Evaluating AI Tools for Research: A Framework for Accuracy, Bias, and Trustworthiness

The Quiet Risk Behind Convenient Intelligence AI-assisted research has reached a point where the bottleneck is no longer access to information, but the reliability of what is returned. Tools powered by large language models can synthesize papers, summarize datasets, and even propose hypotheses. The problem is not capability - it's calibration. When an AI system produces a confident answer, how do we know whether it is correct, biased, or subtly misleading? This article proposes a practical frame