Browsing through social networks one can find various testimonies of how AI is affecting the labor market, especially in fields like programming and software engineering. “We were released without identification,” Valino said in Juanjo Valino’s testimony.
Joseba Lagaretta, another X user, spoke of a similar situation, and both publications are filled with professionals who share similar sentiments and experiences. The fear of losing one’s job already weighed heavily, but added to that stress were other stresses: feeling that “years of effort at education had gone down the toilet.”
What is lost hurts more. AI slows access to junior profiles and takes over jobs that previously served as a training step to launch their careers. A Stanford publication claims that 22- to 25-year-old programmers experience declining employment, but those who keep their jobs also experience constant pressure. said DD Das, partner at venture capital firm Menlo Ventures Business Insider that most engineers “suffer from an identity crisis bordering on depression.”
Researchers at the Friedrich-Alexander University of Erlangen-Nuremberg have taken a more academic approach to this new level of AI problems and propose that employment gives these engineers more than just a salary: it gives them a routine, social contact, status and a sense of togetherness.
Kahneman and Tversky describe loss aversion and how losing something is greater than gaining the same thing. That is, the feeling of losing control over work and creative abilities far outweighs the acceleration of projects that AI can provide. Years of work devoted to programming represent the kind of possession they refuse to lose, though Valino admits that turning on functions “that you never dreamed of before” is “dopamine through a tube.” That gain does not offset the loss.
Hours that are not restored. On the other hand, what many developers commented on was “thousands of hours of practice” that “disappeared” in 18 months. Here comes another important psychological factor: the sunk cost fallacy, the tendency to cling to what has already been invested in terms of time or effort. There are precedents in that sense.
Lee Seidl, an 18-time Go world champion, retired in 2019 after losing to AlphaGo. Even after he became number one, he said that “there is one entity that cannot be defeated.” That entity was AI.
The history of industrial evolution also gives us a similar discourse. For example, the Luddites of early 19th-century England rebelled not against technology, but against processes that reduced the value of their years of professional education to zero.
Author to reviewer. One of the main complaints of software engineers is their shift from being key players in the development of applications to being mere caretakers of AI-generated code, even though this new role is their lifeline. This brings us to a furniture store: the IKEA effect
This approach ensures that we value what we build ourselves, even if the results are mediocre. For software engineers, programming is a way to create something of your own by applying your own hands and knowledge. Now agents write and people review alone, breaking that sense of belonging.
AI as a demotivating factor. Another psychological factor by which the two publications are removed from comments and reactions
A response to the Lageretta thread speaks of the vertigo of “not being able to feel 100% responsible for the outcome”. Research from the University of Rochester addresses this same disconnect and places decision-making autonomy and competition among the basic psychological needs to achieve that motivation.
In Xataka | The problem isn’t that AI is going to destroy the labor market: it’s that millions of employees will have to learn another trade
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