For several years, humans have been developing Artificial Intelligence (AI) and implementing it in increasingly many aspects of our lives, in hopes that it would generate more optimal results.
Yet, AI and Advanced Analytics techniques themselves can be severely biased, even when the modeler isn't. How could this happen?
Dive into this issue with a Dr. Napat Jatusripitak, as he will guide us through real case studies in several areas such as;
AI in Healthcare Diagnosis, Should we trust AI or Physicians?
Predicting Road Accidents in Insurance Business
HR Analytics, Does Predicting People’s Performance with Robots a Final Answer?
Financial Crime Analytics
We’ll find out together where these biases stem from and how to solve them. The highlight discussions are;
Diagnosing the Bias: Data Problem VS. Modeling Problem
Black Box Engine VS. White Box Engine
Balancing Act: Should AI be Regulated and How?
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