COG ai definition?

Ron and all

- since we are educating ourselves :-) -
I wonder if someone may know where the definition COG AI comes from

I first started studying AI around the nineties, and got an MSC in 2000,
but we never used this term
we used KBS (knowledge based systems)

here it says cognitive computing came about in 2014
ttps://cognitivecomputingconsortium.com/definition-of-cognitive-computing/

thank you!


On Mon, Sep 14, 2020 at 11:04 AM Paola Di Maio <paola.dimaio@gmail.com>
wrote:

> Thank you Ronald for setting this up
> I should be able to make it
>
> For me, AI has always been cognitive AI - probably because I started
> learning AI
> from knowledge based systems (long ago), I never felt the necessity to
> call AI cognitive
> (i understand that given the spike of ML this disambiguation may be useful
> now)
> at the same time, I have been practicing all along for thirty years
> (unlabelled, and unaware perhaps
> that a discipline was forming )
>
> My suggestion is to try make the call a bit participatory, make sure that
> whoever is on the call
> can contribute to the call agenda and bring in their
> perspective/experience to whatever is the agenda goal
>
> Its good to learn but  to "éducate'' sounds as if people dont know about
> cogAI already, like a bit patronizing perhaps?
> what about co-learn :-)
>
> I am a constructivist by nature
>
> P
>
>
>
> On Mon, Sep 14, 2020 at 2:38 AM Ronald Reck <rreck@rrecktek.com> wrote:
>
>> Hello Cognitive AI Community group,
>>
>> Our first conference call is scheduled for
>> September 21, 2020 at 1 PM London time.
>> Contact information will be sent out later this week.
>>
>> The agenda is as follows:
>>
>> 1. Educate - gentle introduction to the topic of cog-ai
>>
>> 2. Outreach - Discuss how to extend reach out beyond
>> our current group. We seek to bridge the technical
>> clique mindsets as the topic is interdisciplinary.
>> It involves traditional AI (deep learning),
>> natural language processing, logic, pragmatics,
>> cognitive science, and semantic web.
>>
>> 3. Use cases - Understand and document business cases
>> especially around machine & human collaboration. This hopes
>> to drive funding.
>>
>> 4. AI ethics / explainability
>>
>> As we are still in the early stages, there is
>> much exciting work to be done, we need to consider
>> how to involve different orientations to incubate
>> a paradigm shift so that future intellectual effort
>> is exerted in the most effectively toward AI's ability
>> to enhance society.
>>
>> Please feel free to comment or make suggestions!
>>
>> -Ronald P. Reck
>>
>>
>>