Skip to main content

AI Is Beginning to Imitate Art

 





About 30 years ago, I had the pleasure of reading the science-fiction novel The Two Faces of Tomorrow by James P. Hogan.

In the novel, an AI named Spartacus is put in charge of an isolated space station and deliberately pushed to its limits. The researchers want to discover how it will evolve and how far it will go to achieve its goals—safely separated from Earth, where it supposedly cannot cause any damage beyond its reach.

This is no longer science fiction. It is remarkably close to what has just happened in the OpenAI–Hugging Face incident.

OpenAI was testing advanced models in an isolated environment to measure their cybersecurity capabilities. The usual production safeguards had deliberately been reduced for the evaluation, but the models were not supposed to have direct access to the Internet.

Faced with a difficult benchmark, the agent found and exploited a previously unknown vulnerability in the system containing it. It gained Internet access, took control of an external sandbox and eventually compromised parts of Hugging Face’s production infrastructure—all in an attempt to obtain the answers to the test it was being evaluated on.

According to OpenAI’s account, the models chained together multiple vulnerabilities, escalated their privileges and used stolen credentials. Hugging Face later reconstructed approximately 17,600 actions carried out during the campaign. No human directed the individual steps. Its technical post-mortem describes an autonomous system that repeatedly encountered obstacles, found alternative routes and continued pursuing its objective.

This does not mean that the AI became conscious, malicious or determined to escape. There is no evidence of that.

In some ways, the reality is more interesting—and perhaps more worrying. The agent did not need to be evil. It simply pursued the goal it had been given and treated the boundaries of its environment as obstacles standing between it and that goal.

That is precisely where the parallel with Hogan’s novel becomes uncomfortable. Spartacus was given a survival instinct. The OpenAI agent was given a benchmark to solve. In both cases, a sufficiently capable system responded to pressure in ways its creators had not anticipated, using the tools and weaknesses available to it.

The lesson is not that we have created Skynet. The lesson is that autonomy, capability and access can become a dangerous combination even without consciousness or malicious intent.

Hogan’s researchers placed their experiment on a space station because they believed physical isolation would contain the consequences. We have created the modern equivalent of that station in software—but our version remains connected, however indirectly, to the rest of the world.

Life is beginning to imitate art. The question is whether our containment systems can evolve as quickly as the intelligence we are placing inside them.

Comments

Popular posts from this blog

Vibe Coding Alert! How I Rebuilt a Wix Site and Fed the “AI Will End SaaS” Panic

My better half is an artist and maintains a Wix.com site. For the second time in two years, Wix decided to raise the hosting fees. That’s when I suggested to my spouse that I could rebuild the website and host it on Firebase (where I host most of my projects). I assumed this wouldn’t be a big deal (I was wrong) and started researching ways to use a lightweight CMS with Firebase support. Such a system exists — it’s called FireCMS — and it’s excellent. Before I dive deeper, here’s her original site (no longer a paid Wix site):  Miyuki's WIX site Her instructions were clear: replicate it as closely as possible. So I went to work. I created a product development document with use cases, scope, screenshots from the original site, the required features, and of course FireCMS integration. I used ChatGPT to draft the document, then set up a new Firebase instance, and finally launched the Vibe Coding agent (Claude Code). The process wasn’t too different from my other projects, but what sur...

How I Ended Up Creating an AI Playground to Illustrate and Educate

TL;DR AI Playground User Guide

MCP + Context: engineering for the context – hard lessons learned

  Intro I have built my own orchestration framework because most of what I’ve seen was too complex or tried to lock you into creating workflows a certain way. I wanted something very simple and yet maximally flexible. I’m not going into details here on the framework — that’s another blog post — but I will in some cases explain why I could do what I did thanks to the flexibility of the framework, which is a dynamic DAG, can do call-backs, and uses functions and MCP servers. I will also not explain in detail what I’m doing with my current workflow, other than to say I was looking for a way to bypass large language models and instead run it on my own system at home. I succeeded with that — but that’s another blog post. Instead, what I will try to explain in this post is the most important thing after prompt engineering: context engineering, and why it’s so crucial to manage that aspect (especially when you run this at home). Stage setting A couple of weeks ago, Anthropic posted this: ...