There’s a lot of talk out there about using large language models to help testers write tests, such as coming up with scenarios. There’s also talk out there about AI based tools actually doing the testing. Writing tests and executing tests are both a form of performing testing. So let’s talk about what this means in a human and an AI context. Continue reading AI-Powered Testing: Exploring and Exploiting with Reinforcement
Category: Testing AI
AI Testing – Generating and Transforming, Part 3
We come to the third post of this particular series (see the first and second) where I’ll focus on an extended example that brings together much of what I’ve been talking about but also shows the difficulty of “getting it right” when it comes to AI systems and why testing is so crucial. Continue reading AI Testing – Generating and Transforming, Part 3
AI Testing – Generating and Transforming, Part 2
This post continues on from the first one. Here I’m going to break down the question-answering model that we looked at a bit so that we can understand what it’s actually doing. What I show is, while decidedly simplified, exactly what tools like ChatGPT are essentially doing. This will set us up for a larger example. So let’s dig in! Continue reading AI Testing – Generating and Transforming, Part 2
AI Testing – Generating and Transforming, Part 1
The idea of “Generative AI” is very much in the air as I write this post. What’s often lacking is some of the ground-level understanding to see how all of this works. This is particularly important because the whole idea of “generative” concepts is really focused more on the idea of transformations. So let’s dig in! Continue reading AI Testing – Generating and Transforming, Part 1
AI Testing – Measures and Scores, Part 2
AI Testing – Measures and Scores, Part 1
There are various evaluation measures and scores used to assess the performance of AI systems. As someone adopting a testing mindset in this context, those measures and scores are very important. Beyond simply understanding them as a concept, it’s important to see how they play out with working examples. That’s what I’ll attempt in this post. Continue reading AI Testing – Measures and Scores, Part 1
Human and AI Learning, Part 2
In part 1 of this post we talked about a human learning to play a game like Elden Ring to overcome its challenges. We looked at some AI concepts in that particular context. One thing we didn’t do though is talk about assessing any quality risks with testing based on that learning. So let’s do that here. Continue reading Human and AI Learning, Part 2
Human and AI Learning, Part 1
Humans and machines both learn. But the way they do so is very different. Those differences provide interesting insights into quality and thus the idea of testing for risks to quality. I found one way to help conceptualize this is around the context of games. Even if you’re not a gamer, I think this context has a lot to teach. So let’s dig in! Continue reading Human and AI Learning, Part 1
The Spectrum of AI Testing: Case Study
The Spectrum of AI Testing: Testability
It’s definitely time to talk seriously about testing artificial intelligence, particularly in contexts where people might be working in organizations that want to have an AI-enabled product. We need more balanced statements of how to do this rather than the alarmist statements I’m seeing more of. So let’s dig in! Continue reading The Spectrum of AI Testing: Testability