Why does it matter if the Y axis doesn't start at 0? Let's see!
However progressive we like to think we are, our society still has a massive problem with gender bias. Chatbots hold a mirror up to the data we train them on, and the society that created that data. And, of course, it's not just gender bias we can find in these chatbots.
When we use machine learning for really important things like recruitment and health, we need to be immensely cautious and rationally sceptical of the results that we get.
There truly is no such thing as Artificial Intelligence. But, but ChatGPT, you cry! But self-driving cars! But The Algorithm! None of these are even close to intelligent. But how do we know?
It doesn’t matter what technology you teach, when you’re teaching Data Science. I don’t care whether you use Python, R, spreadsheets, or stacking blocks to make graphs and analyse your data. What matters, above all else, is that you teach your students to ask critical questions about the data. How was it collected? What are the definitions you used? How do we know the definitions are valid? What other definitions could we use, and how would that change the data?