Can automated testing create a better foundation for ethical, responsible, and transparent AI?
I think you can say using AI as a tool, but also thinking of automation holistically—covering areas like governance, user experience, and ethical considerations. It’s about applying AI strategically, not just using it for speed or cost-cutting, unlike traditional automation which focuses mainly on repetitive tasks.
AI can definitely cut down on some tasks that need to be done by hand, but I’ve noticed that it doesn’t get rid of the need for people altogether. Instead, people move up to more complex jobs like keeping an eye on things, fixing problems, and dealing with tricky situations. When it comes to when we’ll have AI doing most of the QA work, I’d guess we’re still a couple of years off from that happening.
It’s all about doing a good job, not just doing a lot. AI can handle the boring, repetitive testing stuff, letting QAs spend their time on the more important, creative testing. To handle this change, you’ve got to get better at using AI tools and get used to new ways of working, all while showing everyone how crucial QA’s job is in making sure AI results are top-notch.
Sure, totally! AI is a strong tool, but getting the basics of testing, such as Java and Selenium, is key. AI can’t do it all, so having a strong base in automation will help you use AI better.
To get your manager on board, begin with something small—suggest a trial run that uses AI for certain, big-deal tasks like regression testing. Demonstrate to them how AI can cut down on time, money, and make things run smoother, while making a strong argument for doing more of it.
Manual testing is super important when you’re checking out how users feel about things, dealing with tricky situations, or when you need someone’s smarts to figure things out. Sure, AI and machines are awesome for doing the same thing over and over, but doing Manual testing is still key for coming up with new solutions and checking out stuff you haven’t seen before.
A balanced approach is about using AI for stuff like predicting outcomes and checking how well things work, but also sticking to doing tests by hand for more detailed, digging into tasks. It’s about knowing what each is good at and using them in the right places.
Begin by figuring out where AI can make a quick difference, such as tasks that are the same over and over again. Teach your team how to use AI tools, and make a plan to slowly start using it. Getting better service will happen by mixing the smarts of people with the speed of AI.
Even though AI is getting better and better, I don’t think it’s going to take over completely anytime soon. It’s really good at doing the same thing over and over again, but we still need people to make the tough calls, think about what’s right and wrong, and figure out if something works well in different situations.
Right now, AI is mainly taking care of doing the same tasks over and over again. To do more, we need to mix AI with smart test creation, scripts that can fix themselves, and models that keep getting better and adjust to changes in software. We can put these things into tools like Selenium or Appium.
Testing out AI-ML models can be tough because they keep changing. You’ve got to use methods like always checking them, making sure the data is right, and finding bias.
In the next year, I think AI will be more of a team player in testing, handling a lot more test cases and even predicting when things might go wrong. But it’s going to be a mix of AI and human testers working together.
Definitely! AI is great at doing the same tests over and over again. It can do it faster and better than people, which means we can spend more time on the important stuff.
AI can make testing quicker by doing things like creating test cases on its own, fixing tests that break by themselves, and cutting down the time it takes to run big tests. The key is using AI for the tasks that are the most repetitive and time-consuming.
AI in software testing can help with predicting what might go wrong, making test cases on its own, and even making sure tests cover everything. Tools like Devin AI make these tasks easier, letting testers focus on the bigger picture.
Yes, if AI is getting more involved in making software, we’ll need to step up our game in testing. We’ll have to keep an eye on AI-made code to make sure it doesn’t cause any problems or ethical issues. Testing will be a crucial part of making AI work well.
Absolutely. By making testing automatic, we can make sure AI is fair, transparent, and reliable. Automated tests can spot any biases early, making sure AI stays ethical and responsible all the way through.