Extra! Extra! AI Will Eliminate Our Research Jobs!
…Not So Fast… We Humans Aren’t Obsolete Yet
by Felicia Rogers, Decision Analyst and Lisa Hazen, Nuance
Go to any conference. Attend any webinar. Scroll through any discussion board. Read the top business news articles.
You might be convinced from these sources that Generative AI—the new technology on the block in early 2023—is going to take over and push us out of our jobs. On the flip side, you might learn from listening to some of the rebuttals and reasoning that it’s going to be an incredibly useful tool to streamline processes, create efficiencies, and help propel us further than we’ve been able to go before, but it won’t be pushing any of us out of the way.
Decision Analyst’s recent data* show that, in general, (68%) people are concerned about possible negative impact of AI. There are some (38%) who are excited about its potential helpfulness. Some are on the fence about both of these scenarios.
Regardless of where you fall on the fear to excitement spectrum, here are some thoughts on the continuing importance of humans in the research process.
Understanding the Business Question
Before any data is gathered, we need an accurate understanding of the question we’re trying to answer or the problem that needs to be solved. Grasping the issues at hand requires good conversation skills. We (humans) have to ask good questions, listen carefully, and think before replying. Sure, machines can ask, listen, and respond, but they may not get it right if unusual phrases are used, new ideas are shared, or a spoken accent is challenging to understand. We understand background and context, probably in more detail than we realize or would communicate to an AI engine in the form of a prompt. Our brains can process on the fly like a computer, AND we can think creatively about the meaning and relevant application of the words being shared.
Planning the Methodology
In research, there are scores of options when it comes to the methodologies we leverage to gather information. Some questions lead us to a quick decision on how to approach the research, but some require careful consideration of options, weighing pros and cons, not to mention available time and budget. Discussions, collaborations with experts, and some give-and-take are very often part of the process of proposing and deciding on the right approach to use. There’s rarely an “easy button.”
Writing the Instruments
Here’s an area where AI can be a very helpful part of the process. With the correct (human-generated) inputs or prompts, AI can be useful in developing a first draft of a questionnaire or discussion guide. From there, the people working on the project—those who had the initial conversations to understand the business issues—need to carefully review, revise, and refine the instruments to make sure the research uncovers the needed information.
Analyzing the Data
This is another step that can be assisted or accelerated via AI. A first pass through comments or numbers can, again, help with that first draft. However, we have to carefully review and build on the initial output.
Here’s a recent example: In the process of analyzing open-ended responses to questions from a pet product taste test, a comment was encountered that went something like this. After one taste, he (my dog) was jumping all over me. I couldn’t keep him off of me. The AI model being used determined this to be a negative comment when, in fact, the sentiment was anything but negative for the manufacturer. The pet loved the item so much that he was pestering his parent for another!
In this example, sentiment was misinterpreted. Without human review of this example, such mis-coded comments would have gone unnoticed. Worst case scenario, the new product may have been cut from the lineup when the research actually showed it could be a big winner.
Making Plans to Act
Once the research, analysis, and report are finalized, we humans need to spend more time thinking. We may hold a workshop where people can interact to understand the results and brainstorm on what’s next. The brand team needs to collaborate with design, production, marketing, finance, and all the other stakeholders to weigh pros and cons of where the research is suggesting the team should go. Experience and intuition will play a role in any move-forward decisions to be made.
AI algorithms are smart and becoming smarter by the day. They’re sure to be able to do some of these tasks now, and perhaps more of them in the future. As we sit here today, relying solely or even too heavily on AI comes with significant risk. We humans have a broad and deep understanding of the business issues—the context of the problems, if you will. We are intelligent, intuitive, discerning, and creative. Humans are still in control and still needed, and we’re very happy that’s true! There’s a very good chance you are happy about that, too.
* Source: Decision Analyst’s Consumer Trends survey conducted in May 2023 among 1,012 U.S. consumers. Questions: “Now please think for just a moment about technology—specifically artificial intelligence, or ‘AI.’ How strongly do you agree or disagree with each of the following statements about AI?” “I’m Excited About The Potential Of AI To Be Helpful Technology” and “I’m Concerned About The Possible Negative Impact Of AI”
About the Authors
Felicia Rogers (email@example.com) is an Executive Vice President at Decision Analyst, she may be reached at 1-800-262-5974 or 1-817-640-6166. Lisa Hazen (firstname.lastname@example.org) is President at Nuance, she may be reached at or 1-817-640-6170.
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