Human Control: Definitions and Algorithms

Ryan Carey, Tom Everitt
5/31/2023
cs.AI

No confident code implementation found for this paper. 2 possible matches can be shown below.

Abstract

How can humans stay in control of advanced artificial intelligence systems? One proposal is corrigibility, which requires the agent to follow the instructions of a human overseer, without inappropriately influencing them. In this paper, we formally define a variant of corrigibility called shutdown instructability, and show that it implies appropriate shutdown behavior, retention of human autonomy, and avoidance of user harm. We also analyse the related concepts of non-obstruction and shutdown alignment, three previously proposed algorithms for human control, and one new algorithm.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 2 weaker matches are hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{carey2023human,
  title  = {Human Control: Definitions and Algorithms},
  author = {Ryan Carey and Tom Everitt},
  year   = {2023},
  eprint = {2305.19861},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2305.19861v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2305.19861.svg)](https://codeofpaper.com/paper/2305.19861)

Discussion