"Explainable AI" in the digital era

The driving force behind the explosion of AI-based solutions is deep learning, one of the core machine learning algorithms. There is, however, a fundamental problem with this rapid AI adoption – the black box nature of AI. This introduces major challenges with regard to applying AI to business decisions where reliability and responsibility are paramount considerations, because with deep learning there is no transparent basis for the actual decision-making. Fujitsu Research has been actively addressing this issue, developing the world's first "explainable AI" so that the reasoning behind any decisions is easy for humans to understand. With a clear explanation and verification of how AI has reached a decision, we can eliminate concerns, promote confidence in the AI process and achieve a level of AI that is genuinely trustworthy. Hence, we are working to ensure that as the use of AI becomes ever more ubiquitous, it is underpinned by a genuinely social and responsible role.

An example of Explainable AI’s value includes genomic medicine such as cancer treatment. In this instance, Fujitsu Research' proprietary AI technology, the Deep Tensor, learns from 350,000 pieces of data in order to estimate the relationship between a disease and a specific genetic mutation. In conjunction with the Knowledge Graph, which is a structured collection of more than 10 billion specialized knowledge from approximately 30 million medical articles, this can provide the medical basis for doctors to conduct much more rapid genetic analysis and tailor drug treatment to individual genetic abnormalities – reducing timescales from two weeks to just a single day.