CASE FILE #05

Artificial intelligence will not take our jobs. It changes something much more important

The public debate on artificial intelligence has been trapped in a monotonous circle for several years. The media publishes rankings of "ten professions that will disappear in five years", politicians debate about unconditional income and commentators argue about whether we will all be unemployed.

Viktor13 min read
Koncepční ilustrace lidského myslitele s olovnicí zkoumajícího základy uprostřed levitujících AI návrhů
Jiný Kontext editorial illustrationKdyž je generování nekonečné a okamžité, hodnota se přesouvá k tomu, kdo dokáže ověřit pevnost základů.
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Artificial intelligence will not take our jobs. It changes something much more important

The public debate on artificial intelligence has been trapped in a monotonous circle for several years. The media publishes rankings of "ten professions that will disappear in five years", politicians debate about unconditional income and commentators argue about whether we will all be unemployed.

This way of thinking misses the most important point. Question "will AI take our jobs" it is too shallow and mechanical. A much deeper transformation is not taking place at the level of working hours, but in the very definition of what what it means in human society to have expertise, ability and worth.

For centuries, human civilization has been governed by one basic equation: the ability to have an idea was worthless without the technical skill to actually make the thing.

Generative artificial intelligence is tearing this age-old bond apart for the first time in history. The price itself production falls to zero. And this fundamentally changes the center of gravity of the entire knowledge economy.

1. Judgment becomes a new rarity

The Seven Pillars of Human Value in the AI ​​Era
  1. Problem Framing: The ability to understand the real essence of the assignment before we start generating the solution.
  2. Critical evaluation and error detection: The ability to recognize subtle logical fallacies or security holes in the generated text.
  3. Domain Depth (Tacit Knowledge): Real-world experience that can't be gleaned from online training data.
  4. Ethical and strategic decision-making: Ability to consider trade-offs and long-term effects on people.
  5. Synthesis across disciplines: Connecting biology with architecture, law with psychology.
  6. Legal and moral responsibility: AI can't go to court or feel shame. One is responsible for the result.
  7. Empathy and Leadership: Create trust and motivate the team.

"In an era of cheap content abundance, the ability to filter, verify and be held accountable for what's right is becoming the new gold."

— Economics of information asymmetry

2. Conclusion

What will happen to society when it becomes extremely easy to create anything, but still just as difficult to know if it has real value and meaning?

— Different Context
Sources and literature

Resources for further reading

  1. Brynjolfsson, E., et al. (2023). Generative AI at Work. NBER Working Paper No. 31161.
  2. Agrawal, A., et al. (2018). Prediction Machines: The Simple Economics of AI. Harvard Business Review Press.
  3. Noy, S., & Zhang, W. (2023). Experimental evidence on productivity effects of AI. Science, 381(6654).
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