Understanding and Avoiding AI Failures: A Practical Guide

• URL: http://arxiv.org/abs/2104.12582v4
• Date: Mon, 11 Mar 2024 18:58:33 GMT
• Title: Understanding and Avoiding AI Failures: A Practical Guide
• Authors: Heather M. Williams, Roman V. Yampolskiy
• Abstract summary: We create a framework for understanding the risks associated with AI applications. We also use AI safety principles to quantify the unique risks of increased intelligence and human-like qualities in AI.
• Score: 0.6526824510982799
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: As AI technologies increase in capability and ubiquity, AI accidents are becoming more common. Based on normal accident theory, high reliability theory, and open systems theory, we create a framework for understanding the risks associated with AI applications. In addition, we also use AI safety principles to quantify the unique risks of increased intelligence and human-like qualities in AI. Together, these two fields give a more complete picture of the risks of contemporary AI. By focusing on system properties near accidents instead of seeking a root cause of accidents, we identify where attention should be paid to safety for current generation AI systems.

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