Tuning in
I was recently interviewed by Thomas Pagbe for IT for Business while in Paris. The conversation was short, but it landed on a question that has been following me around for most of my career.
Do computers isolate us, or do they connect us?
It is a familiar framing, and one that tends to assume the answer before the conversation even starts. Computers are cold. Networks are impersonal. AI is productive but distancing. That story has been told so often it now feels like background radiation.
I never bought into that kind of thinking.
Checking the signal strength
Early in the interview, Thomas put the question directly: When we think about computers, we tend to think about space and machinery, not about people connecting to one another. Why do I see it differently?
Because the entire history of computing is a history of connection.
As I said in the interview:
“The whole history of computing and machinery is always about connecting people in some way, connecting one machine to another, connecting you, your television, your telephone, all these kinds of things.”
This is not a modern reinterpretation or a convenient reframing. It is the original intent. Long before the web, long before social media, long before anyone worried about screen time, people were already imagining machines as connective tissue.
Standing in Paris, that history feels especially close. Paul Otlet was imagining a worldwide network of documents, audio, video, and broadcast media here more than a century ago at the 1900 Paris Exhibition. He imagined not a website, not an app, but a shared information space that linked people, through machines.
We did not accidentally stumble into a connected world; that was always the original intent. Even if naked commerce and data-extraction got in the way.
Capturing the return signal
Our conversation naturally turned to AI, which today is often framed as a productivity tool, a labor replacement, or a risk to be managed.
Again, that’s not a framing I buy into.
AI is not interesting because it does things for us. It is interesting because it helps us get better at getting better.
As I put it in the interview:
“AI helps us become smarter and we can build more tools and that makes us smarter.”
This is an old idea with new machinery behind it. Engelbart would recognize it immediately (since I ripped off that quote from him!). So would Licklider. Augmentation beats automation every time, especially when the goal is not efficiency, but understanding.
AI, used well, helps expose shared context, shared language, shared intent. It helps people find common ground more quickly. It helps teams explore more options, not collapse prematurely on the first plausible answer they stumble upon. AI amplifies creative and problem-solving skills that already exist.
Another line from the interview captures this succinctly:
“It’s not for replacing anyone. It’s about enhancing. It’s what helps me connect even better with you.”
Now, that is the signal worth amplifying.
Logging the frequency
The clip from the interview, is short, but it captures something I keep coming back to in my work.
Computers connect people.
Networks scale that connection.
AI has the potential to deepen it.
But only if we choose to use it that way.
We already have extraordinary creative people. The work ahead is not to sideline them, but to give them better tools. Tools that help them see farther, reason together, and build shared understanding across systems, teams, and time.
That was true in Otlet’s Paris. It was true in Engelbart’s California lab. It is still true right now; wherever we are today.
The signal has been there all along. We just need to keep tuning in.
