Re: Growing list of priority issues for AI and thus also ethical use and explainable AI

Yes, I will upload information as soon as possible.
In the meantime I want to reiterate a point made:
https://scitechdaily.com/300-covid-19-machine-learning-models-have-been-developed-none-is-suitable-for-detecting-or-diagnosing/

Milton Ponson
GSM: +297 747 8280
PO Box 1154, Oranjestad
Aruba, Dutch Caribbean
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, March 25, 2021, 11:55:44 PM ADT, Paola Di Maio <paola.dimaio@gmail.com> wrote:  
 
 Thank you Milton
After consulting with the list, ie does anyone ahve any comments/suggestions on the prioritiesI d say each priority should be followed by one or more proposed actions, perhaps?(immediately feasible actions that are within our currently capabilities, and desirable actions that require further/future resources not yet available). This may help list members steertheir energies 
Perhaps you can simply upload these priorities as an entry onto the CG web pages and wiki
After the list is available as a URL then converting to stratml should be straightforward with Owens help?
On Thu, Mar 25, 2021 at 9:54 PM ProjectParadigm-ICT-Program <metadataportals@yahoo.com> wrote:

For AI the list of priority issues keeps growing.
In our WG we have identified several issues of importance to AI as pertains in particular to KR.
I am still working on the graph and other representation paradigms.
But other issues have become important:(1) bias, huge datasets used for machine learning have been indicated to be in many cases and fields to have several forms of bias, i.e. in facial recognition, NLP using machine learning, but more recently also in the validity, reliability, information exchange and compilation of all manner of data related to COVID-19, from points of care data registration, tracing, tracking, monitoring and monitoring of data related to (field trials of) vaccines
(2A) data protection and privacy, which is evident in the rush to create industry wide global vaccination certification and or passport schemes which use mobile apps, cloud based services, and point of care based services to record, store and exchange information and data between actors in such networks. In particular in air and sea travel the intention is to use machine learning to detect patterns of disease spread and improve health and safety protocols
(2B) social media, news and entertainment delivery are fully AI driven, and now under increasing scrutiny form regulators and governments around the world fro a host of data privacy, security and intellectual property issues

(3) weaponizing of AI for economic, intellectual property, cyber and military warfare.The following link summarizes some of the main aspects:https://www.brookings.edu/blog/techtank/2021/03/24/it-is-time-to-negotiate-global-treaties-on-artificial-intelligence/

(4) the creation of autonomous systems, AI driven is expanding to so many different fields that the themes of explainable AI, accountability and control which are to a great extent knowledge driven force us to address technical issues and KR issues
(5) the marriage of edge computing, quantum computing with AI brings new challenges and poses several new points of concern
Can we create a list of priorities and create a StratML blueprint for potential tackling of these?

Milton Ponson
GSM: +297 747 8280
PO Box 1154, Oranjestad
Aruba, Dutch Caribbean
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