Miscellaneous

[Airicist]

Article "Reimagining What’s Possible With Machine Learning"

by Deepak Dube
November 9, 2020

[Airicist]

Article "Banks look at ‘explainable’ AI systems to boost consumer trust"
Finance industry turns to emerging technology aimed at making decisions more transparent as it tries to root out biased algorithms

by Henry Kenyon
December 8, 2020

[Airicist]

Article "Truera raises $12 million for its AI explainability platform"

by Kyle Wiggers
December 14, 2020

[Airicist]

Article "Explaining Explainable AI"

by Brandon Purcell
December 18, 2020

[Airicist]

Article "Explainable AI in practice"
How committing to transparency made us deliver better AI products

by Ayla Kangur
December 25, 2020

[Airicist]

Article "How explainable artificial intelligence can help humans innovate"

by Forest Agostinelli
January 13, 2021

[Airicist]

Article "Can Artificial Intelligence Explain Itself?"
As an end user, you may never have to work with artificial intelligence from a developer’s perspective, but knowing how it works is key to ensuring its successful use. Fortunately, the technology can explain itself.

by David Greenfield
January 21, 2021

[Airicist]

Article "Why Does Explainable AI Matter Anyway?"

by Dr. Tehseen Zia
Reviewed by Justin Stoltzfus
February 2, 2021

[Airicist]

Article "Why ‘Explainability’ Is The Next Step For AI In Manufacturing"

by Max Versace
February 22, 2021

[Airicist2]

What is explainable AI?

May 4, 2022

What is Explainable AI: https://ibm.biz/Explainable_AI

Explainable artificial intelligence (XAI) is a set of processes and methods that allows human users to comprehend and trust the results and output created by machine learning algorithms. Explainable AI is used to describe an AI model, its expected impact and potential biases. Sound complicated? Master Inventor Martin Keen gives you a simple (and fun) explanation on how explainable AI works.