recursiveself-improvement

What Will White-Collar Jobs Be Like in 2030? What Should We Do Now?

As many of you may know, Dario Amodei has issued a warning to people. Roughly speaking, he stated, "The demand for entry-level jobs, such as those performed by new graduates, will be cut in half. This will become a reality within the next one to five years." This is shocking news, and the fact that it came from the CEO of a company actually developing generative AI has made it a global topic of discussion. In this article, I would like to delve deeper into this matter.

 

1. Dario Amodei's Warning

He is the co-founder and CEO of Anthropic, a U.S. company developing generative AI. He holds a Ph.D. in Physics from Princeton University, and from what I've seen, he strikes me more as a researcher than a business executive. I've been following his statements for the past two years, and I remember them being relatively conservative. I thought they were consistent with his researcher-like nature. However, this time he stated, "We are not keeping up with the pace of AI evolution," and "Unemployment rates will be 10% to 20%" (1), which shocked the world. I don't recall similar warnings from other frontier model development companies like OpenAI or Google DeepMind. This is why his latest statement garnered so much attention.

 

2. Current Performance of Generative AI

Currently, generative AI indeed possesses sufficient ability to handle entry-level tasks. As I mentioned before, Google Gemma 3, an open-source generative AI, achieved an accuracy of around 80% without any specific tuning for a 6-class classification task of bank customer complaints. Typically, relatively simple tasks like "Which product does this complaint relate to?" are assigned to new employees, and they learn the ropes through these assignments. However, with generative AI's performance reaching this level, management will undoubtedly lose the incentive to assign tasks to new employees at a cost. It's not yet clear whether the impact will be as significant as half of entry-level jobs disappearing, but given that even free generative AI can achieve around 80% accuracy today, a considerable impact is inevitable.

 

3. So, What Should We Do?

There is a division of opinion among experts regarding when AGI (Artificial General Intelligence), with capabilities equivalent to human experts, will appear. The most common estimate seems to be around 2030, but honestly, it's not clear. If so, we have about five years. In any case, we need to adapt our skills to the advent of AGI. Past computers could not be instructed or managed without a computer language. However, with the emergence of ChatGPT in November 2022, generative AI can now be instructed using natural language—"prompts." However, prompting is not a simple matter. It's an extremely delicate process of finely controlling the behavior of generative AI to precisely fit one's needs. Therefore, it's not uncommon to write prompts exceeding 20 to 30 lines. While I cannot delve into the detailed techniques here, it is certainly a skill that requires logical prompt writing. Even though prompts can be written in English or Japanese, acquiring this skill requires time and individual training. Given that open-source and free generative AIs are rapidly improving in performance, it is imperative for us, as users, to learn "prompting," the method of controlling them, regardless of our position or industry.

 

What do you think? It's good that Dario Amodei's warning has sparked more active discussion. As I mentioned in my previous blog post, generative AI is on the verge of implementing recursive self-improvement, gaining the ability for computers to improve themselves. The evolution of generative AI will accelerate further in the future. I believe the time has come to thoroughly learn prompting and prepare for the emergence of AGI. Discussions about AI and employment will continue globally. ToshiStats will keep you updated. Stay tuned!

 
 

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1) AI company's CEO issues warning about mass unemployment, CNN, May 30, 2025

 

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