- AI & Machine Learning Black Boxes: The Need for Transparency and Accountability - Apr 25, 2017.
When something goes wrong, as it inevitably does, it can be a daunting task discovering the behavior that caused an event that is locked away inside a black box where discoverability is virtually impossible.
- Big Data Desperately Needs Transparency - Mar 6, 2017.
If Big Data is to realize its potential, people need to understand what it is capable of, what information is out there and where every piece of data comes from. Without such transparency and understanding, it will be difficult to persuade people to rely on the findings.
- Machine Learning Meets Humans – Insights from HUML 2016 - Jan 6, 2017.
Report from an important IEEE workshop on Human Use of Machine Learning, covering trust, responsibility, the value of explanation, safety of machine learning, discrimination in human vs. machine decision making, and more.
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- Interview: Slava Akmaev, Berg on Healthcare Transparency & Effectiveness using Big Data - Mar 9, 2015.
We discuss Big Data Analytics at Berg, making Healthcare effective through Big Data, impact of falling cost of DNA sequencing, Berg AI-Analytics Suite and more.