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Wednesday, October 14, 2020 at 22:48:23 Eastern Daylight Time 

Subject: Resending: Feedback on e xplainability NIST (Email feedback) 

Date: Wednesday, October 14, 2020 a t 10:04:02 PM Eastern Daylight Time 

From: Paola Di Maio 

To: NIST Explainable AI, W3C AIK R CG, www-archive@w3.org 

AFachments: nist feedback.txt, NIST COMMENTS.xlsx 

resending the feedback notes with linked MP3 rather than bulky audiofile aVachment which may not come 

through the email 

hVps://drive.google.com/file/d/1INcc8c7LKIlcI3j9WfyQGBSOup-WrOIJ/view?usp=sharing 

Dear NIST 

cc W3C AI KR CG 

Thank you for the opportunity to provide feedback on the drab 

principles for Xplainability 

I paste below and aVach (as text, xls and mp3 narradon in the link linked) 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 

Drab 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 beVer understood/defined. The reality is that we may not 

yet have AI aber all 

b) In addidon to the disdncdon between narrow and general AI, the 

disdncdon between closed vs open system AI is also necessary. This 

pardcularly applies to the point of Knowledge limits in the drab. 

GENERAL COMMENTS ON THE PRINCIPLES IN THE DRAFT 

1. EXPLANATION type mismatch among the principles 

for example explanadon, is a noun, while meaningful is an adjecdve, 

would be advisable to have some consistency in the naming convendons? 

2. MEANINGFUL explanadon is described as a principle that mandates an 

explanadon for AI, and meaningful is described as a principle that 

the explanadon 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 explanadon 

(1) 

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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 beVer defined 

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

reference for such a nodon? 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 

deducdon, abducdon to achieve a conclusion. Reasoning with limited 

knowledge is a defining characterisdc of intelligent systems. 

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

is condnually updated with new knowledge. To consider limited 

knowledge for intelligent systems/AI is a contradicdon in terms. A 

knowledge limit applies to closed database systems not to AI. 

OTHER points 

======= 

- In addidon to meaningful and accurate, explanadons should also be 

dmely, accessible, updatable etc 

- (symbolic) Knowledge Representadon (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 

Virus-free. www.avast.com 

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