A couple of weeks ago, I wrote about "Generative AI and Qualitative Data Analysis: New Frontiers?
" . In this blog, I elaborated a little bit on how you can experiment with Generative AI yourself, some insights from our conversations with researchers across the globe, and finally, about the need for a co-pilot in this journey.
I am going to close out this series on Generative AI and QDA (do I hear a collective sigh of relief??) by talking about different aspects of automating the qualitative research process in general, and the QDA process in particular.
So let’s dive right in. I will be talking about what directions one can take, and how our experiments are panning out and becoming features on our platform.
Revisiting where Gen AI can make a difference in QDA
Hark back to an earlier blog I had written about Top 3 advances in AI that matter. We had looked at the following visualization of AI and its possible influences in the process.
Let’s focus on the elements 8 – 10. Lets see what is out there.
AI-powered transcription can quickly and accurately convert audio or video recordings, interviews, into digital text. This literally happens in minutes. Of course different models offer different levels of accuracy for different languages. The good part is that there are enough and more people solving the accuracy bit that should give us confidence to start this journey.