As part of our 2023 Q Report survey of Quirk’s readers earlier this summer we asked an open-end on their current or planned use of generative AI in their work. (“Are you using or planning to use generative AI in the research process?”) The yesses and nos (and all the variations thereof) were pretty equally split, with a slight edge to those saying they are using or planning to use it.
With this being early days (and, in the case of this survey, which was fielded in July, even earlier days), it’s understandable that there are so many in wait-and-see mode. And, unlike any new method or tool in recent memory, major and unavoidable issues around privacy and data security loom over its use by companies and organizations, as many of our readers indicated in their responses.
In the spirit of things, I used ChatGPT to generate a report on the responses to the open-end. Here is an edited version of what it came up with (a bit bland but not bad!) along with some handpicked survey responses sprinkled in to add color.
A significant portion of respondents indicated that they are already using generative AI in their research processes. Some of the common applications include:
Data analysis: Generative AI is being used to analyze data, which can include tasks like summarizing findings, coding open-ended responses and identifying trends.
It is built into our dashboard product and we always use it for on-the-fly analysis.
Content generation: Respondents are leveraging generative AI to help create content for reports, blogs, newsletters and questionnaires.
Idea generation: Generative AI serves as a valuable tool for brainstorming and idea generation, helping researchers come up with innovative concepts.
Yes, we explore broad topics/genres/audience interests this way. More in a brainstorming approach as well as analyzing open-ends.
Survey development: It is used to assist in the de...