![[Define with AI] Processing Raw Data Using ChatGPT](/_next/image?url=https%3A%2F%2Fwww.notion.so%2Fimage%2Fhttps%253A%252F%252Fwww.notion.so%252Fimages%252Fpage-cover%252Fgradients_8.png%3Ftable%3Dblock%26id%3D18120fbb-a154-80ec-bcba-c0eeabb17652%26cache%3Dv2&w=3840&q=75)
Back in this story, we tried to use AI to help us generate an interview script, and yes, the result is lacking the nuance and detail that would be present in an interview with a real person because the results are based on demographic data, statistical interpretations, and other sources. but we still can use it as a starting point in predicting what the interview session would be.
And after running the actual interview session that involves real users in a certain group, the next step will be analyzing the interview results. It can take a lot of time and occasionally feel very tiresome to analyze all that data. By allowing a tool to handle big datasets, we can concentrate on interpreting the result and then pulling and drawing conclusions from it. Here is a summary from this article of what kind of research work can be helped by incorporating AI into the workflow.
How do we process all that data? Let's see how we can leverage the power of AI tools for data processing and analysis. For now, we're going to use the result from kaggle.com. The data set will focus on the user's experience with virtual reality technology; you can obtain it by clicking this link.
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It could be as simple as attaching the file and giving this prompt
“ i have some data set about comfort in using a virtual reality headset.”
The result:
As we can see, GPT has recognized the data and tried to explain the data attached inside the file to the chat. We can ask deeply about the data.
“yes, please generate the trends based on the data”
The result:
The result seems good. We can ask some more detailed prompts, such as comparisons or correlations about the data inside the file. We can also ask about what the best VR headset is to be used in daily activity, considering our VR Gym Application will be used daily.
“Based on the dataset, what is the best VR headset to be used in daily activity?”
The result:
Based on the dataset we got from kaggle.com, Oculus Rift is the best for daily use. However, the Oculus Rift is no longer in production, and Meta’s most recent technology is the Meta Quest 3. This nearly matches the information we learned in the last story. Thus, we can infer that the VR gym app we plan to create will be accessible through Meta Quest 3.
Tips
Here are a few tips to make the research still sharp when collaborating AI with our research workflow, as stated in this article
- Be sure to thoroughly spot-check any analysis or data processing you ask the AI to perform.
- Ask the AI tool to follow data-visualization best practices when creating charts.
- Use AI transcription, summarization, and coding features to speed up the initial steps in your analysis process.
- Remember that AI systems can handle data from interviews, surveys, and diary studies, but they can’t observe usability testing or watch video clips like a human can.
- Treat AI’s coding as an initial pass. A human still needs to make sense of the data and translate it into insights.
- Don’t attempt to use AI analysis tools for usability testing.
References:
- Previous story [Empathy with AI] Discover the Problem, the Competitor, and the Target User Using ChatGPT
- Artificial Intelegence & Machine Learning community https://www.kaggle.com/
- Accelerating research process with AI, https://www.nngroup.com/articles/research-with-ai/
- Best practice in creating, https://www.nngroup.com/articles/contrast-charts/
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