Glocal-ideation

Glocal-ideation, a contraction of globalisation, localisation and ideation, and borrowing from the notion of glocalisation in the social sciences and postcolonial studies, may be understood as an ideation process that combines the concerns of localism with the forces of globalisation, or a local adaptation and interpretation of global forces. That is, adaptation of universal ideas to local levels and conditions. The spread of universal design ideas has had, and continues to have an impact on a range of specific design areas in local contexts, from design education to architecture, product design and media. For example, the Bauhaus pedagogic model, modern and postmodern architecture (theories, styles and materials), high-tech consumer products and social media platforms. With growing concern about glocal issues such as climate change, waste products and sustainability, glocal-ideation becomes a necessary approach in the early stages of the design process.

Comprehensive design ideation

The notion of comprehensive design ideation suggests not only designers' use of the full range of ideation tools, viz. words, sketches, and models - in physical as well as digital modes, but that design ideation can be pursued by anyone engaged in activities that apply ingenuity, originality, strategic thinking and other qualities that are indispensable to good design. In this sense, comprehensive ideation highlights the view of design as a fluid, intuitive process, or "open design" that goes beyond traditional boundaries of professional or commercial application of design. Such inclusiveness and widening participation in the design process seems particularly useful and meaningful in dealing with everyday design issues such as wasteful packaging, or design for the elderly.

Advantage AI-deation

CAD programs, such as Rhino, are already great at researching algorithm-based design solutions which allow designers a high degree of flexibility in creating both simple and complex forms. Now the use of artifical intelligence, AI, which writes its own algorithms through coded programs based on data fed to it, is supporting design ideation by researching and calculating responses to well-defined design problems. Although AI works on a system of probability, it may come up with creative surprises. But it is not so much the case that AI "tells" the designer what the best idea is for a given problem, rather AI enables ideas to scale, test and measure more easily and quickly, producing hundreds of possible iterations of an idea instantly, which the human mind never could. So the main advantage of AI, as the technology appears currently, is to minimise mundane and repetitive tasks thereby freeing up designers' time for more human-centered inventiveness as well as keeping the emotional resonance of the idea. Or put differently, while the design brief is inspirational, AI makes the brief aspirational, enhancing existing ideation processes.* It may be worth pointing out that AI-ideation carries the risk of algorithmic bias, that is, different types of outcomes depend not only on the amount of data, but also what kind of digital information is being generated, classified, stored, and made available for analysis.

Ideation as stream of consciousness

Ideas are elements of thought. But ideation, at the early stages of the design process, is not just thinking. Because thoughts create feelings. And feelings create actions. And actions define design outcomes. Ideation, then, is a process, or a continuous flow of  thoughts, feelings and actions. That is, thinking generates ideas, which, combined with feeling, produce a desire to express the idea, which, in turn, triggers the action to communicate the idea, and through using a range of ideation tools, such as words, sketches or models. Ideation, then, could be perceived as a stream of consciousness, or a narrative mode, device or method that attempts to capture and express an idea made up of numerous thoughts and feelings which pass through the mind of the ideator.

Bauhaus and the culture of drawing

Designers talk ideas but better still, they visualise them. And drawing is a prime tool for ideation, as celebrated by Bauhaus, the German design school founded 100 years ago (1919-1933). Paul Klee was one of the school's teachers promoting drawing not only as a practice but a practice underpinned by theory, as articulated in his Pedagogical Sketchbook (1925). This was in parallel to his Bauhaus colleague Johannes Itten who emphasised the psychological and emotional aspects of drawing, as well as colour, including gymnastic excercises to loosen up the body before drawing. Klee's lesson plans included hands-on step-by-step approaches to creative expression, such as outlining the types of lines and how a line can become a plane; drawing from observation analysing natural forms (from fish to plants to the body's circulatory system); drawing with colour (explaining Goethe's colour wheel) also making connections between colour and music; and researching contemporary and historic drawings in terms of line, form and colour. Klee, like Itten, provided student feedback but did not give individual grades believing that this would stifle the creative impuls.

Situated ideas

An idea is an idea is an idea. Or is it?  If ideas can be understood as elements of thought that can be either abstract, concrete or visual, is design ideation situated in any particular element of thought? Although design is often thought of in visual terms, as expressed in, for example, 2D and 3D images, graphs, prototypes or models, design can also be articulated in the abstract, say design theory or programming, or in concrete terms, in which the idea has physical referents. So what seems to matter in design ideation is that the idea is not localised in any particular element of thought but that which best expresses the essence of the idea, and be it in the context of, say function, styling or production.

Idea generator

Words are prime tools in the ideation process. But with the advancement of artificial intelligence, AI, the distinction between natural language, as spoken and written by humans, and formal or built language, as used in computing, is narrowing. For example, recent machine learning research has revealed a new text generator, the GPT2, which is capable of performing goal-oriented tasks including translation and summarisation, and pass simple reading comprehension tests giving the model more knowledge of how to understand written text. Moreover, the unsupervised transformer-based language model, created by nonprofit company OpenAI, and trained on a huge dataset, can be used to generate infinite positive – or negative – reviews of products. That is, the model is capable of generating samples from a variety of prompts (human written) that feel close to human quality and show text coherence. This, in turn, may suggest that if the model were to be trained on a dataset of designs, it is conceivable that the text generator, given sufficient and contextual relevant data, could turn idea generator. This raises furter questions, such as, what is the most authentic, or the highest valued idea: human generated ideas - the human connection or ideas generated by the algorithms in machines? That is, questions about the impact of AI system design on ethics, trust and humanity. See also: https://blog.openai.com/better-language-models/ ; https://www.cam.ac.uk/research/news/