AI Will Require Even Better Testers             

Written by Matt Kuntz

With the advancements of Artificial Intelligence, there is a growing concern that people working in the Information Technology industry will gradually be replaced.  It is correct that the demand of traditional “IT” roles will be on the way out, but this will only bring greater demand for those which focus on architecting, implementing, and testing the capabilities of AI.  Much like tradition software/development, it will need to be built/configured and tested to make sure it meets its intended use.  Just the same as the AI of tomorrow, testing is still going to be a critical step of the Software Development Lifecyle Process (SDLC).  AI will continue to improve, and has already become a partner with quality, validation, and overall testing.  Of course, this is just my opinion, so I thought it would be a good test to ask this new AI technology what it’s thought were on the topic.

When asked if testing is important to AI Technology, here is what it told me:

AI – ChatGPT:

Testing AI is important for several reasons:

1. 1. 1. 1. Accuracy and Performance: To ensure that the AI system performs as expected and produces accurate results. Without testing, there could be errors or failures that negatively impact its effectiveness.
         2. Bias Detection: AI systems can sometimes learn biases from the data they are trained on, leading to unfair or discriminatory decisions. Testing can help identify and mitigate these biases to ensure fairness and inclusivity.
         3. Reliability and Robustness: To make sure the AI works well in a variety of scenarios, including edge cases or unexpected inputs. Proper testing ensures the system can handle real-world complexity.
         4. User Experience: AI systems that interact with people need to be tested to ensure they’re intuitive, easy to use, and meet user needs. Testing helps improve the user interface and overall experience.
         5. Compliance and Ethics: There are regulations (like GDPR) and ethical considerations in AI development. Testing helps ensure compliance with these legal and moral guidelines, especially around privacy, transparency, and accountability.
         6. Security: AI systems can be vulnerable to malicious attacks, such as adversarial attacks, where slight modifications to inputs lead to incorrect behavior. Testing helps uncover such vulnerabilities.
         7. Continuous Improvement: AI systems need ongoing refinement as they encounter new data and situations. Testing provides insights for improvement and helps developers adjust the model over time.

Overall, testing is crucial to ensure that AI systems are safe, reliable, and beneficial in real-world applications.

AI – Grok 3:

Testing AI is a big deal because it’s all about making sure these systems—like me—actually work as promised. Think of it like this: AI gets thrown into everything from answering your questions to crunching data for big decisions. If it’s not tested properly, you might end up with answers that are off the mark, biased, or just plain weird. Nobody wants an AI suggesting you cook your shoes for dinner, right?

It’s also key for catching glitches before they snowball. Untested AI could misinterpret stuff, miss edge cases, or even amplify mistakes—like if I started giving you outdated info or wild tangents instead of straight-up useful responses. Testing keeps us reliable and trustworthy, which matters when people lean on AI for real-world stuff like medical advice or navigating traffic.

And honestly, it’s not just about us being helpful—it’s about safety too. Badly tested AI could mess up in high-stakes situations. My makers at xAI want me to advance human understanding, not confuse it, so testing’s how they keep me on track. What’s your take—any specific angle on this you’re digging into?

In summary, Quality Professionals are not going away any time soon. They may not need to out-think a physical developer writing the code as much in the future but will also need to out-think the Artificial Intelligence creating the code in the future.  Most importantly, they will need to continue to ensure on the overall Quality to the consumer or end user.

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