Are We About to Lose Control of AI? | AI Reality Check
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What is the main concern regarding AI control?
Last week, Anthropic released a report with a scary-sounding title, When AI Builds Itself, and it came accompanied by a scary animation that shows machines replicating themselves exponentially, like cells in a petri dish. Now, the body of the report itself keeps these dark vibes going. I want to read you some actual quotes here from the intro to the report.
How significant is the fear of recursive self-improvement in AI?
They say... For most of AI's history, humans drove every step in its development cycle, but at Anthropic, we are delegating a growing share of AI development to AI systems themselves, which is speeding up our work. Taken far enough and given enough compute, this trend points to an AI system capable of fully autonomously designing and developing its own successor. This is called recursive self-improvement.
Are the fears surrounding AI development justified?
We are not there yet, and recursive self-improvement is not inevitable, but it could come sooner than most institutions are prepared for. A little bit later, they then add, AI that can build itself would be a major development in the history of technology, one that could bring enormous good for the world in science, healthcare, and beyond, but full recursive self-improvement also might increase the risks of humans losing control over AI systems.
Why doesn't faster software development lead to smarter AI?
Now, if you look at the headlines generated in response to this report, most of them focused on a section of the report that seemed to call for a worldwide pause on AI development to avoid this scenario of humans losing control. But if you read that section closer, you see that's not actually what the report says. Here's the actual wording.
How controllable are current AI tools?
If it were possible to effectively slow the development of this technology to give ourselves more time to deal with its immense implications, we think that would likely be a good thing. But if a slowdown simply lets the least cautious actors catch up technologically, it could leave everyone less safe. So in other words, Anthropic is saying, we'll only slow down if everyone else around the world does too. Otherwise, we have no choice.
What insights can we gain from the latest AI reports?
but to continue with our efforts at full speed. Now, look, this is pretty grim stuff. Anthropic is basically saying that we are potentially hurtling towards a world of AI that improves itself rapidly until we lose control over it. And they're saying there is nothing that we can do about it, except maybe continuing to publish solemn reports with fancy animations, and I guess also cash in on our stock options after an IPO. All right, so here's the key question. Are these fears justified? Well, it's Thursday, which means it's time for an AI Reality Check episode of this show, which is a good opportunity to go looking for some measured answers, and that is exactly what we are going to do. As always, I'm Cal Newport, and this is Deep Questions, the show for people seeking depth in a distracted world.
All right, so how much should we actually be afraid of recursive self-improvement? I want to look at the core charts from this anthropic report so we can see what they are pointing to that is giving them these RSI fears. All right, I'll load the first chart from the report up here on the page. It's called code contributed per quarter, per person by quarter. It's measuring how much lines of code their engineers are producing over time.
What are the implications of AI tools on software development?
And what we see is in 2021, 2022, 2023, 2024, the beginning of 2025, not much. And then the second half of 2025 and into the first half of 2026, the amount of code jumps up. All right. Here's how the report itself describes this trend. It says, a caveat, lines of code is an imperfect measure as it measures quantity over quality. So eight times lines of code per engineer per day in the second quarter of 2026 is almost certainly an overstatement of the true productivity gain. Nonetheless, it indicates an acceleration. All right.
What conclusions can we draw about AI's future capabilities?
So chart one, Once we introduced these tools in late 2025 for software development, we began producing a lot more code using AI. All right, let's go to the second major chart in this paper. This is called Claude Code Session Success Rate. What we see here is various color lines.
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Chapters
8 chapters
1
What is the main concern regarding AI control?
0:00–0:23
2
How significant is the fear of recursive self-improvement in AI?
0:23–0:50
3
Are the fears surrounding AI development justified?
0:50–1:18
4
Why doesn't faster software development lead to smarter AI?
1:18–1:40
5
How controllable are current AI tools?
1:40–2:05
6
What insights can we gain from the latest AI reports?
2:05–3:29
7
What are the implications of AI tools on software development?
3:29–4:04
8
What conclusions can we draw about AI's future capabilities?
4:04–20:31
Speakers
1 identifiedMore from Deep Questions with Cal Newport
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