QA for AI: Why to Test Already Smart Artificial Intelligence?

▤ Summary

The concept of a machine performing human-like tasks emerged nearly in the 1950s after Alan Turing explored the mathematical possibility of Artificial Intelligence (AI). Compared with traditional software testing, ensuring quality for AI systems requires a diametrically different approach. According to the results, AI developers add or remove something from the program for the algorithm to make it work as expected. AI systems still can go wrong; therefore, the final value of testing is providing security and safety for humanity. Obtaining training data sets that are sufficiently large and comprehensive enough to meet ‘ML testing’ needs is a significant challenge.

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