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Modeling AGI Safety Frameworks with Causal Influence Diagrams (arxiv.org)
3 points by sel1 on Jun 22, 2019 | hide | past | pdf | discuss on HN

In plain words: Safety plans for advanced AI are drawn as flowcharts showing what each part of the system optimizes and how the parts affect one another. Putting several leading plans into the same diagram style makes their assumptions about cause and effect easy to compare.

Abstract

Proposals for safe AGI systems are typically made at the level of frameworks, specifying how the components of the proposed system should be trained and interact with each other. In this paper, we model and compare the most promising AGI safety frameworks using causal influence diagrams. The diagrams show the optimization objective and causal assumptions of the framework. The unified representation permits easy comparison of frameworks and their assumptions. We hope that the diagrams will serve as an accessible and visual introduction to the main AGI safety frameworks.

Tom Everitt, Ramana Kumar, Victoria Krakovna, Shane Legg
arXiv:1906.08663 · cs.AI · submitted Jun 20, 2019
abstract · pdf · html · IJCAI 2019 AI Safety Workshop

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