In my latest post I tackle one of those current hot topics – Ethics (and bias) in AI and machine learning.
People tend to simplify. So all types of machine-assisted thinking get dubbed “artificial intelligence,” or AI.
What we’re really talking about with AI or machine learning is an algorithmic approach to analysis: We’re going to look at a bunch of data, and artificial intelligence is going to help us figure some things out. It’s going to tell us things we would have a difficult time finding ourselves.
Here’s where machine learning comes in. It’s all about training a model. When we speak about a model we’re really just talking about code. It’s a coded algorithm—a coded set. A statistical model is the other term for it. So for the data architects of the world, when we think of a data model, we’re thinking of tables, columns, and relationships. In the simplest form, however, we’re talking about a specific set of data.
Check out my thoughts on how we can try to deal with ethics and bias here: A New Ethics of AI
What do you think about this topic?
The Data Warrior