Bioethical Considerations for Building, Evaluating, and Implementing Artificial Intelligence in Perinatal Mood and Anxiety Disorders

项目总结 产后抑郁症(PPD)是一种常见但可治疗的疾病，如果及早发现，也可以 如果不治疗，会对母子产生有害的影响。产后抑郁的常规筛查是 被认为是最佳做法，但由于时间和资源的限制，并不总是发生。 因此，治疗干预措施启动较晚，许多产后抑郁病例未被发现。 总而言之。人工智能(AI)模型可以弥合PPD识别差距，并具有 已被证明能够主动、准确地识别患有产后抑郁风险升高的女性。虹膜OB 数字健康初创公司Health为产后抑郁构建了一个预测性人工智能模型。爱丽丝队是 开发一个界面，向患者和临床医生展示我们的人工智能模型，以促进共享 关于降低风险的干预措施的决策。通过这项工作，我们认识到 需要更好地理解面向患者的人工智能的生物伦理影响。中国的生命伦理学研究 人工智能一直专注于展示模型输出，并培养临床医生对人工智能的信任。然而， 从患者的角度来看，重要的伦理问题仍然没有得到回答。具体地说，它是 不清楚患者是否被告知或批准他们的数据被用于建模 目的。随着耐心参与和共同决策的重要性继续上升，它 人工智能的输出也可能被呈现给患者。PPD呈现了一种复杂的生命伦理 研究面向患者的人工智能的案例，因为在怀孕期间，自主性、危害和好处 必须同时称量围产期患者、新生儿/胎儿和配偶的体重。 因此，本副刊将侧重于制定具体的指导意见，以创建和 实施面向患者的人工智能，同时坚持利用患者数据的伦理原则 敏感和公平地使用PPD作为用例。具体目标是：1)三角测量 从透明、合乎道德和公平的角度在人工智能中使用患者数据进行PPD 通过半结构化访谈吸引不同利益相关者，以及2)评估知识、态度、 以及育龄妇女在产后抑郁中使用人工智能的偏好。 全国范围内的调查。为了实现这些目标，我们将利用我们的多学科团队 父母给予资助，并包括具有产科专业知识的新调查人员， 围产期精神病学、人工智能发展、信息学、定性研究、调查方法和 以用户为中心的设计。鉴于与人工智能相关的生物伦理问题的爆炸性增长，但缺乏 关注面向患者的人工智能，该项目填补了推进生物伦理人工智能的一个重要空白 研究。这项工作将为未来人工智能在其他心理健康领域的工作提供信息，并将 由Iris OB Health直接纳入第二阶段开发活动。

PROJECT SUMMARY Postpartum depression (PPD) is a common, yet treatable illness if detected early, but it can also have deleterious effects to the mother and child if left untreated. Routine screening for PPD is considered best practice but does not consistently occur due to time and resource constraints. As a result, therapeutic interventions are initiated late and many PPD cases go undetected altogether. Artificial intelligence (AI) models can bridge the PPD identification gap and have been shown to proactively, accurately identify women with an elevated risk for PPD. Iris OB Health, digital health startup company, has built a predictive AI model for PPD. The Iris team is developing an interface that presents our AI model to patients and clinicians to facilitate shared decision-making about interventions to decrease risk. Through this work, we are recognizing the need to better understand the bioethical implications of patient-facing AI. Bioethics research in AI has focused on presenting model output and fostering trust in AI among clinicians. However, important ethical questions from the patient perspective remain unanswered. Specifically, it is unclear if patients are informed about or approve of their data being utilized for model building purposes. As patient engagement and shared decision-making continue to rise in importance, it is likely that AI output will also be presented to patients. PPD presents a complex bioethical case for studying patient-facing AI because, in pregnancy, the autonomy, harms, and benefits afforded to the perinatal patient, newborn/ fetus, and partner must be weighed simultaneously. Therefore, this supplement will focus on developing concrete guidance for creating and implementing patient-facing AI while upholding ethical principles to utilize patient data sensitively and equitably, using PPD as a use case. The specific aims are to: 1) triangulate perspectives for transparent, ethical, and equitable use of patient data in AI for PPD from diverse stakeholders through semi-structured interviews, and 2) evaluate knowledge, attitudes, and preferences related to the utilization of AI in PPD among women of child-bearing age via a nation-wide survey. To accomplish these aims, we will leverage our multidisciplinary team from the parent grant and include new investigators who have collective expertise in obstetrics, perinatal psychiatry, AI development, informatics, qualitative research, survey methods, and user-centered design. Given the explosion of bioethical questions related to AI but the lack of attention paid to patient-facing AI, this project fills an important gap in advancing bioethical AI research. This work will both inform future AI work in other mental health domains and be directly incorporated into Phase II development activities by Iris OB Health.