Asking the Right Questions About AI
We’re going to talk about the realities of AI: what it can and can’t actually do, what it might be able to do in the future, and what some of the social, cultural, and ethical challenges it poses are.
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We’re going to talk about the realities of AI: what it can and can’t actually do, what it might be able to do in the future, and what some of the social, cultural, and ethical challenges it poses are.
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In the sciences, metrology is serious business. In the field of software development, it should be serious, but more often it’s just theatre; an exercise in the ritualistic use of numbers to cast a scientific aura around an otherwise irrational management process. People keep trying to count things that don’t make any sense to count, such as test cases. Here’s why you should be skeptical about measurement of software product quality.
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B. F. Skinner might be satisfied that neural networks achieve intelligence when they perform tasks well. This behaviorist perspective leads to misunderstandings of current technology and limits development toward systems that think. (...) In general, a constructivist approach will become necessary for advanced machine learning and artificial intelligence.
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Do I need to be a genius to use AI for software testing? Is AI going to replace me as a tester? Where does AI fit into my testing strategy?
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So you give your data to a guy who calls him/herself a data scientist and ask them to create something for predicting the demand — the data scientist calls this the “model”. (...) After the model is delivered, you need to know if you can trust it (blindly) and use the predictions in your daily work.
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In the manufacturing space in general, and in software development in particular, teams are moving away from quality assurance (QA) in the direction of quality engineering (QE). But what is the difference between these two concepts, and what are the driving trends towards quality engineering over quality assurance?
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In warehouses, call centers, and other sectors, intelligent machines are managing humans, and they’re making work more stressful, grueling, and dangerous.
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