So performance here should be thought of more as ‘how good is the model at learning about a persona in fine-tuning and then being able to imitate/simulate that persona in deployment’. This is different from a model believing it is the persona or applying this knowledge to some concept of self. Good performance at this task does not require having a sense of self, this is just a precursor that may be necessary for situational awareness.
That’s correct. We tried to emphasize that our experiments are testing out-of-context reasoning, rather than situational awareness. We also emphasize that we test whether the model can emulate multiple fictitious chatbots (which have a different identity than GPT-3 or Llama), which wouldn’t make sense if the goal was to test whether the model has a sense of itself.
All the motivation for this project came from wanting to understand and forecast situational awareness and we want to encourage further work on that problem. This is why we’ve framed the paper around situational awareness, rather than simply talking about out-of-context reasoning. This is likely to cause some confusion if someone just skims the paper, but I hope that this will be reduced if people read more of the paper.
That’s correct. We tried to emphasize that our experiments are testing out-of-context reasoning, rather than situational awareness. We also emphasize that we test whether the model can emulate multiple fictitious chatbots (which have a different identity than GPT-3 or Llama), which wouldn’t make sense if the goal was to test whether the model has a sense of itself.
All the motivation for this project came from wanting to understand and forecast situational awareness and we want to encourage further work on that problem. This is why we’ve framed the paper around situational awareness, rather than simply talking about out-of-context reasoning. This is likely to cause some confusion if someone just skims the paper, but I hope that this will be reduced if people read more of the paper.