The following is what ChatGPT says:
"Yes, QA practices still hold significance even in a world where AI is prevalent. While AI can assist in various aspects of software development and testing, it does not eliminate the need for QA practices. Here's why:
AI is not infallible: AI systems are trained based on historical data and patterns, which means they may not capture all possible scenarios or uncover all types of issues. QA practices help identify edge cases, validate system behavior, and ensure comprehensive testing.
Ensuring quality standards: QA practices involve defining and implementing quality standards, test plans, and test cases. These practices help ensure that software meets the desired quality level, adheres to requirements, and functions as intended.
Human perspective and creativity: QA professionals bring human judgment, intuition, and creativity to the testing process. They can think critically, identify potential issues that AI might overlook, and provide insights based on their experience and domain knowledge.
Validation and verification: QA practices involve validating the software against business requirements and verifying its functionality, usability, performance, security, and other aspects. These activities help ensure that the software meets the desired objectives and performs optimally.
Continuous improvement: QA practices emphasize continuous improvement by identifying areas for enhancement, addressing customer feedback, and refining processes. This ongoing evaluation and refinement contribute to the overall quality and reliability of software products.
In summary, while AI can enhance and automate certain aspects of testing, QA practices remain essential to ensure software quality, validate requirements, address diverse scenarios, and provide a human perspective to the testing process."
@wm23 Those are pretentious dialogues by chatGPT!
what chatGPT says on the opposite side:
"Alright, so here's the thing: With AI running the show, QA's become kind of a backseat driver. Why? Let's break it down.
First up, AI's not just smart, it's super smart. It's designed to learn from past scenarios and can pretty much catch anything thrown its way. We don't need QA to baby-sit.
Then there's the quality angle. Our AI's so good it guarantees top-notch software all by itself. It knows what it's doing, and double-checking everything with QA just feels like overkill.
And about the human touch, well, AI's gotten so advanced it's almost human-like. It has the ability to predict and spot stuff even before we do. So, we don't really need a human to do what AI can do better.
Finally, AI's not just about doing the job, it's about improving all the time. It learns from user feedback and tweaks itself. So, we don't really need QA to keep a check.
So yeah, while QA was cool once, with the advanced AI we have now, we can handle testing just fine without it. QA, in a way, has become more of an old-school way of doing things. AI's our main star now, making sure our software is top-tier and reliable."
They are bad robots if you read them in the opposite scenario.
@wm23 Just magic tricks, lolol, but the thing I want to emphasize is AI intends to do good or bad, depending on the handler (2 jobs at the same time) but QA practices only aim for greatness and go straight forward since it was the only job description on their resumes. xD
@wm23@cryptodhemz I def agree! Maybe one day AI will be good enough to fully understand what you want it to do and generate the perfect code to achieve those goals, but until then, QA is still super important
Testing this higher volume of AI gen code doesn't need to take forever, though. Would encourage you to take a look at Momentic and see how we help w/ that 😉 Always appreciate any thoughts / feedback
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