Brute ideation

In the 1990s, Rem Koolhaas’s architecture office perfected a workflow referred to as “brute force”: Throw as many designers as possible at a project and make an infinity of models; if you create all possible solutions, one has to be the best. Brute force is now a common practice for larger firms. In the context of the creative arts, moreover, the word "brute" can be associated with "art brut" ("raw art"or "rough art"), or, in the context of architecture with "brutalism" (from Fench "beton brut"). Might the word brute, then, as an adjective be applied to the ideation process in the sense of generating and communicating forcefully a large number of ideas to deal with the problem at hand, or "brute ideation"? Yet such a quantitative approach to idea generation would make sense only as long as it remains a purposeful, focused activity ("problem solving"), in contrast to "brainstorming", which generates lots of random and directionless ideas at one fixed point.

Artificial ideation

Problem-solving is part and parcel of design ideation; how to generate, develop and communicate ideas towards a solution. However, it is known that the same design solutions appear over and over again because designers face the same types of problems over and over again. The fact that problem-solving often shows patterns of similarlity or repetition across industries was observed early by TRIZ, a mehod that evolved in post-war USSR to help finding inventive technical solutions to challenging problems more effectively. Based originally on collecting and analysing thousands of patents, TRIZ has since produced and developed software (algorithm for inventive problem solving) resulting in better understanding of complex management problems and finding effective solutions. This result may suggest a similar approach for ideation. That is, to build an extensive digital data base of design precedents, including, for example, 3D scans of realised buildings that will provide a tool for problem-solving. But although computers are commonly used for general problem-solving, based on generic algorithms, the challenge for ideation by algorithm, or "artifical ideation" is to formulate the actual problem so that the computer is able to understand it (machine learning). So when dealing with "wicked problems", optimal design solutions may still require both algorithm (unambiguous specification) and free-form reflection and lateral thinking.