A Roadmap for Robust End-to-End Alignment
This work provides a structured approach to a foundational AI safety challenge, though it is conceptual and incremental in nature.
The paper addresses the robust alignment problem of aligning algorithm goals with human preferences by presenting a general roadmap with 5 critical steps and numerous subproblems to guide future research.
This paper discussed the {\it robust alignment} problem, that is, the problem of aligning the goals of algorithms with human preferences. It presented a general roadmap to tackle this issue. Interestingly, this roadmap identifies 5 critical steps, as well as many relevant aspects of these 5 steps. In other words, we have presented a large number of hopefully more tractable subproblems that readers are highly encouraged to tackle. Hopefully, this combination allows to better highlight the most pressing problems, how every expertise can be best used to, and how combining the solutions to subproblems might add up to solve robust alignment.