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Necessary Ingredients for Understanding in AI - David Kremelberg - AGI17

186 views · Published 9 December 2018 · 11:09 · Indexed 16 October 2026
Channel: Science, Technology & the Future · 2018 · Science & Technology
Historically, the use of the term understanding in AI has mostly focused on natural language, which relates to the parsing and manipulation of linguistic tokens, and scene or image understanding, which again relates to parsing or largely semantics-free processing, with any discussion of understanding proper a rare occurrence. To the field of AGI, for which the topic of generality is central, this state of affairs would seem far from ideal. To investigate the phenomenon of understanding, compare systems with respect to their potential for understanding, and get to the crux of what understanding really is, seems important enough to give it more scrutiny.

Part of a session on Machine Understanding held at AGI17 - see : http://cadia.ru.is/workshops/uuw2017/

Further reading: Understanding and Common Sense: Two Sides of the Same Coin?
https://link.springer.com/chapter/10.1007/978-3-319-63703-7_19
Abstract: The concept of “common sense” (“commonsense”) has had a visible role in the history of artificial intelligence (AI), primarily in the context of reasoning and what’s been referred to as “symbolic knowledge representation.” Much of the research on this topic has claimed to target general knowledge of the kind needed to ‘understand’ the world, stories, complex tasks, and so on. The same cannot be said about the concept of “understanding”; although the term does make an appearance in the discourse in various sub-fields (primarily “language understanding” and “image/scene understanding”), no major schools of thought, theories or undertakings can be discerned for understanding in the same way as for common sense. It’s no surprise, therefore, that the relation between these two concepts is an unclear one. In this review paper we discuss their relationship and examine some of the literature on the topic, as well as the systems built to explore them. We agree with the majority of the authors addressing common sense on its importance for artificial general intelligence. However, we claim that while in principle the phenomena of understanding and common sense manifested in natural intelligence may possibly share a common mechanism, a large majority of efforts to implement common sense in machines has taken an orthogonal approach to understanding proper, with different aims, goals and outcomes from what could be said to be required for an ‘understanding machine.’

Bio: David Kremelberg currently works at the Icelandic Institute for Intelligent Machines. He does research in Artificial Intelligence, Social Psychology, and Quantitative Social Research. One of his publications on 'understanding' is 'Understanding and Common Sense: Two Sides of the Same Coin?'

https://www.researchgate.net/profile/David_Kremelberg
https://www.linkedin.com/in/david-kremelberg

#AGI17 #AGI #ArtificialIntelligence #Understanding #MachineUnderstanding #CommonSence #ArtificialGeneralIntelligence #PhilMind 


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Necessary Ingredients for Understanding in AI - David Kremelberg - AGI17

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