According to them, from 2012 to 2022, AI-Research in some disciplines has increased significantly, especially in medical and computer sciences. However, with the increase in AI’s popularity, the number of gross methodological errors is increasing.
The main problem is that it replaces the understanding by guessing. Models usually do not explain the phenomena, but only reproduce the templates with educational data and errors. One of the typical situations is a “data leakage ğinde when the model accidentally“ finds ”in advance.
This leads to false consequences: for example, some AI systems are claimed to recognize COVİD-19, but they actually distinguished patients’ age.
The authors invite them to change their approach to researchers, to introduce control standards and to use hidden test sets to exclude the compliance of the results. Otherwise, science is at risk of entering the illusion of discoveries.
Source: Ferra
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