Multidimensional framework to classify human–AI interactions in clinical trials (arXiv:2609.38559v1)
This arXiv preprint proposes a multidimensional classification framework for human–AI interactions (HAIIs) in clinical-trial records, combining AI tasks, human–AI relationships, interaction configurations, and interacting human groups. The authors applied the scheme to 15 trial records, independently coded by two human reviewers and six LLM classifiers, finding the framework supports more consistent comparison and that LLM assistance shows promise while human judgment remains necessary where records are incomplete or ambiguous.