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Of course, it can. I'm a machine learning engineer and algorithms are biased all the time or more accurately, the algorithm is being influenced by a biased dataset. The algorithms just do what you code them to do but they can work improperly if you dont account for all the possible edge cases like different complexions, background noise, different features, etc . A convolutional neural network for example relies on its dataset to make inferences about different features. If you made an image recognition system that was designed to detect dogs but you trained that model on only pictures of pugs, if you showed the model a picture of a german shepherd, it might not label it as a dog. That is because the model is overfitted to a biased dataset.
youtube 2019-12-09T18:4…
Coding Result
DimensionValue
Responsibilitydeveloper
Reasoningdeontological
Policyregulate
Emotionapproval
Coded at2026-04-27T06:26:44.938723
Raw LLM Response
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