Wednesday, October 14, 2020 at 22:32:03 Eastern Daylight Time 

Subject: Re: Four Principles of Explainable Ar6ficial Intelligence 

Date: Wednesday, October 14, 2020 at 9:25:31 AM Eastern Daylight Time 

From: Shawn Riley 

To: NIST Explainable AI 

Dear NIST, 

You're welcome for the feedback on explainable AI. We're using NIST NVD data (CVE, CWE, CPE, etc) in 

the Explainable AI work going on out at OASIS's Threat Actor Context (TAC) TC where the community is 

building descrip6on logics ontologies and iden6fying explainable deduc6ve logical inference that can 

be made using cyber threat intelligence (STIX) and contextual informa6on sources like NVD. Inference 

iden6fied as part of these standardized descrip6on logics ontologies for the OASIS TAC TC are planned 

to be captured in STIX Notes objects so the step by step reasoning over the evidence to reach the 

conclusion is shared and captured for the humans to agree or disagree with. 

This next year is going to be exci6ng for explainable AI in cybersecurity.

Best regards, 

Shawn 

Shawn Riley 

Chief Visionary Officer & 

Technical Advisor to the CEO 

DarkLight, Inc. 

Mobile:

Email: 

www.darklight.ai 

From: NIST Explainable AI <explainable-AI@nist.gov> 

Sent: Tuesday, October 13, 2020 2:47 PM 

To: Shawn Riley <shawn.p.riley@darklight.ai> 

Cc: NIST Explainable AI <explainable-AI@nist.gov> 

Subject: Re: Four Principles of Explainable Ar6ficial Intelligence 

Dear Shawn Riley, 

Thank you for submitting your comments our draft of Four Principles of 

Explainable Artificial Intelligence (Draft NISTIR 8312). 

Your feedback is important for us to shape this work, and we appreciate your 

contribution. 

Best Wishes, 

NIST Explainable AI Team 

From: Shawn Riley 

< Date: Wednesday, August 19, 2020 at 8:16 AM 

To: NIST Explainable AI <explainable-AI@nist.gov>

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Subject: Re: Four Principles of Explainable Ar6ficial Intelligence 

BTW if the authors are not familiar with modern symbolic AI that uses Descrip6on Logics ontologies 

and that produces fully explainable results, there is a great explainer ar6cle on Medium. 

hfps://medium.com/@shawn.p.riley/modern-symbolic-ai-in-2020-dfcc27abbc5c

Shawn Riley 

Chief Visionary Officer & 

Technical Advisor to the CEO 

DarkLight, Inc. 

Mobile: 

Email: 

www.darklight.ai 

From: Shawn Riley 

Sent: Wednesday, August 19, 2020 6:00 AM 

To: explainable-AI@nist.gov <explainable-AI@nist.gov> 

Subject: Four Principles of Explainable Ar6ficial Intelligence 

NIST Explainable AII was reading the new Four Principles of Explainable Ar6ficial Intelligence NISTIR8312 and it appears to 

be aimed exclusively at non-symbolic AI (machine learning / deep learning) and did not seem to 

guidance on the fully explainable symbolic AI (machine undertanding) used today. If the inten6on is for 

this work only to apply to machine learning / deep learning systems then perhaps it would be 

beneficial to call it Explainable Machine Learning? I'm just concerned there might be some confusion 

since we have 2 very different and very ac6ve fields of ar6ficial intelligence in the community. 

Symbolic AI has advanced from the ProLog days of Proposi6onal Logic, Implica6ons, and Truth Tables 

to using more expressive, standardized Descrip6on Logics Ontologies and Descrip6on Logics Inference 

Engines that are used to create fully transparent and explainable ar6ficial intelligence solu6ons that 

give the AI and human users a shared understanding of the integrated data, informa6on, and 

knowledge. Shouldn't there be one NIST standard for explainable AI or shouldn't the explainable AI 

standard describe both types of ar6ficial intelligence and how both non-symbolic AI and symbolic AI 

can be explainable AI and how their different? 

The point is that symbolic AI today is fully explainable ar6ficial intelligence and the en6re NISTIR8312 

only talks about non-symbolic AI as explainable ar6ficial intelligence. Either change the name of the 

work to be explicit to non-symbolic AI or be inclusive of both fields. 

We already have people out there working on Co-symbolic AI / NeuroSymbolic AI where people are 

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combining the Description Logics Ontologies and Reasoners of symbolic AI for deductive logical

inference and machine understanding with the algorithms of non-symbolic AI with their inductive

statistical inference and machine learning ability. Shouldn't the Artificial Intelligence standards and

guidance cover both non-symbolic AI and symbolic AI given that both have transformed over the last 

20 years? 

Shawn 

Shawn Riley 

Chief Visionary Officer & 

Technical Advisor to the CEO 

DarkLight, Inc. 

Mobile: 

Email: 

www.darklight.ai 

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