Experts related to hiring and neural networks note that neural networks are capable of performing unskilled tasks, routine. This means that the capabilities of artificial intelligence are best used to automate large-scale and meticulous work, where the so-called "human factor" can come into play - errors due to loss of concentration. For example, tracking shoplifting, traffic violations, searching for errors and hong kong telegram number database patterns in a data array, etc.
Neural networks are not capable of performing tasks that require high qualifications, multitasking, and consideration of a person's personal characteristics. The machine does not make decisions, it only offers options or provides information for reflection. AI will definitely not replace a production editor, therapist, teacher, chief accountant, or any other specialist with extensive experience.
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AI uses human labor as the basis for its work
Machine learning models use information collected and prepared by humans in the process of their work and development. Both generative, like ChatGPT, and convolutional, and many other neural networks use data from the Internet or a pre-labeled array of data for training (for example, a person shows what is what in a photo or video). Thus, the issue of intellectual property rights is actively discussed in the legal field: can AI content be considered truly unique if it is entirely based on the work of other people. If a person does not give the neural network new data for training, it will not develop.