| Sumario: | Accurate and appropriate pain assessment is crucial for effective pain treatment and management. When patients who are nonverbal cannot communicate, observational pain assessment carried out by health providers is riddled with issues of bias and subjectivity. Artificial intelligence-driven facial recognition technologies (FRTs) are proposed as the solution to the challenges prevalent in observational pain assessment of nonverbal patients by care providers. It promises to streamline, objectify, and promote accuracy to mitigate inaccurate pain assessment in nonverbal patients. Inaccurate pain assessment could lead to undertreatment or overtreatment of pain in nonverbal patients, with far-reaching and unintended consequences. This paper argues that close ethical scrutiny is pertinent for the deployment of AI-driven FRT for pain assessment to mitigate bias and unequal outcomes in nonverbal patients. A concerted effort by medical professionals is expedient to assure the integration of transparent, explainable, and robust data-driven FRT for pain assessment in the clinical setting to promote quality care and equitable outcomes in nonverbal patients.
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