Ideation and problem-solving

Ideation typically involves designers responding to a problem where problems are of two common types: simple or complex. Simple problems can be described as puzzles, or "tame problems", whereas complex problems are also known as complex challenges, or "wicked problems". A puzzle is fairly straightforward when the pieces need to be located and connected. In contrast, a complex challenge has no known or immediate solution and so designers need a variety of skills or capabilities. A capability, however, is never one skill in isolation but multiple subs-kills grouped together, such as creative and critical thinking, and using collaborative and decision-making tools and techniques. But whether simple or complex, the starting point for problem solving includes clarifying the goal, identifying the constraints, and understanding the context of the situation. To achieve this it can be helpful to make a checklist for questions to look at a problem from a variety of perspectives or angles. Also, Tame vs Wicked problems, blog below. https://www.td.org/content/atd-blog/puzzle-problem-challenge-or-conundrum

AIdeation and conversational prompting

Prompt engineering is the process of writing effective instructions for a GPT model, such that it generates content that meets desired outcomes. And because the content generated from a model is non-deterministic, and the datasets combine art and science, prompting can be particularly useful in creative fields such as design. However, there’s more to effective human-AI collaboration than a perfect prompt. That is, it’s about workflow and conversation too. Conversational prompting, then, is a technique that involves interacting with AI systems like ChatGPT in a natural, conversational way as if chatting with a human. And so, users simply describe what they want the AI to do rather than trying to craft complex prompts. In this, it focuses on intuitive back-and-forth interactions to refine the results, provide additional context, and answer the AI's questions. That is, the user guides the process while letting the AI handle the specifics of generating appropriate prompts and responses. Problem solving, then, is enhanced by balancing human ingenuity and machine intelligence.  Selected sources:  https://platform.openai.com/docs/guides/prompt-engineering    https://promptengineering.org/conversational-prompting-in-generative-ai/