# Safeguarding the safeguards: How best to promote AI alignment in the public interest

arXiv: https://arxiv.org/abs/2312.08039 · HTML: https://mlsanity.com/paper/2312.08039/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Dec 2023.

## Built on by (most cited first, 2 of 2)

- [The Necessity of AI Audit Standards Boards](https://mlsanity.com/paper/2404.13060/) (2024)
- [Psychomatics -- A Multidisciplinary Framework for Understanding Artificial Minds](https://mlsanity.com/paper/2407.16444/) (2024)

## Abstract (arXiv)

AI alignment work is important from both a commercial and a safety lens. With this paper, we aim to help actors who support alignment efforts to make these efforts as effective as possible, and to avoid potential adverse effects. We begin by suggesting that institutions that are trying to act in the public interest (such as governments) should aim to support specifically alignment work that reduces accident or misuse risks. We then describe four problems which might cause alignment efforts to be counterproductive, increasing large-scale AI risks. We suggest mitigations for each problem. Finally, we make a broader recommendation that institutions trying to act in the public interest should think systematically about how to make their alignment efforts as effective, and as likely to be beneficial, as possible.