The application of artificial intelligence to generate or analyze questions within a contextual inquiry framework represents a significant advancement in user research. Contextual inquiry, a user-centered design method, emphasizes understanding users within their natural environments. AI-driven tools can assist in formulating relevant, insightful questions tailored to specific user contexts, potentially uncovering nuanced information that might be missed by traditional methods. For example, an AI could generate prompts related to a user’s workflow after analyzing their screen activity, prompting them to elaborate on challenges or workarounds.
This approach offers several potential advantages. The speed and scale at which AI can generate and refine questions can significantly accelerate the data gathering process. It can also mitigate researcher bias by suggesting alternative lines of inquiry, leading to a more comprehensive understanding of user needs. Furthermore, the structured analysis of user responses facilitated by AI can reveal patterns and insights that might otherwise remain hidden. Historically, creating effective contextual inquiry questions was a time-consuming process relying heavily on researcher expertise and intuition. AI offers the potential to democratize this process, making it more accessible and efficient.
