Re: First Deliverable, Outline and Draft

Dave

thanks for the questions and pointers-
Yes,  agree on the point that AI is changing everything is chancing fast,
and unfortunately many students and lecturers remain in the dark of key
issues pertaining to KR, because they are indoctrinated into following the
dogma of the day/

 KR is the handle we can still hold on to to keep some grip
on AI developments, and why I am doing this

The more AI evolves, the more we need to hold on to  explicit KR

I have reviewed the texts you cite, but they all provide different emphases
and views on KR, and each
come with weaknesses and strengths gaps. None include many KR approaches
which have emerged from research, so I am trying to figure out what is
causing these deficiencies

 there are at least two faults, one are omissions, and one are distortions
- things are purported to be what they are not -

This is part of the problem I am addressing in a research paper. My work
as a lecturer and research is partly driven by my experiences working in
Universities where I gather first hand of what is going on
There is something going on that is misleading students

So the evaluation of the teaching resources, gaps and how to to address
them is sometime I am doing  a for curriculum development exercise,
secondary outcomes are likely to result in a paper publication. and if
useful it can also be used in the group report if/when  we get to it.

Thank you also for the slides, if a paper with the full narrative or a
recording is available, that would be helpful. If you can frame this talk
with a few additional sentences the content of the slides to the aims of
the CG. we can add it to the resources and include it in the report

On Fri, Dec 6, 2019 at 7:18 PM Dave Raggett <dsr@w3.org> wrote:

> Hi Paola,
>
> Are these colleges ignoring well known AI text books, e.g. Russell &
> Norvig "Artificial Intelligence: A Modern Approach"?  I understand that a
> new edition is about to be released. Then there are books focusing on
> knowledge engineering, e.g. Kendal & Green “An introduction to knowledge
> engineering”, and Liebowitz “Knowledge management: learning from knowledge
> engineering”.
>
> Many of these books are rather expensive, so an alternative is to look at
> University courses where these are available online. Search for terms like
> “knowledge engineering lecture”. It is easy to find lecture notes, slides
> and videos.
>
> If colleges are ignoring existing resources, why would they take note of a
> W3C CG Report?
>
> I fully expect that AI will change dramatically over the next few years so
> that much of the existing courseware will become obsolete. We will see a
> merging of symbolic and sub-symbolic techniques based upon insights from
> the cognitive sciences. In addition, deep learning for single tasks will be
> replaced by modern evolutionary based approaches that cover a broad range
> of capabilities and which integrate into knowledge based approaches,
> replicating and improving on human performance.
>
> See the talk I presented to the AIOTI semantic interoperability group this
> week:
>
> https://www.w3.org/Data/demos/chunks/chunks-20191205.pdf
>
> On 6 Dec 2019, at 02:02, Paola Di Maio <paola.dimaio@gmail.com> wrote:
>
> Following on the opportunity to address the AI ALLIANCE, I have requested
> to the EU some data on t member's  profiles to help us scope this doc,
> although I envisage - and hope - that this deliverable will
> be a general set of guidelines for others as well.  I ll share this info
> when it arrives.
>
> In my work I specifically target the AI research community in colleges,
> where future generations of AI engineers are formed by instructors who
> teach mostly statistical methods with nothing in between, however,the
> deliverable could become a useful educational tool for many others,
> especially individuals and organisations coming to AI riding the latest
> wave following a trend, and who have not had exposure to the long history
> of risks and failures nor to intelligent systems development,  I personally
> think that leaving AI in the hands of statistical analysis folks is a risk.
> we need to bring knowledge modelling to the statistical table.
> There are a lot of people and orgs out there talking AI who have never
> heard of KR
>
> I have started a page on the wiki,  with a very indicative outline, feel
> free to modify it and populate it
> https://www.w3.org/community/aikr/wiki/AI_KR_Guidelines
>
> Members please claim a section a paragraph or a sentence by entering text,
> and please do add your initials
> to the text you enter so that we can keep track of who is making the
> contribution, although the wiki should capture your activity when you are
> logged in.
>
> At some point when we have enough tofu (ex beef) we can finalize edits and
> publish
> could this aim to be a mini spec of sorts?
> Should we try to set some deadlines or calls around this?
> Co chairs wish to cultivate this draft welcome to, in addition to anything
> else they may have in mind, if not I ll wrap something up from my own
> materials and shall submit to the group for approval before publishing
>
> Obviously suggestions welcome
>
> Cheers
> 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 Friday, 6 December 2019 11:48:41 UTC