Clever Han

The Clever Hans effect describes the phenomenon where machine learning models achieve high accuracy by exploiting spurious correlations in data rather than learning the intended task. Current research focuses on identifying and mitigating this effect in various domains, including unsupervised learning, image classification (e.g., echocardiography), and natural language processing (e.g., large language models), employing techniques like data augmentation and explainable AI to improve model robustness and generalization. Addressing the Clever Hans effect is crucial for building reliable and trustworthy AI systems, ensuring that predictions are not only accurate but also based on genuine understanding of the underlying data.