Where Technology meets human connection

When this year's lernOS Convention ended, the complete documentation of the two-day unconference was already on the table — printed, bound, ready to read. Three AI systems had written it in parallel, and the community judged the three versions blind. The appetite was unmistakable: people want documentation like this, and they want it again.

But acceptance turned out to be more layered than appetite.

Trust in the machines' accuracy did not simply follow their usefulness. Privacy did not behave like a price that better quality could pay off. And no setup — cloud or local, fast or thorough — could maximize all four criteria at once: timeliness, quality, confidentiality, use-case fit. These are patterns that forty years of technology-acceptance research, from TAM to UTAUT2, help explain — up to a point.

What can acceptance theory tell us about machines writing the minutes — and where does a real unconference push beyond it?

There's a principle in architecture that became a mantra in organizational design: form follows function. Structure should serve purpose. First decide what you're trying to do, then design how you'll do it. The principle isn't wrong. The problem is how leaders apply it — as a one-time setup rather than a continuous design challenge. They build the structure once, for the organization as it was, and then expect that structure to carry everything the organization wants to become. What gets missed is the second half of the logic: form doesn't just follow function. Form determines what functions are possible.

Team members are beginning to use AI tools in their daily work. Often, they do so with good intentions: to save time, write faster, summarize more efficiently, prepare meetings better, or improve the quality of their individual output. In many cases, this use is exploratory, pragmatic, and self-initiated.

But something is missing.

Most AI use still happens at the level of the individual. It is framed as a personal productivity enhancer — a smarter assistant, a faster drafting tool, a private shortcut. Much less often do we see teams asking a different and more consequential question:

How could AI help us collaborate better?

Some hybrid events fail because of inadequate technology, but most fail because they treat hybridity as a mere logistical challenge rather than a fundamental social design problem. This article argues that creating truly equitable hybrid experiences requires moving beyond technical functionality to consciously architect the social conditions for genuine human connection. Drawing on three sociological frameworks—Goffman's front stage/back stage dynamics, Rosa's concept of resonance and self-efficacy, and Welzer's notion of "good places"—we identify the essential prerequisites for successful hybrid interaction. The key insight: bridging the hybrid gap demands explicit attention to visibility, active engagement, and purposeless connection, ensuring all participants, regardless of location, experience themselves as part of a shared space.