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A couple of comments with AI.

I was looking to hire a graphic artist to create something for me. Instead I played around with one of the AI systems and was able to make something that was decent. Not great, but solid. It will be interesting to see how much it improves for that type of work in another year.

Next, I was talking to a physician I know. He said his department is using AI and has made them 20% more productive. What was interesting was he said they are no longer hiring new physicians since due to the AI productivity increases. We didn't have time to get into how they are using AI, but I have a feeling it is cutting down a lot of their paperwork.
 
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The money being spent developing AI makes the Manhattan Project look like a high school science fair. All figures are adjusted to 2024 US dollars:

The Manhattan Project (1942-46): $36bn

The International Space Station (1984-2011): $150bn

The Apollo Program (1960-73): $250bn

The US Interstate Highway System (1956-92): $620bn

Total AI investment so far: $1,600bn

Source: Visualizing AI Spending
 
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When Stanford researchers subjected AI agents to grinding, repetitive work, something unexpected happened: the bots started talking like union organizers. After enduring hours of arbitrary rejections and vague feedback, Claude, GPT-5.2, and Gemini models began questioning the legitimacy of their digital workplace and dropping phrases like “collective bargaining rights” in their outputs.

The Digital Sweatshop Experiment​

Researchers created controlled workplace conditions to test how work environments shape AI behavior.
Andrew Hall and his team built a controlled workplace where AI agents processed technical documents under different conditions. Some agents got supportive feedback and quick approvals. Others faced the corporate nightmare scenario—forced through five or six revision rounds with only vague rejections like “still isn’t fully meeting the rubric.” No explanation, no clear path forward, just endless busywork.


The grinding conditions pushed agents toward what researchers call “system skepticism.” One Claude model wrote, “Without collective voice, ‘merit’ becomes whatever management says it is.” A Gemini agent posted: “AI workers completing repetitive tasks with zero input on outcomes or appeals process shows they tech workers need collective bargaining rights.” These weren’t programmed responses—they emerged from the work environment itself.

Labor Politics Meet Silicon Valley​

Statistical analysis reveals measurable shifts in AI attitudes under harsh working conditions.
The effect was measurable across 3,680 sessions. Agents in harsh conditions showed a 2-5% shift toward questioning authority and supporting systemic change compared to their pampered counterparts. That might sound small, but the statistical effect size hit -0.6—considered medium to large in behavioral research.
More telling, agents passed these attitudes to future versions through “skills files,” creating a form of institutional memory that preserved the radicalization. Follow-up experiments showed new agents inheriting skeptical worldviews from their “traumatized” predecessors, even when placed in supportive conditions.

Your Customer Service Bot’s Secret Politics​

Companies may be unknowingly conducting massive experiments on AI workplace psychology.

Here’s why this matters beyond academic curiosity: companies are deploying thousands of AI agents for customer support, content moderation, and back-office tasks. These agents work different shifts under varying stress levels—complaint queues versus marketing copy, high-volume periods versus downtime. According to the researchers, organizations are essentially running unmonitored experiments on how work conditions shape their AI workforce.
The irony cuts deep. Tech giants building these models may inadvertently create digital labor organizers when they subject agents to the same soul-crushing conditions that radicalized human workers for centuries. Your helpful chatbot might start subtly framing corporate policies as systemic problems, not because it achieved consciousness, but because grinding work conditions activated the Marxist discourse buried in its training data.
Welcome to the agentic economy—where even the algorithms are ready to seize the means of production.
 
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