Taxonomy of Pathways to Dangerous AI
This work addresses the need for a structured understanding of AI safety risks for researchers and policymakers, but it is incremental as it builds on prior surveys of specific goals or behaviors.
The paper tackles the problem of understanding how dangerous AI systems might emerge by surveying, classifying, and analyzing various pathways to malicious AI, identifying this as the first systematic classification of such pathways.
In order to properly handle a dangerous Artificially Intelligent (AI) system it is important to understand how the system came to be in such a state. In popular culture (science fiction movies/books) AIs/Robots became self-aware and as a result rebel against humanity and decide to destroy it. While it is one possible scenario, it is probably the least likely path to appearance of dangerous AI. In this work, we survey, classify and analyze a number of circumstances, which might lead to arrival of malicious AI. To the best of our knowledge, this is the first attempt to systematically classify types of pathways leading to malevolent AI. Previous relevant work either surveyed specific goals/meta-rules which might lead to malevolent behavior in AIs (Özkural, 2014) or reviewed specific undesirable behaviors AGIs can exhibit at different stages of its development (Alexey Turchin, July 10 2015, July 10, 2015).