Dear NIST Thank you for the opportunity to provide feedback onf the draft principles for X I paste below and attach as text some comments, which I would be grateful if they could be taken into account and possibly addressed. Looking forward to the standard for explainability Best regards Paola Di Maio, PhD --------------------------------------------------------------------------- FEEDBACK FOR NIST ON EXPLAINABILITY Draft 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 better understood/defined. The reality is that we may not yet have AI after all b) In addition to the distinction between narrow and general AI, the distinction between closed vs open system AI is also necessary. This particularly applies to the point of Knowledge limits in the draft. GENERAL COMMENTS ON THE PRINCIPLES IN THE DRAFT 1. EXPLANATION type mismatch among the principles for example explanation, is a noun, while meaningful is an adjective, would be advisable to have some consistency in the naming conventions? 2. MEANINGFUL explanation is described as a principle that mandates an explanation for AI, and meaningful is described as a principle that the explanation 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  explanation (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 better defined 4. KNOWLEDGE LIMITS - this is new (ie. unheard of) Is there a reference for such a notion? 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 deduction, abduction to achieve a conclusion. Reasoning with limited knowledge is a defining characteristic of intelligent systems. Furthermore in open systems, knowledge is not limited, by contrast, it is continually updated with new knowledge.  To consider limited knowledge for intelligent systems/AI is a contradiction in terms.  A knowledge limit applies to closed database systems not to AI. OTHER points ======= - In addition to meaningful and accurate, explanations should also be timely, accessible, updatable etc - (symbolic) Knowledge Representation (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 -----------------------