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- W4312337561 abstract "The Value Alignment Problem in AI research is the challenge of how to “align the values” of AI with those of humans such that, as AI systems develop, they do not become an “existential risk” to humans. A fundamental feature of how the problem is currently understood is that AI systems do not take the same things to be relevant as humans do, for example, eradicating the human species in order to “solve climate change”. Conceived in this way, the Value Alignment problem is “how do we make relevant to AI what is relevant to humans?” Existing approaches do not address this feature. This paper offers an approach, inspired by Enactive and “4E” cognition, which is oriented toward engaging the Alignment Problem in this way. Naturally, there are benefits and challenges." @default.
- W4312337561 created "2023-01-04" @default.
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- W4312337561 date "2022-01-01" @default.
- W4312337561 modified "2023-10-15" @default.
- W4312337561 title "An Enactive Approach to Value Alignment in Artificial Intelligence: A Matter of Relevance" @default.
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- W4312337561 doi "https://doi.org/10.1007/978-3-031-09153-7_10" @default.
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