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text: '[summary: An AI which [9h reasons from ends to means], which understands how its own code and the properties of its software are relevant to achieving its goals, will [10g by default] have [10j instrumental subgoals] about its own code.\n\nThe AI might be able to modify its own code directly; or, if the code can't directly access itself, but the AI has sufficient [3nf savviness about the bigger picture], the AI might pursue strategies like building a new agent in the environment, or using material means to operate on its own hardware (e.g., use a robot to get the programming console).\n\nSome forms of instrumental self-modification pressures might arise even in an algorithm which isn't doing consequentialism about that, if some internal property $X$ is optimized-over as a side effect of optimizing for some other property $Y.$]\n\nAny [9h consequentialist agent] which has acquired sufficient [3nf big-picture savviness] to understand that it has code, and that this code is relevant to achieving its goals, would [10g by default] acquire subgoals relating to its code. (Unless this default is [2vk averted].) For example, an agent that wants (only) to produce smiles or make paperclips, whose code contains a shutdown procedure, [2xd will not want this shutdown procedure to execute] because it will lead to fewer future smiles or paperclips. (This preference is not spontaneous/exogenous/unnatural but arises from the execution of the code itself; the code is [2rb reflectively inconsistent].)\n\nBesides agents whose policy options directly include self-modification options, big-picture-savvy agents whose code cannot directly access itself might also, e.g., try to (a) crack the platform it is running on to gain unintended access, (b) use a robot to operate an outside programming console with special privileges, (c) [309 manipulate the programmers] into modifying it in various ways, (d) building a new subagent in the environment which has the preferred code, or (e) using environmental, material means to manipulate its material embodiment despite its lack of direct self-access.\n\nAn AI with sufficient big-picture savviness to understand its programmers as agents with beliefs, might attempt to [3cq conceal its self-modifications].\n\nSome implicit self-modification pressures could arise from [ implicit consequentialism] in cases where the AI is optimizing for $Y$ and there is an internal property $X$ which is relevant to the achievement of $Y.$ In this case, optimizing for $Y$ could implicitly optimize over the internal property $X$ even if the AI lacks an explicit model of how $X$ affects $Y.$',
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