- From: Paola Di Maio <paola.dimaio@gmail.com>
- Date: Wed, 14 Oct 2020 20:33:35 +0800
- To: www-archive@w3.org
On Wed, Oct 14, 2020 at 8:09 PM Paola Di Maio <paola.dimaio@gmail.com> wrote: > > Dear NIST > cc W3C AI KR CG > > Thank you for the opportunity to provide feedback on the draft > principles for Xplainability > > I paste below and attach (as text, xls and mp3 narration) 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 > 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 > > -------------------------------------
Received on Wednesday, 14 October 2020 12:34:28 UTC