Executive summary: This exploratory post outlines the author’s personal model of AI risk and Effective Altruism’s role in addressing it, emphasizing a structured, cause-neutral approach to AI safety grounded in a mix of high-level doom scenarios, potential mitigations, and systemic market failures, while acknowledging uncertainty and inviting alternative perspectives.
Key points:
The author sees existential AI risk—especially scenarios where “everyone dies”—as the most salient concern, though they recognize alternative AI risks (e.g., value lock-in, S-risks) are also worth investigating.
They categorize AI risk using Yoshua Bengio’s framework of intelligence, affordances, and goals, mapping each to specific mitigation agendas such as interpretability, alignment, and governance.
A core rationale for AI risk plausibility is framed in economic terms: systemic market failures like lemon markets, externalities, and cognitive biases may prevent actors from internalizing catastrophic AI risks.
Practical agendas include pausing AI development, improving evaluations, incentivizing safety research, and developing pro-human social norms to counteract these failures.
The author reflects that their model unintentionally mirrors the EA framework of importance, tractability, and neglectedness—starting from doom, identifying mitigations, and explaining why others don’t prioritize them.
The post is cautious and reflective in tone, aiming more to clarify personal reasoning than to assert universal conclusions, and encourages readers to critique or build on the model.
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, and contact us if you have feedback.
Executive summary: This exploratory post outlines the author’s personal model of AI risk and Effective Altruism’s role in addressing it, emphasizing a structured, cause-neutral approach to AI safety grounded in a mix of high-level doom scenarios, potential mitigations, and systemic market failures, while acknowledging uncertainty and inviting alternative perspectives.
Key points:
The author sees existential AI risk—especially scenarios where “everyone dies”—as the most salient concern, though they recognize alternative AI risks (e.g., value lock-in, S-risks) are also worth investigating.
They categorize AI risk using Yoshua Bengio’s framework of intelligence, affordances, and goals, mapping each to specific mitigation agendas such as interpretability, alignment, and governance.
A core rationale for AI risk plausibility is framed in economic terms: systemic market failures like lemon markets, externalities, and cognitive biases may prevent actors from internalizing catastrophic AI risks.
Practical agendas include pausing AI development, improving evaluations, incentivizing safety research, and developing pro-human social norms to counteract these failures.
The author reflects that their model unintentionally mirrors the EA framework of importance, tractability, and neglectedness—starting from doom, identifying mitigations, and explaining why others don’t prioritize them.
The post is cautious and reflective in tone, aiming more to clarify personal reasoning than to assert universal conclusions, and encourages readers to critique or build on the model.
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, and contact us if you have feedback.