The Intelligence in AI
Talk around the use of various tools and how it will replace human effort has been around for as long as software testing has existed as a concept. These days, artificial intelligence (AI), machine learning (ML) and low-code/no-code are the talk of the town. Surely the advent of AI will diminish the need for humans in the software testing equation?
If you think the future of testing lies in AI, you’re wrong.
As Larry Goddard pointed out in a recent conversation I had with him and Joe Colantonio, people tend to forget that ML and AI still need to learn the different processes and needs in their specific application. You cannot just apply AI to a specific situation and expect it to work.
Increasingly, I see a move to use AI and other tools to remove the human aspect out of software testers. There seems to be a perception that since humans are fallible (not to mention expensive), we should replace them with automated processes and tools- and what better technology than AI?
If this is the way you think, I’m here to tell you that you’re wrong.
The I of AI
Of course, there is a place for AI. AI is great! But we shouldn’t forget the intelligence part of Artificial Intelligence: The I of AI.
This intelligence lies with the human planning and doing the testing.
Intelligence is what sets excellent testing apart from a mediocre or failed attempt: the ability of people to think how to apply their craft and testing expertise to a specific situation.
We don’t live in a cookie-cutter world, where every scenario is an exact replication of the next, and our approach to testing should not be either. The Intelligence of Testing lies in the ability to think differently.
As test professionals, our intelligence is what sets us apart. We’ll always be the I in AI, the Intelligence of Testing.