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

> **NIH NIH R41** · IRIS OB HEALTH INC. · 2022 · $137,274

## Abstract

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.

## Key facts

- **NIH application ID:** 10593284
- **Project number:** 3R41MH124581-02S1
- **Recipient organization:** IRIS OB HEALTH INC.
- **Principal Investigator:** Michael B. Laskoff
- **Activity code:** R41 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $137,274
- **Award type:** 3
- **Project period:** 2021-07-21 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10593284

## Citation

> US National Institutes of Health, RePORTER application 10593284, Bioethical Considerations for Building, Evaluating, and Implementing Artificial Intelligence in Perinatal Mood and Anxiety Disorders (3R41MH124581-02S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10593284. Licensed CC0.

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