Intricacies of Human-AI Interaction in Dynamic Decision-Making for Precision Oncology: A Case Study in Response-Adaptive Radiotherapy.
Dipesh NiraulaKyle C CuneoIvo D DinovBrian D GonzalezJamalina B JamaluddinJionghua Judy JinYi LuoMartha M MatuszakRandall K Ten HakenAlex K BryantThomas J DillingMichael P DykstraJessica M FrakesCasey L LiveringhouseSean R MillerMatthew N MillsRussell F PalmSamuel N ReganAnupam RishiJavier F Torres-RocaHsiang-Hsuan Michael YuIssam El NaqaPublished in: medRxiv : the preprint server for health sciences (2024)
Human-AI interaction depends on the complex interrelationship between expert's prior knowledge and preferences, patient's state, disease site, treatment modality, model transparency, and AI's learned behavior and biases. The collaborative decision-making process can be summarized as follows: (i) some clinicians may not believe in an AI system, completely disregarding its recommendation, (ii) some clinicians may believe in the AI system but will critically analyze its recommendations on a case-by-case basis; (iii) when a clinician finds that the AI recommendation indicates the possibility for better outcomes they will adjust their decisions accordingly; and (iv) When a clinician finds that the AI recommendation indicate a worse possible outcome they will disregard it and seek their own alternative approach.