An Enactivist account of Mind Reading in Natural Language Understanding
This work addresses the classic AI-hard problem of understanding human language, offering a novel perspective that could improve systems like Alexa and Siri, though it appears incremental as it builds on existing enactivist ideas.
The paper tackles the problem of Natural Language Understanding by exploring how humans communicate through 'mind reading' rather than symbolic representation transfer, and proposes a computational 'cheat' inspired by enactivist theory to simulate this process.
In this paper we apply our understanding of the radical enactivist agenda to the classic AI-hard problem of Natural Language Understanding. When Turing devised his famous test the assumption was that a computer could use language and the challenge would be to mimic human intelligence. It turned out playing chess and formal logic were easy compared to understanding what people say. The techniques of good old-fashioned AI (GOFAI) assume symbolic representation is the core of reasoning and by that paradigm human communication consists of transferring representations from one mind to another. However, one finds that representations appear in another's mind, without appearing in the intermediary language. People communicate by mind reading it seems. Systems with speech interfaces such as Alexa and Siri are of course common, but they are limited. Rather than adding mind reading skills, we introduced a "cheat" that enabled our systems to fake it. The cheat is simple and only slightly interesting to computer scientists and not at all interesting to philosophers. However, reading about the enactivist idea that we "directly perceive" the intentions of others, our cheat took on a new light and in this paper look again at how natural language understanding might actually work between humans.