Organisations are moving towards artificial intelligence (AI) to solve business challenges. While machines are here to aid, it is the human intellect that has to get better everyday and drive the machines to be able to work smarter. Here is how we are inferring this shift in the testing world and analyze how we could improve our testing perspectives to deliver better quality products.
Rethinking test design in the age of AI
Test design is a technique that helps testers to model the product under various use cases. Testers ought to be able to understand what are those fallible scenarios are that could put the system at risk and be able to analyse the risk.
While machines think of scenarios based on patterns, they infer with tons of data fed into them. We forget the basics that it is the human brain that has more sensibility towards do’s and dont’s of the system and uncover such possibilities.
We ought to understand and keep checking our process if we are actually adding value to the product with all the tools and machines that we use daily, and rethink about the purpose of our job in the system.
Testing has to be about identifying risks associated with the product, and testers have to get better at the science of uncovering ways to identify such risks, rather than generating hundreds of test cases executed by smart machines driven by so called best practices – contextual thinking is important.
While Alexa can answer a question right, it for sure gives wrong answers to hundreds of the same questions asked differently – context is the key and yes Alexa needs testing too – brainual testing though.
Themes for discussion
Why a thinking tester is always powerful
Why technology should augment thinking testers
What is the impact on test design
Are we adding value or just following a process
Even Alexa needs testing