DARPA pushes for AI that can explain its decisions

guest · Jul 23, 2018

DARPA pushes for AI that can explain its decisions
It's backing research into 'third wave' AI projects.
July 23, 2018
https://www.engadget.com/2018/07/23/darpa-third-wave-ai-support/

Companies like to flaunt their use of artificial intelligence to the point where it's virtually meaningless, but the truth is that AI as we know it is still quite dumb.

It's launching an Artificial Intelligence Exploration program that will invest in new AI concepts, including "third wave" AI with contextual adaptation and an ability to explain its decisions in ways that make sense. If it identified a cat, for instance, it could explain that it detected fur, paws and whiskers in a familiar cat shape.

The industry isn't beholden to DARPA's schedule, of course. It's entirely possible that companies will develop third wave AI as quickly on their own terms. This program could light a fire under those companies, mind you. And if nothing else, it suggests that AI pioneers are ready to move beyond today's 'basic' machine learning and closer to AI that actually thinks instead of merely churning out data.
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guest · Aug 24, 2020

NIST Publishes Proposed Principles for “Explainable” AI Systems
August 20, 2020
https://www.huntonprivacyblog.com/2...oposed-principles-for-explainable-ai-systems/

On August 18, 2020, the U.S. National Institute of Standards and Technology (“NIST”) published a draft report, Four Principles of Explainable Artificial Intelligence (Draft NISTIR 8312 or the “Draft Report”), which sets forth four proposed principles regarding the “explainability” of decisions made by Artificial Intelligence (“AI”) systems.

Explainability refers to the idea that the reasons behind the output of an AI system should be understandable. According to the NIST press release, AI must be explainable to society to enable understanding, trust and adoption of new AI technologies and the decisions and guidance they produce.
The proposed principles are: [...]
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The Draft Report is a part of a broader NIST effort to develop trustworthy AI systems. In publishing the Draft Report, NIST indicated it hopes to start a conversation about the expectations to which decision-making devices should be held. NIST is accepting comments on the draft report until October 15, 2020.
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NIST: NIST Asks A.I. to Explain Itself

Technical agency proposes four fundamental principles for judging how well AI decisions can be explained
According to the authors, the four principles for explainable AI are:

AI systems should deliver accompanying evidence or reasons for all their outputs.

Systems should provide explanations that are meaningful or understandable to individual users.

The explanation correctly reflects the system’s process for generating the output.

The system only operates under conditions for which it was designed or when the system reaches a sufficient confidence in its output. (The idea is that if a system has insufficient confidence in its decision, it should not supply a decision to the user.)

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