Effect of professional experience on automation bias
Investigate whether professional experience among practicing advocates and judicial officers naturally mitigates the automation bias observed among Indian law students when they evaluate and verify legal outputs generated by large language models, in order to inform long-term AI regulation for the Supreme Court and High Courts of India.
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Future research should expand this dual-audit methodology to practicing advocates and judicial officers. Investigating whether professional experience can naturally mitigate the “automation bias” observed in students will be essential for developing long-term regulatory frameworks for AI in the Supreme Court and High Courts of India.
Inspired by our findings, another question to explore in future work is whether or how to intervene during human-AI collaboration. If AI summaries are used in high-stakes settings like policing, are there strategies that can be implemented to help officers resist the influence of misleading information?