A Roadmap for Robust End-to-End Alignment

TL;DR

This paper outlines a comprehensive roadmap for achieving robust alignment between algorithms and human preferences, emphasizing five critical steps and numerous subproblems to guide future research in the field.

Contribution

It introduces a structured roadmap with five key steps and detailed subproblems to advance the understanding and solutions for robust alignment.

Findings

Identifies five critical steps for robust alignment.

Highlights numerous subproblems for targeted research.

Proposes a collaborative approach combining solutions.

Abstract

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.