aiddependent
AIDdependent is a term used primarily in the context of artificial intelligence (AI) research and machine learning to describe models that exhibit strong reliance on auxiliary inputs or data during training, even when such inputs are not necessary for the task at hand. These models may become overly dependent on specific features, labels, or additional data points that are not inherently part of the core problem, leading to suboptimal performance when those inputs are removed or altered.
The concept gained attention in discussions surrounding AI fairness, robustness, and interpretability. For instance, some AI
Researchers have explored ways to mitigate AIDdependency by designing more robust training methodologies, such as removing
Critics argue that AIDdependency highlights broader issues in AI development, including the need for more transparent