---------------------------------------------------------------------------

Wednesday, October 14, 2020 at 22:48:04 Eastern Daylight Time 

Subject: Feedback on e xplainability NIST (Email feedback) 

Date: Wednesday, October 14, 2020 a t 8:09:05 AM Eastern Daylight Time 

From: Paola Di Maio 

To: NIST Explainable AI, W3C AIK R CG 

AEachments: nist feedback.txt, Inbox (12,949) - paoladimaio10@gmail.com - Gmail.mp3, NIST 

COMMENTS.xlsx 

Dear NIST 

cc W3C AI KR CG 

Thank you for the opportunity to provide feedback on the draW 

principles for Xplainability 

I paste below and aZach (as text, xls and mp3 narra[on) some 

comments, which I would be grateful if they could be 

taken into account and possibly addressed. 

Looking forward to progress towards a standard for explainability 

Keep us informed, thank you 

Best regards 

Paola Di Maio, PhD 

FEEDBACK FOR NIST ON EXPLAINABILITY 

DraW NIST IR 8312 

from PAOLA DI MAIO, Expert and Co-chair W3C AI KR CG 

13 October 2020 

PREAMBLES 

a) before explainability can be addressed in the context of AI, AI 

should be beZer understood/defined. The reality is that we may not 

yet have AI aWer all 

b) In addi[on to the dis[nc[on between narrow and general AI, the 

dis[nc[on between closed vs open system AI is also necessary. This 

par[cularly applies to the point of Knowledge limits in the draW. 

GENERAL COMMENTS ON THE PRINCIPLES IN THE DRAFT 

1. EXPLANATION type mismatch among the principles 

for example explana[on, is a noun, while meaningful is an adjec[ve, 

would be advisable to have some consistency in the naming conven[ons? 

2. MEANINGFUL explana[on is described as a principle that mandates an 

explana[on for AI, and meaningful is described as a principle that 

the explana[on is meaningful, but it does not describe 

criteria/parameters for meaningfulness. This does not seem up to 

standard. Looks to me that meaningful is a qualifier for explana[on 

(1) 

3. EXPLANATION ACCURACY - same as above, this does not seem a 

principle more like a qualifier for principle 1. Looks to me that 2 

and 3 are qualifiers for 1. however they should be beZer defined 

Page 1 of 2 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

-------------------------------------

4. KNOWLEDGE LIMITS - this is new (ie. unheard of) Is there a 

reference for such a no[on? Where does it come from? who may have 

come up with such an idea? 

Intelligence can be said to overcome knowledge limits, ie, given 

limited knowledge, an intelligent process relies on logical inferences 

deduc[on, abduc[on to achieve a conclusion. Reasoning with limited 

knowledge is a defining characteris[c of intelligent systems. 

Furthermore in open systems, knowledge is not limited, by contrast, it 

is con[nually updated with new knowledge. To consider limited 

knowledge for intelligent systems/AI is a contradic[on in terms. A 

knowledge limit applies to closed database systems not to AI. 

OTHER points 

======= 

- In addi[on to meaningful and accurate, explana[ons should also be 

[mely, accessible, updatable etc 

- (symbolic) Knowledge Representa[on (KR) is a mechanism for 

explainability should be emphasized 

- this work possibly leads to a standard for explainability? would be 

needed, please keep me up to date 

Best regards 

Page 2 of 2