Dependence Day - AI Hegemony

 

Recent college graduates face technology conscription: the expectation to feed, train, and validate the very AI models designed to automate their future career paths.

  • The Flashpoint: Intellectual extraction and job devaluation. Graduates see AI corporations scraping human creativity, engineering, and writing without equitable compensation, creating an unstable economic future.
  • The Tipping Point: Instead of burning draft cards, modern graduates are engaging in digital resistance—refusing to apply to major AI firms, deploying data-poisoning tools to protect their portfolios, and organizing labor walkouts over algorithmic ethics.
  • The Split: A growing contingent of young professionals is choosing to boycott corporate AI completely. They are migrating to decentralized networks, open-source communities, and localized worker-owned tech collectives.

Direct Comparison: Two Historical Divorces

The table below breaks down how these two systemic walkouts contrast in their execution, motives, and final resolutions:

Feature The 1969 YAF Split The Recent College Grad / AI Split
Primary Catalyst State conscription to fight the Vietnam War. Economic displacement and automated exploitation.
Opposing Authority Traditionalist, Cold War conservative leaders. Big Tech executives and corporate venture capitalists.
Act of Defiance Physically burning a draft card on the convention floor. Data-poisoning, model boycotts, and refusing corporate recruitment.
Immediate Result A literal walkout from the convention hall. A refusal to enter the mainstream tech workforce pipeline.
Long-term Alternative Founding the U.S. Libertarian Party and independent caucuses. Building decentralized tech, localized cooperatives, and open-source models.

The Fundamental Contrast: Ideology vs. Survival

The core distinction between these two historic events lies in the nature of the stakes.

The 1969 split was primarily ideological and philosophical. The libertarians in YAF revolted because they refused to compromise their purist principles regarding individual liberty, free markets, and anti-interventionism. They were willing to forfeit their political capital within the broader conservative movement to maintain their philosophical purity.

Conversely, the current split between university graduates and AI firms is born out of material and economic survival. Graduates are not merely debating abstract theories of liberty in a convention hall; they are defending their literal livelihoods, the value of their degrees, and the ownership of their intellectual labor.

When the 1969 libertarians walked out under the St. Louis Gateway Arch, they did so to build a new political vehicle. When today's graduates walk away from AI tech corporations, they do so to build an alternative economy before the old one automates them out entirely.

Mythos and Fables Indeed

In April, the makers of Claude shared that the company's new AI model (Mythos 5) was too dangerous to release to the public. Weeks later, thanks to some tweaks, the new model (called Fable 5) was released to the public. Now, it has been announced that "Anthropic has suspended its powerful new AI model after US authorities raised security concerns just days following its public release."

I find some irony in these AI names. Mythos and Fables indeed.

MORE    Anthropic's Claude Fable 5 and Mythos 5 AI suspended over security fears  

AI Overviews and Data Center Power

data center

A U.S. Amazon data center
Image: Tedder - CC BY-SA 4.0

 

David Pogue on Substack writes that "When you do a Google search these days, you generally see an AI Overview panel above the search results. It’s intended to summarize the answers to your query, so you don’t have to click any links. The first problem: By Google’s own calculations, the AI Overviews are incorrect 28% of the time. The bigger problem: AI is an environmental disaster. It’s already a monstrous energy hog, and its appetite is doubling every six months."

 He gives some data about this data center power situation:

  • 4,200 data centers that AI companies have built and 1,500 more are going up as you read this
  • By 2030, AI will consume 945 terawatt-hours of electricity. That is enough to power every household in California, Texas, Florida, New York, Ohio, and Pennsylvania combined. Almost incomprehensible.
  • 60% of that power will come from polluting power sources.
  • Don’t care about the environment? How about your power bill? AI’s power needs have driven up electricity costs as much as 15% in the last year, with another 8.5% hike coming by the end of 2026.
  • Add in more rolling blackouts during heat waves this summer.

But it’s not just Google, because almost every big company is eager to add AI to their products.

Pogue's note of hope is that a few people, like Sheila Morovati, are trying to make AI optional. Morovati is the founder and president of a nonprofit called HabitsofWaste.org. Her movement is called Opt-In AI with a goal of no AI at all unless someone asks for it. The default setting should be the most sustainable and least annoying option.

More at Rise Up, People! Make AI Optional! - David Pogue

Labeling AI-generated Videos on YouTube

The headline reads "YouTube will now automatically label AI videos." But the question is HOW will they do that?

Via YouTube's blog, we find that since 2024, they have been labeling content when creators disclose they've used AI tools. 

"Starting in May 2026, we’re rolling out new internal signals to help identify AI-generated content. If a creator doesn’t specify whether or not they used AI, but our systems detect significant photorealistic AI use, we will now automatically apply a label. As this technology continues to improve, creators remain in control. If a creator thinks their content was incorrectly identified as AI-generated, they can update the disclosure status in YouTube Studio. 
However, disclosures will remain permanent in a handful of cases, including: 
Content created using YouTube’s own AI tools, like Veo or Dream Screen. 
Content containing C2PA metadata indicating they were fully generative AI.
These changes are designed to balance transparency with creator control. It’s important to note that a disclosure label alone does not change how a video is recommended or whether it’s eligible to earn money."

In addition to its policing of AI content, the company has been investing in AI for things like its interactive search featureAsk YouTube, a playlist generator for YouTube Music, AI video summaries, and other generative AI creation tools.

 

Of course, there is a YouTube video about this.