In the previous posts from the “Henhouse” series, we took you to IPPE in Atlanta, the International Production & Processing Expo, and described what we learned there. The people we spoke with knew the poultry industry inside out, and they told us that trust depends on the partner behind a machine, on surviving the realities of the plant, and on being able to recover when something goes wrong. But they saw MOZART only briefly, on a tablet, between one booth and the next.

This time, we wanted to try it the other way round. What happens when people get a proper look at MOZART, but do not necessarily come from the food industry? What do they understand, what convinces them, and what still holds them back?

One hour with AUTOMAT

On 22 June 2026, we held an open online webinar, “Showcasing AUTOMAT’s Integration in Industrial Contexts”. Sixteen people registered through the form provided by our project partner ICONS. For about an hour, the MOZART partners presented the project: the morphing surface itself and how the basic research connects to real applications.

Different project partners showed three industrial cases our project works with: rotating tuna, moving chicken parts and sorting them by weight, or arranging chicken parts for packing. We also talked about possible interfaces for our novel robot. Finally, we from the SSH team at SDU talked about trust and how to make sure that people trust the system appropriately – not only more.

After the webinar, we invited everyone to fill in a short, anonymous questionnaire. We kept it open after the event, shared it with the YouTube recording, emailed it to people who had shown interest, and posted it on social media. In the end, ten people answered.

Ten answers are not a survey of an industry, and we do not treat them as one. They came from food production, retail, robotics, research, and other fields, and had never heard of MOZART before. But their answers were thoughtful, and they told a clear story.

“I think” it’s a robot

We first asked people to describe MOZART in their own words. Everyone could. Some called it “a robotic table for factories”, others “a manipulation system featuring motion surfaces” or a “pick and place robot”. Several picked up on what makes it different: it can handle objects that are soft, delicate, or irregular.

But the answers were also full of small hesitations: “I think”, “not sure”, “maybe”. One person understood the fish and chicken examples well, but added: “I’m not totally sure what it does mechanically.” When we asked people to rate how well they understood the system, nobody chose the top of the scale (see the statistics below). Half placed themselves in the middle, and three rated their understanding as low.

For us, this was a useful reminder. An hour of presentations and three demonstrations got the project idea across. At the same time, the short presentation didn’t give everyone the same picture of how the system works and what it can do in reality.

Beyond chicken and fish

The examples in the webinar came from poultry and tuna. Yet several respondents also thought about using MOZART in different domains. They mentioned sorting fruit without bruising it, handling fabric, use in warehouses, or even sorting medicines. This does not mean there is a market waiting in each of these places. But it shows that people understood the core idea well enough to carry it into their own world, and see other opportunities for use outside of the primary target domains.

Comfortable, but not convinced

The participants’ ratings of the robot across various scales showed an interesting gap. Six of the ten webinar participants felt very comfortable working alongside a system like AUTOMAT, and nobody felt uncomfortable. But when we asked whether systems like this were ready for industrial use, only one person rated it as very ready.

In other words, being open to the technology is not the same as being ready to rely on it in production. For a system that is still a prototype, that caution is reasonable: it fits what the system can currently show.

“A demo isn’t enough”

So what would people need to see before using this system in their settings? This was the clearest message in the whole dataset. People wanted to see MOZART work in real conditions: in a real factory, with real products, and for long enough to see what goes wrong.

“I need to see the failure modes and proper safety validation. A demo isn’t enough.”

Another respondent wanted “to see the system being implemented in the actual industrial environment and the users try it”. Others asked to see it run for a full day, to test it on their own materials, or to know how fast it really is.

Behind this was a very practical worry: what happens when it fails? People mentioned food safety, damaged products, and the cost of mistakes. “One mistake with chilled food is expensive,” as one put it. They asked for a stop button, a way for the operator to take over, and clear documentation.

One answer captured what many seemed to be looking for:

“Good data and clear system status. If the interface tells me honestly what it’s doing and why, I trust it.”

People did not ask to control everything themselves. They wanted to be able to see when something goes wrong, and to step in when needed.

This sounded familiar. At IPPE, people told us that the most important moment of interaction is when something goes wrong: “Operators won’t babysit a smart surface. They need a clear status and an obvious stop/recover.” The webinar audience came from different sectors and had seen far more of MOZART, yet they asked for the same things. Both groups also told us that to trust MOZART, they would need to see more than just a presentation.

Who gets a say?

A few answers looked beyond the machine altogether. Some mentioned hygiene and cleaning, others training and jobs. “People here (are) scared to lose work,” one respondent wrote.

One person went further and put trust in very different terms:

“Whether the workers who use it actually had a say in how it works. Do they need this? Technology done to people without them is what I don’t trust.”

This was one voice, not a pattern in the data. But it points to something we had noticed ourselves. At IPPE, we talked with people who build, sell, and buy automation. Operators came up often, but as people to be supported, not as a group of stakeholders making decisions about automation.

Beyond the henhouse

So what did we learn from leaving the trade fair behind? People can like the idea of MOZART and still not be ready to rely on it. At this stage, that is the right response. What they asked for was not more promises, but three things: trials in realistic conditions, honest communication about what the system can and cannot do yet, and a place at the table for the people who will work with it every day, not only for those who decide what is installed.

The question for any new system is not only whether it works. It is also who gets to decide that it does.

The webinar recording is available on YouTube: link

The analysis draws on ten anonymous questionnaire responses collected after the MOZART webinar on 22 June 2026. Quotations have been lightly edited for readability.