While we have seen dramatic progress in machine learning in recent years, we still haven’t reached a level where we can attribute ethical responsibility to these systems. That is one of the reasons that despite high expectations we still need to monitor their behavior closely for unwanted effects such as bias. Then again, most algorithms aren’t biased in themselves but will greedily learn from the data and sometimes painfully show you the existing bias in your organization. I will share examples from my own practice to illustrate what to look for and how to deal with it.
Damiaan Zwietering is an IBM specialist who spent his career on achieving real world results innovating with information. He was a developer, consultant, architect and sales engineer in the area of data warehousing, business intelligence and advanced analytics before his current position as a developer advocate for data science, specializing in the practical application of machine learning and artificial intelligence.