Overcoming exclusion bias
Exclusions bias is when you choose to delete information that isn't considered useful. One of the strengths of AI is that it can find patterns or relationships for things that you didn't realize existed. This can happen more often if individuals or a team don't have a good set of domain knowledge around a subject and therefore are dismissive of items that they don't realize would be valuable.
An added danger arises if data scientists believe that they know an area well enough to be able to create models around it. This can go hand in hand with the Dunning–Kruger effect, which is a potential cognitive bias where people with low skill in a particular area overestimate their ability. You don't know what you don't know, meaning that when you are new to an area, there are many aspects of it you can't even realize are gaps in your knowledge. Conversely, you can have people with high knowledge in an area perceiving their...
