As individuals perform their jobs, they generate enormous volumes of digital traces: emails, presentations, documents, videos, meeting transcripts, software code, customer interactions and countless other artifacts. Embedded within these traces are not only facts and knowledge, but also aspects of how individuals reason, communicate, solve problems and interact with others. The concept of the codified self helps explain what happens when AI learns from these traces.

The traditional view of human capital rests on two assumptions. First, workers retain ownership of their human capital. Second, organisations can create value from that human capital only when workers are actively engaged in work. Artificial intelligence is beginning to weaken both assumptions.

Technical debt lives in the code; cognitive debt lives in developers' minds

Well, PKM is not actually my idea. There are other people who are writing about personal knowledge management. I changed it to mastery because I wanted to move away from the knowledge management world, which was too much about big systems and big databases. I wanted to focus on what I, as an individual, do, and what we as a community or a network do. For example, how do we enable that kind of collaboration and cooperation? So, personal knowledge mastery just became the term because it is about mastery, and you never master it completely, right? It’s like any discipline, a lifelong thing. You continuously try to get better.

work is learning, and learning is the work.

Donald Schön hat den Begriff „reflection-on-action“ geprägt: Wir lernen, indem wir nach der Handlung darüber nachdenken, warum wir etwas getan haben, und welche Alternativen möglich gewesen wären [2].

The book’s central argument was not about timelines or machines outperforming humans at specific tasks. It was about scale. Artificial intelligence, I argued, should not be understood at the level of an individual mind, but at the level of civilization. Technology does not merely support humanity. It shapes what humanity is. If AI crossed certain thresholds, it would not just automate tasks, but it would reconfigure social coordination, knowledge production, and agency itself. That framing has aged better than I expected, not because any particular prediction came true, but because the underlying question turned out to be the right one.

The cost goes beyond simple inefficiency and becomes a mountain of invisible labor, usually absorbed by the most junior person in the room or whoever has the misfortune of being labeled as “good with computers.” It becomes a drag on every collaboration, the friction in every workflow, the meetings that take an extra ten minutes while someone (who is often paid twice the average salary of the other people in the meeting) figures out why they can’t access the shared folder the rest of us have been using for months. It’s the quiet erosion of patience and goodwill among people who are constantly expected to know and fix things that shouldn’t need fixing in the first place.

Imagine a carpenter who couldn’t figure out how to adjust their table saw, or a surgeon who shrugged and said something like, “I’m just not a scalpel person.” We would never accept that. But in the field of knowledge work, “I’m just not a tech person” has become a permanent identity instead of a temporary gap to be filled.

I’m talking about the basics: keyboard shortcuts that save hours per week. Understanding the difference between “reply” and “reply all.” Knowing how to search your own inbox or switch between work and personal accounts. Reading the words on your screen or an error message before throwing your hands up and declaring “something’s broken.” Learning how to unmute yourself or share your screen after years of being forced to do all our meetings on Zoom.

The number of professionals in journalism, media, communications, and academia who still don’t understand how to use the very tools they depend on for their livelihood is, frankly, staggering

I assumed we would all finally reach a baseline level of digital fluency. I could not have been more wrong.

I think we’d see a much more substantive transformation in journalism if we started by simply learning how to use our computers.