AI Needs Testers

Tariq King, Towards Better Software: How Testers Can Revolutionize AI and Machine Learning

Tariq issued a powerful call to arms in his talk at CAST 2021. Yes, AI/ML is new technology and, yes, it is solving new problems, and so, yes, testers may find themselves out of their comfort zones in some respect.

But there are parallels between machine learning and testing that should give testers confidence that they have something valuable to contribute right now: mapping inputs to outcomes for black boxes, partitioning a possibility space, and data wrangling.

Learning is part and parcel of testing, so why think we can’t learn what’s needed for working with AI and ML systems? And don’t forget that testers come preloaded with universally-valuable skills such as exploring, questioning, and assessing.

Without some kind of challenge, Tariq says, AI is going to continue powering the runaway train of bad software. Testers can and should be standing squarely in front of it.

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