Anchoring Bias in AI: Ensuring Accuracy and Integrity in Research

Researchers can use artificial intelligence tools to streamline and enhance many steps in the research process. AI can quickly and efficiently curate research questions, identify relevant studies, synthesize prior research and identify gaps, gather and analyze data, and compose research findings and conclusions. Despite AI’s impressive capabilities, its responses are not necessarily accurate, complete, or free from bias. This presentation explores the ethics of responsible use of AI in research through the lenses of accuracy, honesty, and anchoring bias. Anchoring bias refers to a person’s tendency to over-rely on initial pieces of information that they receive, potentially discounting or ignoring other information that could confirm or disconfirm the veracity of the initial information. To mitigate this bias, researchers should think critically about AI-generated outputs, rather than over-relying on the first information they receive. This presentation provides researchers with strategies to mitigate the anchoring effect when they use AI in various stages of research: understanding AI’s limitations, nurturing awareness of anchoring bias, asking critical thinking questions to evaluate the accuracy of AI outputs, and employing other strategies to verify the accuracy and reliability of AI outputs. While AI can be a valuable research tool, researchers should remain ethically responsible for the rigor of their research methods and the veracity of the findings they report.