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.