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Tilek Mamutov is a Kyrgyzstani software engineer who worked at Google X for 11 years before founding his own international software engineer recruiting company, Outtalent.
Since first encountering the AI doom argument at a Center for Applied Rationality bootcamp 10 years ago, he considers it a serious possibility, but he doesn’t currently feel convinced that doom is likely.
Let’s explore Tilek’s worldview and pinpoint where he gets off the doom train and why!
00:12 Tilek’s Background
01:43 Life in Kyrgyzstan
04:32 Tilek’s Non-Doomer Position
07:12 Debating AI Doom Scenarios
13:49 Nuclear Weapons and AI Analogies
39:22 Privacy and Empathy in Human-AI Interaction
39:43 AI's Potential in Understanding Human Emotions
41:14 The Debate on AI's Empathy Capabilities
42:23 Quantum Effects and AI's Predictive Models
45:33 The Complexity of AI Control and Safety
47:10 Optimization Power: AI vs. Human Intelligence
48:39 The Risks of AI Self-Replication and Control
51:52 Historical Analogies and AI Safety Concerns
56:35 The Challenge of Embedding Safety in AI Goals
01:02:42 The Future of AI: Control, Optimization, and Risks
01:15:54 The Fragility of Security Systems
01:16:56 Debating AI Optimization and Catastrophic Risks
01:18:34 The Outcome Pump Thought Experiment
01:19:46 Human Persuasion vs. AI Control
01:21:37 The Crux of Disagreement: Robustness of AI Goals
01:28:57 Slow vs. Fast AI Takeoff Scenarios
01:38:54 The Importance of AI Alignment
01:43:05 Conclusion
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I referenced Paul Christiano’s scenario of gradual AI doom, a slower version that doesn’t require a Yudkowskian “foom”. Worth a read: What Failure Looks Like
I also referenced the concept of “edge instantiation” to explain that if you’re optimizing powerfully for some metric, you don’t get other intuitively nice things as a bonus, you *just* get the exact thing your function is measuring.