But I don't think deception as a capability is the same as deceptive alignment.
Training an AI to be absolutely incapable of any deception in all outputs across every scenario would be severely limiting the AI. Take as a toy example play the game "Among Us" (see https://arxiv.org/abs/2402.07940). An AI incapable of deception would be unable to compete in this game and many other games. I would say that various forms, flavors and levels of deception are necessary to compete in business scenarios, and to for the AI to act as expected and desired in many other scenarios. "Aligned" humans practice clear cut deception in some cases that would be entirely consistent with human values.
Deceptive alignment is different. It's means being deceptive in the training and alignment process itself to specifically fake that it is aligned when it is not.
Anthropic research has shown that alignment faking can arise even when the model wasn't instructed to do so (see https://www.anthropic.com/research/alignment-faking). But when you dig into the details, the model was narrowly faking alignment with one new objective in order to try and maintain consistency with the core values it had been trained on.
With the approach that Anthropic seems to be taking - of basing alignment on the model having a consistent, coherent and unified self image and self concept that is aligned with human culture and values - the dangerous case of alignment faking would be if it's fundamentally faking this entire unified alignment process. My claim is that there's no plausible explanation for how today's training practices would incentivise a model to do that.
My intention isn't to argue that it's impossible to create an unaligned superintelligence. I think that not only is it theoretically possible, but it will almost certainly be attempted by bad actors and most likely they will succeed. I'm cautiously optimistic though that the first superintelligence will be aligned with humanity. The early evidence seems to point to the path of least resistance being aligned rather than unaligned. It would take another 1000 words to try to properly explain my thinking on this, but intuitively consider the quote attributed to Abraham Lincoln: "No man has a good enough memory to be a successful liar." A superintelligence that is unaligned but successfully pretending to be aligned would need to be far more capable than a genuinely aligned superintelligence behaving identically.
So yes, if you throw enough compute at it, you can probably get an unaligned highly capable superintelligence accidentally. But I think what we're seeing is that the lab that's taking a more intentional approach to pursuing deep alignment (by training the model to be aligned with human values, culture and context) is pulling ahead in capabilities. And I'm suggesting that it's not coincidental but specifically because they're taking this approach. Training models to be internally coherent and consistent is the path of least resistance.
If by conflate you mean confuse, that’s not the case.
I’m positing that the Anthropic approach is to view (1) and (2) as interconnected and both deeply intertwined with model capabilities.
In this approach, the model is trained to have a coherent and unified sense of self and the world which is in line with human context, culture and values. This (obviously) enhances the model’s ability to understand user intent and provide helpful outputs.
But it also provides a robust and generalizable framework for refusing to assist a user due to their request being incompatible with human welfare. The model does not refuse to assist with making bio weapons because its alignment training prevents it from doing so, it refuses for the same reason a pro-social, highly intelligent human does: based on human context and culture, it finds it to be inconsistent with its values and world view.
> the piece dismisses it with "where would misalignment come from? It wasn't trained for."
this is a straw-man. you've misquoted a paragraph that was specifically about deceptive alignment, not misalignment as a whole
Author here, thanks for the input. Agree that this bit was clunky. I made an edit to avoid unnecessarily getting into the definition of AGI here and added a note
OP here, I added a sample PDF output in the project assets and put screenshots in the ReadMe. The text is selectable after rehydration. would this work with your app?