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Cognitive biases within Artificial Intelligence are a common phenomenon. Before this background, we asked ChatGPT what the cognitive biases of AI are. In this article, we critically reflect on the response we got from Generative AI, and discuss cognitive biases in general. We then focus on concrete implications for handling cognitive biases. Such as Algorithms and techniques that can help AI systems identify and reduce bias could be implemented, and standardized techniques to check AI systems for bias before implementation. We also highlight the importance of realizing procedures for ongoing observation and input to identify and rectify prejudices in AI systems once they are put into use. We conclude that solving such biases calls for an allencompassing strategy that incorporates experts from other fields and places an emphasis on moral issues in addition to technological fixes. By doing this, we can encourage the creation of AI technologies that are not just advanced but also ethical, equitable, and beneficial to society as a whole.
Brem et al. (Fri,) studied this question.
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