Testing (AI) is Testing

Last November I gave a talk, Random Exploration of a Chatbot API, at the BCS Testing, Diversity, AI Conference. It was a nice surprise afterwards to be offered a book from their catalogue and I chose Artificial Intelligence and Software Testing by Rex Black, James Davenport, Joanna Olszewska, Jeremias Rößler, Adam Leon Smith, and Jonathon Wright.

This week, on a couple of train journeys around East Anglia, I read it and made sketchnotes. As someone not deeply into this field, but who has been experimenting with AI as a testing tool at work, I found the landscape view provided by the book interesting, particularly the lists: of challenges in testing AI, of approaches to testing AI, and of quality aspects to consider when evaluating AI.

Despite the hype around the area right now there's much that any competent tester will be familiar with, and skills that translate directly. Where there's likely to be novelty is in the technology, and the technical domain, and the effect of both of them when it comes to identifting and evaluating risk and strategies for its mitigation.

But that's the game, right? Testing is testing, after all, whatever the system under test.

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