The quiet disappearance of thinking together
AI helps us think. But what happens if we no longer think together?
AI training
We have run AI training for many different groups and organisations. Audiences and starting points have varied, but the same question lies underneath: what do we want to do with AI, and why?
What should we understand about AI?
What does the spread of AI change in collaboration, in everyday life and in how tacit knowledge is passed on?
What do we want from AI?
Everyone is in a hurry, but the direction isn't clear. What do we want to improve, what do we not want to lose, and who decides where and how AI is used?
The quiet disappearance of thinking together
More and more often in expert work, the first conversation is no longer with a colleague but with AI.
A question to ChatGPT. An idea from Copilot. Problem-solving with Claude.
AI talk is moving fast. Who will lose their job? Which professions will disappear? How much faster, more efficiently and more cheaply can we work?
“AI reveals which employees are useless.” “AI is replacing thousands of workers.”
At the same time, a quiet change is taking place.
AI helps us think, write, come up with ideas and solve problems. Handy! But at the same time, thinking moves from between people to between a person and AI. You used to ask a colleague. Now you ask AI.
An unfinished idea used to end up in a shared conversation. Now the thinking happens mostly with AI, and the team is shown a finished, polished version. A finished version is hard to dig into, because it looks too complete.
So what?
Others can't see where the idea came from, what you discarded or what you were unsure about. They can't challenge the assumptions, pick up on a side remark or take the thought further – to a thought nobody would have reached alone. We do get “answers” faster, but fewer moments where something new is born.
I also studied this phenomenon in my thesis. The expert team used AI a lot, but had not stopped to consider its effect on their shared thinking. Once AI use was made visible, the changes in how the team worked were noticed too. The team decided to start regular conversations and share best practices for using AI.
The question is no longer whether we use AI. We do.
Everyone is rushing to adopt AI, streamline, automate and keep up. In the rush, the essential questions can go unasked. What do we improve by using AI? What knowledge are its answers based on? What does using it do to our own skills and to shared thinking? What can AI decide on our behalf? Who decides where and how AI is used? And what kind of future are we building with it?
In the AI race, it would be good to reach the point where we decide which direction we are running in.
Sonja Baer has researched the impact of AI on shared thinking and has run AI training for very different audiences. What connects them is the idea that AI training should not only teach what AI can do. At least as important is to ask what is worth doing with it – and what we humans want to do together.