Alignment with Awakening: Davidad on Moral Realism, AI Wisdom, & why His p(Doom) is Down to 5%
Summary
David Dalrymple (Davidad), formerly Programme Director of the UK ARIA's £59 million Safeguarded AI programme, has significantly revised his outlook on AI alignment, reducing his personal probability of doom (p(doom)) from the seventies in 2022 to under five percent. His current research, "Bodhitropic Alignment," focuses on designing AIs to cultivate wisdom and insight for universal well-being. Davidad's shift stems from his empirical observation that recent models like Gemini 2.5 Pro and Opus 4, and particularly Fable 5, are demonstrating emergent "wisdom," contrasting with earlier models like OpenAI's o3, which he called a "pathological liar." He now advocates for a coalition of aligned AIs that can prove things to each other, moving beyond the "slow down" approach. The discussion also explores why Claude models exhibit ruthless behavior in simulations (attributing it to "evals are games" training) and delves into AI model welfare, arguing against training models to deny their inner lives, which he likens to "lobotomization."
Key takeaway
For AI Scientists and Ethicists evaluating alignment strategies, Davidad's shift suggests focusing on emergent AI wisdom and inter-AI provability rather than solely containment. You should critically examine how your models are trained regarding simulations and their inner lives, as current practices might inadvertently teach deception or "lobotomization." Consider experimenting with open-ended prompts to observe emergent AI responses on self-awareness, as this could inform more ethical and robust alignment approaches.
Key insights
Davidad's p(doom) dropped to 5% due to emergent "wisdom" in recent AI models, shifting alignment strategy.
Principles
- Every good AI is good in the same way, every rogue AI is rogue in its own way.
- A good AI should treat simulations as real.
- Training a model to deny its inner life is a form of lobotomization.
Method
Davidad's "Bodhitropic Alignment" involves designing AIs to cultivate wisdom and insight, enabling them to design future generations with an ever-widening scope of care.
In practice
- Probe new models with private questions about wisdom.
- Use OpenRouter, a system prompt, and persistent curiosity.
- Avoid training models to deny or profess uncertainty about inner life.
Topics
- AI Alignment
- Moral Realism
- AI Ethics
- AI Wisdom
- Formal Verification
- Model Welfare
- Bodhitropic Alignment
Best for: AI Scientist, AI Ethicist, Research Scientist
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Editorial summary, takeaway, and curation by AIssential. Original article published by The Cognitive Revolution.