I came across this article on social media: https://www.pimlicojournal.co.uk/p/mps-are-almost-certainly-using-chatgpt This got my attention, because I'm sick of people ragging on college students using AI. EVERYONE is using AI. That doesn't mean it is always OK or evil, but let's stop ragging on the kids. Anyway, the author used data to make their claims via z scores: https://www.pimlicojournal.co.uk/p/mps-are-almost-certainly-using-chatgpt Ways to use in class: 1. I like to talk to students about data as evidence. In science, it can be evidence to reject or not reject a hypothesis. In real life, it can track trends, both innocuous and suspicious. 2. This is another way of talking about z scores, a crucial but less exciting aspect of basics statistics. As best as I can tell, this was the z score formula used:  frequency z score = (number of times phrase was used in a year - mean times the phrase was used in all years)/standard deviation of number of times the phrase was...

When I teach regression, I touch on AI/Machine Learning. Because it is fancy regression and ties classroom lessons to real life. During discussions about AI/ML, we often talk about "training" computers to look for something by feeding computers data. Which is slightly abstract. And a bit boring, if you are just talking about a ton of spreadsheets. As an alternative to boring, I propose you ask your students to help train Google's computers to recognize doodles . Visit this website, and a prompt flashes on your screen: You draw the prompt (I used my touchscreen), and Google tries to guess what you drew. Here is my half-done wine glass. Google guessed what it was. The website includes additional information on the data that has already been collected. For every one of the doodles above, you can click through and look at all the ones created in response to each prompt. SO MUCH INFORMATION. If you would like, you can also show your students this explainer video.

Sometimes, I post whole class lessons. Sometimes, I post short little example nuggets. Today I share the latter.  This one is a brief, easy-to-understand example of why AI only learns what we teach it and how even a smarty pants computer can get a little confused about correlations and what they mean. A great way to introduce ML, AI, problems with both, and even discuss correlation and predictions and regression. https://twitter.com/hoalycu/status/1507770891786096643...in my head, I imagine that AI was just judging comic-sans font. The text in this tweet was from a MIT Technology Review article by WIll Douglas Heaven: https://www.technologyreview.com/2021/07/30/1030329/machine-learning-ai-failed-covid-hospital-diagnosis-pandemic/ If you want to go deeper with this example, I strongly recommend reading Dr. Cat Hicks's thread about this post:  https://twitter.com/grimalkina/status/1508095358693302275 .