“Can You Trust Machine Learning Decisions?”

In this blog, our Managing Consultant Erik Haahr gives you a few advice on how to avoid some of the pitfalls that can occur when dealing with machine learning.

“You need a lot of data when you want to train a machine learning algorithm and since Big Data became a buzz word we have been collecting massive amounts of data that could be used for this purpose.

The last couple of years we have been discussing bias in machine learning. We have heard about Microsoft’s Chatbot Tay and Google’s Image recognition that “recognized” non-Caucasian people as Gorillas and most AI-professionals nowadays know they must consider a way to avoid bias when selecting training data.

But as the world is ever changing and there is one form of bias that will always be present – the fact that historical data doesn’t necessarily represent the future very well! I will call this history bias. You could argue that ML will never work well in an ever-changing world, but that would probably be to go too far.

ML can be used for a few different categories of problems:

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Read the full article and interact with Erik here.