through technology? Or, in post-digital society, does it suggest design can be perceived purely as a conceptual medium liberated from the need of realisation? If so, are designers conceptualisers first, and makers second, if makers at all? Discuss.

AI: creative vox populi?

Generative AI is being promoted as a tool for creating new ideas, or augmenting content such as audio, text, images, and video, which is often shared on social media platforms, such as Instagram or TikTok. Indeed ideas are content. But more than this, generative AI has the potential to democratise design allowing greater participation in decisions around societal innovation. However, new ideas or content thus generated may not be that original but rather reconfigured versions of something done in the past. In fact, much creative content on media platforms is about remaking existing ideas, or piggy-backing off the creativity of others. Moreover, as generative AI is apt at generating variations of ideas, this may lead to a feedback loop where AI generates content that is already popular or proven to be successful on social media. That is, generative AI is socially embedded giving a boost to creative vox populi. Yet what is originality in the age of AI?  Revisiting older ideas, however, can be fruitful in problem solving ("what's wrong"), or in solution finding ("what's right"). That is, the circularity of ideas, in which each idea is revisited at intervals, at a more sophisticated level each time may help generate ideas for the emergent circular economy, defined as an industrial economy that is restorative or regenerative by value and design.

Train of thought

Train of thought, as understood by Thomas Hobbes, the English philosopher (1588-1679) was the succession of one thought to another. A train of thought, then, refers to the interconnection of a sequence, series or succession of thoughts or events. It may also refer to a path of reasoning. Or, how this sequence leads from one idea to another. The sequence, however, is not necessarily a linear one. And so, and notably in ideation, the sequence is rarely straightforward but rather an iterative or cyclical process, of trial-and-error. However, train of thought can also be interpreted literally. For example, Charles Dickens, the English novelist (1812-1870) found that, on a train journey, observing from a railway carriage was 'always a wonderful suggestive place'. Indeed, there are many places and spaces - and activities that can inspire creativity or trigger imagination, from the inherent character of nature to divers social or cultural settings. Indeed, the more unique or unusual the physical spaces or place, or unconventional the activity, on their own or in imaginative combinations, the greater the chance to set in motion pioneering thoughts or breakthrough ideas.

Idea curation

The rapid advancement of generative AI may suggest that AI and automation could replace entry-level designers, that is, designers whose main tasks are with creating repetitive designs. But even more senior designers might be at risk as their roles are becoming impacted of AI which is capable of keeping up with the latest design trends and fulfil the needs of mainstream clients,. One approach to turning the risk into opportunity could be designers adapting to a new role where they can act as curators of AI-generated products and services, rather than being sole ideators themselves. That is, using AI as a tool, pulling and filtering ideas from as many places and people as possible (sourcing, organising and prioritising) and then, in conversation with others (sharing insights), asserting and selecting the best. In this way, AI can augment creativity as well as making it more challenging. Indeed, many designers prefer using generative AI over working without it, and they collaborate more effectively when using it. AI-proofed designers, then, may be those whose ideas are crafted and curated with AI integrated in their workflow.

Blank canvas

The idiom "blank canvas" traditionally refers to a painter's canvas that has yet to be painted on. As such it implies the canvas can be easily filled with entirely new things, or, a metaphor for limitless possibilities. But when anything is possible, where to begin? This highlights the reality of most design activities which are full of constraints as expressed in the design brief (objective, site, time, budget etc). Limitation, then, forces the designer to embrace constraints imposed by the design brief. Paradoxically, then, constraint heightens rather than feebles the ideation process. That is, constraint acts as a driver for innovation, not unlike the proverb "necessity is the mother of innovation", or, "if someone really needs to do something, they will find a way of doing it."