What Do People Actually Think About AI? We Asked Them in the Street.

We stopped people on the streets of Montpellier and asked three questions: does AI reassure you or worry you, is it a good or bad thing, and what comes to mind when you hear the words "artificial intelligence"?

A psychologist answered. Someone who worked in advertising answered. Retirees, and professionals answered. The responses were candid, sometimes contradictory, and more considered than the question might suggest.

One person put it this way: "The technological revolution sought to augment our capabilities. This is a level beyond that. Maybe tomorrow there's another level that won't even be called artificial intelligence." Another said simply: "The human has to stay in the loop." A third: "You have to know how to compose with it, not oppose it." And one more, the sharpest summary of all: "If you don't get on the train, you'll stay on the platform."

Nobody described a robot taking their job. The people we spoke to thought about AI the way you think about a tool you haven't fully learned yet: with curiosity, some caution, and a sense that the question of how to use it well matters more than whether to use it at all.

Why Bionomeex Went Into the Street

Bionomeex builds AI for life sciences. Our tools analyze genomic data, detect organisms in biological images, and help researchers and clinicians extract meaning from datasets that manual methods cannot handle at scale. This work runs inside laboratories and hospitals, in collaboration with institutions like CNRS, INRAE, and university hospitals in France and Canada.

None of that is visible to most people. And that gap matters.

The conversation around AI in public tends to flatten into two positions: enthusiasm for productivity tools or anxiety about automation. Both conversations orbit the same reference points, primarily large language models and generative AI. The AI that Bionomeex builds operates in a different register entirely, one where the question is not whether a machine can write a paragraph, but whether it can identify a genetic variant linked to a disease, detect a pest on a vine leaf before it spreads, or track the movement of a protein inside a cell.

We went into the street because we wanted to hear what people actually carry in their heads when they hear the word "AI." The answers told us something useful: most people already understand that AI is a tool, that the human has to remain central, and that the technology moves faster than the frameworks for thinking about it. They are ready for a more specific conversation. We plan to have it.

Human In The Loop

At Bionomeex, we build every AI system around a principle we call Human In The Loop. It means that AI outputs are reviewed, validated, and refined by domain experts at every stage. A biologist checks the cell detections. A clinician interprets the imaging results. A geneticist evaluates the epistatic signals.

This is not a safety disclaimer. It is a design choice that reflects what AI actually does well and what it does not. AI processes volume and consistency at a scale a human cannot match. A researcher brings judgment, context, and the ability to recognize when a result is biologically implausible even if it is statistically significant. The combination produces better science than either alone.

The person in our micro-trottoir who said "it has to remain a complementary tool" described this precisely. We agree. Our technology was built on that premise.

What Comes Next

The micro-trottoir was a first step. We plan to continue producing content that opens up the real breadth of what AI does in science, medicine, and the environment, without reducing it to the reference points that dominate the public conversation.

The formats we are developing include filmed interviews with professionals working on problems where AI plays a genuine role; short-form explanations of scientific concepts that underpin our work; and field reports from the collaborations and events where Bionomeex operates.

These will publish on YouTube, LinkedIn, TikTok, and Instagram. The goal is consistent: give people the tools to understand AI as it functions in a laboratory, a hospital, or a vineyard, not as it functions in a chatbot. The two are related, but the distance between them is larger than most coverage suggests.

The person who said "if you don't get on the train, you'll stay on the platform" was right. The train worth boarding is the one doing the hard scientific work. That is what we want to show.

Watch the Micro-Trottoir

The video is available now on LinkedIn and Youtube. In the coming months, we will publish the first interviews in the series.

If you work in research, medicine, agriculture, or environmental science and want to talk about how AI intersects with your field, contact us.

Contact Bionomeex

Written by the Bionomeex Team - About us