- From: Paola Di Maio <paoladimaio10@gmail.com>
- Date: Sun, 24 Nov 2019 08:21:52 +0800
- To: Dave Raggett <dsr@w3.org>
- Cc: W3C AIKR CG <public-aikr@w3.org>
- Message-ID: <CAMXe=SoXTF-+Wyw9kWJRPvBKgT3OJ-yT9esm7eUWamUZAuXoQA@mail.gmail.com>
Dave, and all . Instead of focusing on manual development of knowledge representations, it would be advantageous to look at how these can be learned through interactions in the real world or simulated virtual worlds, drawing inspiration from the cognitive and linguistic stages of development of young human infants. Glad this is of interest to you too. In Edinburgh I gave a talk once on biologicl inspired systems and more recently one of the projects I collaborated with (not as a PI, so I do not have the ability to change the project scope etc) was indeed designed to learn how knowledge emerges in infants, However there are fundamental design flaws in the research, and data collection is difficult and pointless if the research design is not sound. A lot of issues - too many to discuss in depth here - but in brief: - although intelligent systems are/can be inspired by humans and nature, we have limited capability of engineering natural intelligence . I argue that this is because we still do not understand what intelligence is and how it develops, not only as a mechanism, but also as consciousness - when we design AI systems, the process of learning has to be designed. If you want to produce an intelligent agent without having to engineer it, then you have to make a baby :-) for everything else, standard systems design is necessary (or be ready to generate an artificial monster) - if you want to generate some kind of intelligent agent, say a NN, and do away with good system design practices of planning what it does, how and why it is going to be deployed, etc you are mixing (or trying to mix) natural intelligence with artificial, and should really not let it go outise the lab too soon- Apart from the fact that there are scientific and technical challenges to be overcome, there are also a lot of bigger questions. Human intelligence (which is still not well understood) evolves as part of something bigger, which is human nature in all its facets Humans feel pain, have bad dreams, have a consciousness, a heart, feelings, emotions discernment Intelligence is generally constrained by the other human factors. - recent science using fmri shows that there is knowledge representation in the brain we just dont know how to recognize it yet, and that infants use learning as a way of forming concepts and language, so learning cannot be extricated from KR (so that knowledge without representation is interesting to study, but it clearly only strengthens the argument for KR) - Tha KR can be inferred from observations of how the world works, rather than imposed on how the world works, is the work I am doing - That KR is necessary to explainability and learning and verifiability is what I have observed so far PDM > > On 23 Nov 2019, at 02:24, Paola Di Maio <paola.dimaio@gmail.com> wrote: > > I think I found the culprit, at least one of the papers responsible for > this madness of doing > AI without KR > https://web.stanford.edu/class/cs331b/2016/presentations/paper17.pdf > I find the paper very interesting although I disagree > > Do people know of other papers that purport a similar hypothesis (that KR > is not indispensable in AI for whatever reason?) > thanks a lot > PDM > > > Dave Raggett <dsr@w3.org> http://www.w3.org/People/Raggett > W3C Data Activity Lead & W3C champion for the Web of things > > > >
Received on Sunday, 24 November 2019 00:22:58 UTC