Machine learning has been an incredible breakthrough in the past quarter-century. From diagnostic decisions in hospitals to loan approvals in banking, the conclusions made by machine learning algorithms have key implications on our personal lives, allowing us to process larger quantities of data faster than ever before.
While machine learning and associated artificial intelligence inarguably provide many benefits, unfortunately, they are also prone to error through biases, just like humans. Once we understand how algorithms are designed, we realise that these algorithms that we place so much trust in will sometimes get things wrong.