TL;DR: (AI-generated ๐ค)
The author identifies sixteen weaknesses in the classic argument for AI risk. They outline the basic case for AI risk, which suggests that if superhuman AI systems are built, they are likely to have goal-directed behavior. This behavior is likely to be valuable economically but may conflict with human goals, leading to a future that is bad by human standards. Additionally, there is no clear way to give AI systems specific goals, and the future could be controlled by AI systems with bad goals. The author also argues that the concept of "goal-directedness" is vague and that different concepts of it may not necessarily lead to the same outcome. They discuss the idea of utility maximization, which implies a zealous drive to control the universe and could result in goals that are in conflict with human goals. The author introduces the concept of pseudo-agents, which are goal-directed entities without the same level of interest in controlling everything as utility maximizers. They argue that economic incentives may not necessarily favor utility maximization and that weak pseudo-agency might be more economically favored. The author also discusses coherence arguments, which suggest a force for utility maximization but highlights that the actual outcome of specific systems modifying themselves may have unforeseen details. Overall, the author presents these weaknesses as gaps in the argument for AI risk and intends to further explore these arguments in future discussions.
NOTE: This summary may not be accurate. The text was longer than my maximum input length, so I had to truncate it.
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