Entries by Andreas Holzinger

Microsoft boosts Explainable AI

Microsoft invests into explainable AI and acquired on June, 20, 2018 Bonsai, a California start-up, which was founded by Mark HAMMOND and Keen BROWNE in 2014. Watch an excellent introduction “Programming your way to explainable AI” by Mark HAMMOND here: and read read the original story about the acquisition here: https://blogs.microsoft.com/blog/2018/06/20/microsoft-to-acquire-bonsai-in-move-to-build-brains-for-autonomous-systems “No one really knows […]

The Problem with explainable-AI

A very nice and interesting article by Rudina SESERI in the recent TechCrunch blog (read the orginal blog entry below): at first Rudina points out that the main problem is in data; and yes, indeed, data should always be the first consideration. We consider it a big problem that successful ML approaches (e.g. the mentioned […]

MIT emphasizes the importance of HCI for explainable AI

In a joint project “The car can explain” with the TOYOTA Research Institute  the MIT Computer Science & Artificial Intelligence Lab  are working on explainable AI and emphasize the increasing importance of the field of HCI (Human-Computer Interaction) in this regard. Particularly, the group led by Lalana KAGAL is working on monitors for reasoning and […]

Google Brain says Explainability is the “new deep learning”

There is a very interesting interview in the Talking Machines*) series from May, 31, 2018. Katherine GORMAN interviews Maithra RAGHU **) from the Google Brain Team, where she mentioned that “explainability is the new deep learning”, and it is particularly important for health informatics, where it is important to re-trace, re-enact and to understand and […]

Google Brain says we urgently need a Research Framework around the field of interpretability

In a recent interview Been KIM from the Google Brain team emphasizes the significance of research in explainable AI. Particularly, she emphasized the importance of Human-Computer Interaction (HCI) for Artificial Intelligence generally and Machine Learning specifically (see the differences between AI and ML here), and the urgent need of an research framework around the field […]

“Machine Learning for Health Informatics” Lecture Notes in Artificial Intelligence 9605 > 40,626 downloads 2017

Since its online publication on December 10, 2016 the Volume edited by Andreas Holzinger “Machine Learning for Health Informatics” Springer Lecture Notes in Artificial Intelligence LNAI Volume 9605, has been downloaded 54,960 times as of today (May, 11, 2018, 20:00 CEST) and 44,988 with status as of April 2018 according to the official Springer Bookmetrix […]

AI will change Radiology – NOT replace Radiologists

After the rather shocking statement of Geoffrey HINTON during the Machine Learning and Market for Intelligence Conference in Toronto, where he recommended that hospitals should stop training radiologists, because deep learning will replace them (watch video below), on March, 27, 2018 Thomas H. DAVENPORT and Keith J. DREYER published a really nice article on “AI […]

Human-in-the-loop AI

Human-in-the-Loop-AI This is really very interesting. In the recent April, 5, 2018, TWiML & AI (This Week in Machine Learning and Artificial Intelligence) podcast, Robert MUNRO (a graduate from Stanford University, who is an recognized expert in combining human and machine intelligence) reports on the newly branded Figure Eight [1] company, formerly known as CrowdFlower. […]

A good proof of the importance of the HCI-KDD approach, worth: 2,1 Billion USD !

Our strategic aim is to find solutions for data intensive problems by the combination of two areas, which bring ideal pre-conditions towards understanding intelligence and to bring business value in AI: Human-Computer Interaction (HCI) and Knowledge Discovery (KDD). HCI deals with questions of human intelligence, whereas KDD deals with questions of artificial intelligence, in particular […]