Description: Negativity bias is a psychological phenomenon that manifests when negative experiences or information have a disproportionate impact on our perceptions and decisions compared to positive experiences. This bias can influence how we process information, leading us to pay more attention to the negative aspects of a situation, which can distort our overall view. In the context of artificial intelligence (AI), this bias becomes particularly relevant, as AI models are trained on data that may be biased. If the training data contains a higher proportion of negative examples, the AI may learn to prioritize these aspects, affecting its performance and the quality of its decisions. This can result in systems that are more prone to identifying problems or risks but may overlook opportunities or positive outcomes. Understanding negativity bias is crucial for the ethical development of AI, as it can influence the fairness and effectiveness of AI applications in various domains, from healthcare to finance.
