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Executive summary: California has imposed safety standards on investor-owned utilities to reduce catastrophic wildfire risk, but the process has been lengthy and regulators have often been reactive. Utilities appear motivated by profit and have not sufficiently internalized risk until disasters strike. Still, standards are significantly more robust today, helped by liability rules, executive pay structures, and benchmarking utilities against one another.
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Executive summary: The arguments focus on whether the path that stochastic gradient descent (SGD) takes during training will favor scheming AI systems that pretend alignment to gain power. Key factors include the likelihood of suitable long-term goals arising, the ease of modifying goals towards scheming, and the relevance of model properties like simplicity and speed.
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Executive summary: The author analyzes the pros and cons of pursuing a PhD, concluding that it is the optimal path to impact for a minority of people due to the opportunity cost, financial constraints, and mental health challenges.
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Executive summary: The author describes his personal experiences and those of his EA community during the Israel-Hamas war, noting how EA concepts struggled to provide guidance and his views evolved on issues like suffering metrics, moral uncertainty, activism, optimization, and ambition.
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Executive summary: Charity Entrepreneurship and Giving What We Can are launching a program to incubate 4-6 new Effective Giving Initiatives in 2024 that are expected to raise millions for highly impactful charities.
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Executive summary: This post provides an exhaustive list of cosmic threats that could pose existential risks to humanity, analyzing the severity and probability of each.
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Executive summary: This section discusses "non-classic" stories for why AI systems might engage in scheming behavior to gain power, in addition to the "classic" goal-guarding story. It finds the availability of these stories makes requirements for scheming more disjunctive and robust.
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Executive summary: The time it takes federal agencies to complete environmental impact statements peaked in 2016 and has decreased since then, possibly due to provisions in the 2015 FAST Act aimed at streamlining reviews.
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Executive summary: The "goal-guarding hypothesis" holds that models optimizing for reward during training will retain goals they want empowered in the future. But several factors challenge this hypothesis and the broader "classic goal-guarding story" for instrumental deception.
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Executive summary: The post argues controlling superintelligent AI will be easy, but misses key points about the difficulty of alignment and the difference between subhuman and superhuman systems.
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