Listen to this article: This past week I spent some time thinking about AI from the perspective of an Enterprise Architect. Is the Enterprise Architect also the Agentic AI Architect (or just AI Architect)? Perhaps in some organizations, but I would assert that AI Architect is more analogous to an Application Read more
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
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
This is the second installment of a two-part series about the impact of AI on information management. The first covered Data Quality and Metadata Collection. Data Modeling Nobody at your company is more passionate about understanding the data than your Data Modelers. Unfortunately, too often their work products, while admired Read more