Why Real Human Voices Still Matter in the Age of AI
These insights are drawn from the itracks webinar “The Advantage of Human Truth: Why Real Human Voices Still Matter in the Age of AI,” featuring Leon Bourner (Vice President, itracks), Rasto Ivanic (Co-founder & CEO, GroupSolver), and Don Carli (Founder & President, Nima Hunter). The conversation explored why real human voices still matter as AI becomes more capable, and how researchers can use AI to strengthen the research process without losing the human insight behind the data.
Prefer to watch? You can view the full webinar recording here.
When Fraud Starts Sounding Human
For years, fraudulent participants were often relatively easy to identify. They rushed through studies, gave inconsistent responses, or provided answers that clearly showed they were not paying attention. That is becoming more difficult as AI makes it easier to produce responses that are fluent, relevant, and tailored to the questions being asked.
As Don Carli, Founder and President of Nima Hunter, put it during the webinar, “the fraud used to be lazy. But now bad answers are fluent.”
A participant using AI can understand the language of a study, identify what researchers are looking for, and provide responses that are relevant and well written. The response may look perfectly reasonable while raising a more fundamental concern: is this actually the person the research team intended to hear from?
Participant authenticity affects research quality
Researchers have become good at determining whether participants can answer questions. The challenge is determining whether they are the right participants to answer them.
Real participants bring their own experiences, context, opinions, and perspectives to a research conversation. In qualitative research, those details are often what make the findings useful. When the person contributing the response is not who they claim to be, the research loses access to the experience it was designed to explore.
Rasto Ivanic, Co-founder and CEO of GroupSolver, spoke about using AI to work with real human responses and understand what people are saying without using AI to create the insight itself. The value of the research comes from understanding genuine human experiences and perspectives.
Where human judgment still matters
Technology can take on much of the operational work involved in research. It can organize responses, surface patterns, reduce manual tasks, and support analysis.
Leon Bourner, Vice President at itracks, highlighted the importance of human judgment in the decisions that shape the research. Researchers still need to determine who belongs in a study, what they are trying to understand, and how the research should be designed to answer the business question. Those decisions have a direct effect on the quality of the findings.
The same applies to the participants themselves. A study can have an effective screener and a well-designed research platform, but the findings still depend on hearing from people who genuinely fit the research criteria and can contribute the experiences the study is designed to explore.
AI can support better research
AI has a valuable role in the research process. It can help researchers work through large volumes of qualitative data, organize information, identify patterns, and spend less time on repetitive tasks. Researchers can use those capabilities alongside the parts of research that require human experience and judgment.
When researchers have confidence in their participants and use technology to support the work around them, they can spend more time interpreting what people are saying and considering what those insights mean for the decisions the research needs to inform.
Research quality starts with the participant
Participant fraud has always been a concern for researchers, but AI-generated responses make poor-quality participation harder to recognize. A response can be well written and relevant while still coming from someone who does not belong in the study. That creates a greater need for confidence in the people contributing to research, particularly when findings will influence important business decisions.
As Don Carli noted during the discussion, the value of research has to be considered alongside the cost of making the wrong decision. When research is being used to inform pricing, positioning, product development, or other significant decisions, confidence in the source of the data matters.
The technology used to collect and analyze research will continue to develop. The need for human input remains the same. A question worth asking throughout the research process is:
Do we know that we are hearing from the people we intended to hear from?
Want to build stronger safeguards into your next online qualitative study? Explore how itracks can help you recruit, verify, engage, and learn from real participant: Book a Consultation
Interested in reading more about research on the global scale? Check out our article Best Practices for Conducting International Research.