Re: AI KR Strategist, explainabiilty, state of the art

Carl, good to hear from you and thanks
for picking up where you left .

Btw the attachment you sent never made it into W3C Group reports, maybe at
some point you d like to publish them with some notes explaining how these
addressed the challenges discussed? The documents you send do not seem to
explain how the proposed work fits in the AI KR mission (which problem they
solve).

As previously discussed StratML can be a useful mechanism represent
knowledge, at syntactic level. A markup language by itself it does not
address nor resolve the key challenges faced by AI today that KR (thinking
semantics here) as a whole could tackle. (irrespective of any
implementation language of choice).

In the work you propose, there is strong coupling between AI KR and StratML
as a syntax
(your construct binds the two) This approach may be suitable in a Stratml
CG (is the one by the way)? rather than an AI KR CG  The focus is AI KR,
rather than a modeling language by itself

If the line you are interested to explore is StratML only, it could be
useful if you (or other proponents of this line of work) could  summarise
how it address the broader AI KR challenges.
For example, say, knowledge misrepresentation - or miscategorization - or
wrong recommendations, or making AI more transparent, more reliable, more
accountable etc.

Perhaps  show how these can be addressed  with use cases or other proof of
concept.

So basically, I encourage discussions to be focused on AI KR  and whatever
line of work members propose, please make it clear which problem each
construct intends to resolve in relation to the overall mission.

Thank  you!

Paola Di Maio, PhD


On Thu, Nov 7, 2024 at 6:09 PM carl mattocks <carlmattocks@gmail.com> wrote:

> Greetings All - It has been a while.
>
> Given the interest in AI , I am proposing that we set up a series of
> online meetings to expand on the AI Strategist work that focused on
> leveraging StratML. (see attached).
>
> The topics include:
>
>    1. AI Observability Mechanisms (monitor behavior, data, and
>    performance)
>    2. KR Models used in the explanations (to a given audience, and what
>    concepts are needed for this)
>    3. KR ID needed for Knowledge Content (UID, URI) Logistics management
>    4. Roles of Humans in the Loop (as a creator, and an audience type)
>    5. Agents having Authority awarded by a Human in the Loop
>    6. Catalogs of AI capabilities ( see Data Catalog (DCAT) Vocabulary
>    <https://www.w3.org/TR/vocab-dcat-3/> )
>    7. AIKR Using / Used in DPROD (specification provides unambiguous and
>    sharable semantics) https://ekgf.github.io/dprod/
>
>
> Timeslots for meetings  will be determined by participants.  Please let me
> know if you are interested.
>
> Thanks
>
> Carl Mattocks
>
> CarlMattocks@WellnessIntelligence.Institute
> It was a pleasure to clarify
>
>
> On Tue, Jun 11, 2024 at 5:24 AM Dave Raggett <dsr@w3.org> wrote:
>
>> First my thanks to Paola for this CG. I’m hoping we can attract more
>> people with direct experience. Getting the CG noticed more widely is quite
>> a challenge! Any suggestions?
>>
>> It has been proposed that without knowledge representation. there cannot
>> be AI explainability
>>
>>
>> That sounds somewhat circular as it presumes a shared understanding of
>> what “AI explainability” is.  Humans can explain themselves in ways that
>> are satisfactory to other humans.  We’re now seeing a similar effort to
>> enable LLMs to explain themselves, despite having inscrutable internal
>> representations as is also true for the human brain.
>>
>> I would therefore suggest that for explainability, knowledge
>> representation is more about the models used in the explanations rather
>> than in the internals of an AI system. Given that, we can discuss what
>> kinds of explanations are effective to a given audience, and what concepts
>> are needed for this.
>>
>> Explanations further relate to how to making an effective argument that
>> convinces people to change their minds.  This also relates to the history
>> of work on rhetoric, as well as to advertising and marketing!
>>
>> Best regards,
>>
>> Dave Raggett <dsr@w3.org>
>>
>>
>>
>>