Re: Towards adopting stratml for the AIKRCG 'strategy': Meeting Report

With regard to the original objectives of the W3 AI-KR CG, and global initiatives for (the ethical use of) AI, and its current relevance for disease control issues related to COVID-19, can we please in defining a strategy for use of StratML in AI-KR, independently of KAIROS?
In too many areas I have surveyed and looked into for research on my Smart City framework model I have encountered government contracts on highly controversial issues, hinting at military applications, which are highly suspect in terms of lack of adequate and transparent oversight and accountability.
Since both the European Union and the UN stress the ethical use of AI I would where possible like to steer clear of any military programs or projects.
There should be a Chinese wall (pardon the pun) separating what individual members of the W3 AI-KR CG aspire to do or to participate in RFPs for defense contracts and what we do as a collective in the form of a community group.
As a Dutch/European Union citizen I feel very strongly about this. That our efforts may have military applications is not the issue, but we should center our efforts on civilian frameworks of reference.
If we can find a civilian framework similar in scope and objectives to KAIROS to use alongside KAIROS I would be more at ease.
Just wanting to make explicit my ethical point of view.

Milton Ponson
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Project Paradigm: Bringing the ICT tools for sustainable development to all stakeholders worldwide through collaborative research on applied mathematics, advanced modeling, software and standards development 

    On Thursday, May 14, 2020, 11:10:28 AM ADT, carl mattocks <carlmattocks@gmail.com> wrote:  
 
  Towards adopting stratml for the AIKRCG 'strategy' ...Given we are AIKR ... we understand that Kairos signifies a proper or opportune time for action  and our usage of StratMl to EXPLAIN makes us interested in Knowledge-directed Artificial Intelligence Reasoning Over Schemas (KAIROS) DARPA-SN-19-19 .
Our discussions have focused on:StratML is our Schema start point  for reasoning, as in, the performance of AIKR   inferences is scoped / weighed by the declared strategy. AIKR reasoning uses KRID identifiers and data (aka metadata) properties, such as KR TYPE. KR Types include Declarative and Imperative  (aka procedural). 

 Carl
Chair AIKRCG
It was a pleasure toclarify


On Thu, May 14, 2020 at 7:37 AM Paola Di Maio <paola.dimaio@gmail.com> wrote:

It is under Owen and Chris's leadership that we are making some progress towardsadopting stratml for the AIKRCG 'strategy'
In sum. what are we doing/planning to do as a group is going to be documented in the plan. and although we are still working  things out, as we do have moments of brilliance and outbursts of productivity we can put them down in this stratml plan on the stratnav app so that they ll be a record of that. should be useful. I apologize again for being very tired but 9 pm is very late for me. especially when I have had a full day incl other calls etc-
a few notes below



the plan being developed here. if anyone is inspired to chip in pls ask editing pass to Chris on this list

 
 
With reference to our Frameworks goal, I will endeavor to render in StratML Part 2 format any frameworks that may be discovered and available on the Web.  Please apprise me of any of which you are aware.

To clarify -  Jorge aske whether we are using any framework of reference for our work. which loosely attempts  to study explainability for machine learning. That particular goal for our CG may need to be refined a little - I dont think a frameworks exists as such (strategies, methods) but there is interesting work being done, which I dont think is a framework yet. rather a compilation of possible techniques. the effectiveness of which may need to be evaluated in the field. So to answer the question, methods to address explainability of ML exist but a) I dont think are frameworks/strategies - this may be our goal? to gather what is in the field and make a framework?b) evaluation criteria for the effectiveness of these methods may not yet be studied, againcould this be our work? I am doing some research in this direction but not yet conclusive I volunteered to take up this task and shall soon update the plan with some links but  I am putting together a presentation- anyone want to contribute?
The caveat is that  statistical pronability and non parametric methods in ML are  unpredictable by definitionhttps://machinelearningmastery.com/uncertainty-in-machine-learning/  
http://mlg.eng.cam.ac.uk/zoubin/talks/mit12csail.pdf

(this is not my field at all, does anyone care to expand?)so I am not sure how to address this unpredictability other than with the question
Can we use known symbolilc KR to  explain ML?

 
In the meantime, this Google site-specific query of the StratML collection turns up about 29 hits on the terms "AI framework".  Here's the top paid ad-placed hit (not yet in the StratML collection but soon to be).


thanks -  how do we query for ML explainability framework (a bit more precise semantically in relation to what we are doing here) 
KRID -  Carl is putting forward a category/concept/type  whereby KR is identified so KRID = some value to describe KR identityCarl started by suggesting the top level distinction for this concept would bedeclarative/procedural i  do not yet have an opinion about this, but would request Carl to start sketching outthe taxonomy for KRID as he envisions it. so that we can have a discussion about itOne considertation is: to what extent is declarative/procedural knowledge relevant to support ML?  or is KRID intended for AI in general (not ML) . Carl perhaps you should create this as a goal for yourself.Also could you clarify the relation of KRID to KAIROS?
Thanks!
PDM