Science, Technology & the Future | Do Machines Understand? - David Kremelberg - AGI17 @scfu | Uploaded December 2018 | Updated October 2024, 9 hours ago.
Understanding seems central to the human ability to assess our own capacity for affecting change in particular contexts on particular tasks. Most humans not trained in mountain climbing will turn down an offer to climb Mount Everest. They also have an easy time explaining why they turn it down, and can probably cook up a rough outline for the kind of training that might make them change their mind. We call it a lack of understanding when issues central to a topic or problem are blissfully ignored by someone trying to solve it, and consider it a hopeless case when repeated attempts at explaining to them that they don't have sufficient understanding of the subject to make any important decisions about it are ignored.
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?
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?'
researchgate.net/profile/David_Kremelberg
linkedin.com/in/david-kremelberg
#AGI17 #AGI #ArtificialIntelligence #Understanding #MachineUnderstanding #CommonSence #ArtificialGeneralIntelligence #PhilMind
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- Science, Technology & the Future
Understanding seems central to the human ability to assess our own capacity for affecting change in particular contexts on particular tasks. Most humans not trained in mountain climbing will turn down an offer to climb Mount Everest. They also have an easy time explaining why they turn it down, and can probably cook up a rough outline for the kind of training that might make them change their mind. We call it a lack of understanding when issues central to a topic or problem are blissfully ignored by someone trying to solve it, and consider it a hopeless case when repeated attempts at explaining to them that they don't have sufficient understanding of the subject to make any important decisions about it are ignored.
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?
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?'
researchgate.net/profile/David_Kremelberg
linkedin.com/in/david-kremelberg
#AGI17 #AGI #ArtificialIntelligence #Understanding #MachineUnderstanding #CommonSence #ArtificialGeneralIntelligence #PhilMind
Many thanks for watching!
Consider supporting SciFuture by:
a) Subscribing to the SciFuture YouTube channel: youtube.com/subscription_center?add_user=TheRationalFuture
b) Donating
- Bitcoin: 1BxusYmpynJsH4i8681aBuw9ZTxbKoUi22
- Ethereum: 0xd46a6e88c4fe179d04464caf42626d0c9cab1c6b
- Patreon: patreon.com/scifuture
c) Sharing the media SciFuture creates: scifuture.org
Kind regards,
Adam Ford
- Science, Technology & the Future
