Like Sabine Hossenfelder, I Was Offered Money to Tell You AI Will Kill Us
Long-form29:28Science & TechnologyPublished Sep 22, 2026, 4:00 PM · 3w ago
Views
657,623
+368 views/hour
Views / hour now
368
measured 1h ago
Peak views / hour
643
1d ago
First 24 hours
—
not tracked from upload
Engagement
7.0%
likes + comments / views
Likes
37.5K
5.7% of views
Comments
8.3K
1.26% of views
Est. ad revenue
$4,603–$10,522
lifetime, $7–16 RPM
Checked every 12 h while the video is this age · last check 1h ago · next in 615 min. YouTube itself updates public counts with a short delay.
Avg views / day
24.1K
since upload
vs channel median
1.9×
this video's views ÷ the channel's usual
Rank in channel
#1
of 20 tracked
Views over time
5 readings
Total views Views gained per hour
Description
Can AI really improve itself recursively until it becomes powerful enough to cause human extinction? Nobody sponsored this video, I turned down funding specifically for this topic, I do not work for any frontier AI lab, and I have no financial stake in whether the answer turns out to be yes or no. What I do have is a PhD in Computer Science and research experience, so instead of relying on headlines, CEO warnings or expert forecasts, I went through the research itself. Across twelve papers, I found evidence that genuinely surprised me, some of it far more concerning than I expected, but also major gaps between what has actually been demonstrated and what is being claimed publicly. So the question I wanted to answer was simple: where is the scientific evidence that gets us from recursive self-improvement to zero humans?
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📌 Chapters
00:00 Introduction
03:54 It's More Real Than I expected
06:23 Conclusion 1
08:04 The Hidden Dependency
14:33 Conclusion 2
15:01 Could the bottleneck vanish?
19:24 Even if the bottleneck gets solved, does the loop run away?
23:26 Fine. Grant everything. Show me extinction.
27:50 Don't Look Up
📚 SOURCES & FURTHER READING
Chen, Wang & Qu (2026). “Recursive Self-Improvement in AI.”
https://arxiv.org/abs/2607.07663
Zhang, Hu et al. (2025). “Darwin Gödel Machine.”
https://arxiv.org/abs/2505.22954
Novikov, Vu et al. (2025). “AlphaEvolve.”
https://arxiv.org/abs/2506.13131
Wijk, Lin et al. (2024). “RE-Bench.”
https://arxiv.org/abs/2411.15114
Wen, Qiu et al. (2026). “Anthropic Automated Weak-to-Strong Researcher.”
https://alignment.anthropic.com/2026/automated-w2s-researcher/
Kirgis, Kapoor, Narayanan et al. (2026). “Can AI Agents Conduct Open-Ended AI Research?”
https://arxiv.org/abs/2607.27191
Cunningham et al. (2026). “The Economics of Recursive Self-Improvement.”
https://arxiv.org/abs/2609.15802
Burtsev (2026). “Recursive Criticality of AI Self-Improvement.”
https://arxiv.org/abs/2609.00137
Google DeepMind (2026). “From AGI to ASI.”
https://deepmind.google/research/publications/239142/
International AI Safety Report (2026). “International AI Safety Report 2026.”
https://internationalaisafetyreport.org/publication/international-ai-safety-report-2026
OpenAI (2026). “Research Acceleration: A View Inside OpenAI.”
https://openai.com/index/research-acceleration-view-inside-openai/
Grace et al. (2024). “Thousands of AI Authors on the Future of AI.”
https://arxiv.org/abs/2401.02843
#AI #ArtificialIntelligence #AISafety #RecursiveSelfImprovement #AGI #Superintelligence #ComputerScience #AIResearch #AIExtinction
Details
- Published
- Sep 22, 2026, 4:00 PM
- Length
- 29:28 (1,768 s)
- Format
- Long-form
- Category
- Science & Technology
- Audio language
- EN
- Quality
- HD
- Captions
- No
- Made for kids
- No
- Licensed content
- Yes
- Video ID
- claxN4oxDuY
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