The Productivity Paradox describes a fundamental tension in AI adoption: using AI responsibly requires significant time and effort, but AI is only considered productive when it saves time. This creates pressure to use AI irresponsibly to demonstrate quick wins. The problem intensifies for software testers because testing and development aren't symmetrical—code generated quickly by AI doesn't necessarily mean it can be tested quickly. Testers must balance efficiency demands while highlighting risks that require thorough investigation.
Sort: