Practical Data is an occasional series that examines data concepts that we encounter in our everyday lives, sometimes without even knowing it. It is my pleasure to introduce you to the Sigmoid Function. I can’t help but think of it as the “Sigmund Function” after the main character in the Read more
I have long held that the main reason that corporate adoption of Artificial Intelligence has been slow is because leadership would necessarily have to accept the fact that sometimes the AI would be wrong. The demand for AI has always been strong, but the demand for “deterministic AI” has been Read more
Today I start teaching introductory computer science at Rhodes College. It’s the first course in the computer science major sequence, but it is also a recommended elective for non-majors. I’ve been told to expect non-majors to make up as much as three-quarters of the class. It goes without saying that Read more
I enjoy puzzles. Especially the constraint-satisfaction kind like they have on the qualitative section of the GRE. I have one of those page-a-day puzzle calendars that I work each morning while brushing my teeth. Here’s one from a couple weeks ago: Insert the letters A to J, one per square, Read more
The ink is barely dry on Generative AI and AI Agents, and now we have a new next big thing: Agentic AI Sounds impressive. By the time this article comes out, there’s a good chance that Agentic AI will be in the rear-view mirror and we’ll all be chasing after Read more
“Good afternoon. This is Domino’s Pizza. What can I get started for you?” “Hi. Yes. I’d like a thousand assorted large pizzas delivered tonight.” “Very well. Where would you like them delivered to? “The Pentagon. Add it to the tab.” “Will do. Thank you very much.” Click. After hanging up Read more
An AI made a decision. You want to know why it decided the way it did. Seems reasonable. Well, reasonable depending upon the AI technique being used. Some are more transparent than others. First, we need to know what we’re asking for: interpretability or explainability. Both seek to understand the Read more
Last week in the Reservoir of Ideas, I discussed bias in generative models and the impact of the data that’s fed to them. As luck would have it, a couple days later, a colleague reposted a TikTok video of a woman reading the ChatGPT analysis of HR-1, a.k.a. “The Big Beautiful Read more
One of the most significant areas of Data Ethics concern is bias in generative AI models. Concerns about algorithmic bias are not new. Associative model (i.e. neural network) bias is not new. Even the ceding of consequential decisions to these models is not new. Just a few examples: AI is Read more
In the holiday classic, It’s the Great Pumpkin, Charlie Brown, and earlier in the October 25, 1961 Peanuts comic strip, Linus Van Pelt famously says: There are three things I’ve learned never to discuss with people: religion, politics, and the Great Pumpkin. Unfortunately, it’s hard to talk about Data Ethics Read more