Paperclip maximizer

An expected paperclip maximizer is an agent whose utility function is linear in the number of paperclips, or in paperclip-seconds (each second that each paperclip exists). See http://wiki.lesswrong.com/wiki/Paperclip_maximizer.

The agent may be a bounded maximizer rather than an objective maximizer without changing the key ideas; the core premise is just that, given actions A and B where the paperclip maximizer has evaluated the consequences of both actions, the paperclip maximizer always prefers the action that it expects to lead to more paperclips.

Key ideas that the notion of an expected paperclip maximizer illustrates:

• A Reflective paperclip maximizer does not change its own utility function to something other than 'paperclips', since this would be expected to lead to fewer paperclips existing.
• A paperclip maximizer instrumentally prefers the standard convergent instrumental goals - it will seek access to matter, energy, and negentropy in order to make paperclips, try to build efficient technology for colonizing the galaxies to transform into paperclips, do whatever science is necessary to gain the knowledge to build such technology optimally, etcetera.
• "The AI does not hate you, nor does it love you, and you are made of atoms it can use for something else."