Legislators question AI tools impact on maternal care for women of color

May 28, 2025 | California State Assembly, House, Legislative, California


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Legislators question AI tools impact on maternal care for women of color
The Assembly Joint Hearing of the Health Committee and the Privacy and Consumer Protection Committee convened on May 28, 2025, to address critical issues surrounding maternal health, particularly focusing on the disparities faced by women of color during childbirth. The meeting highlighted the urgent need for improved healthcare outcomes for these populations.

The discussion began with a stark acknowledgment of the higher maternal mortality rates among Black women and women of color. Committee members expressed concern over existing biases in healthcare delivery, emphasizing the importance of tools that can accurately assess and respond to the varying risk factors these women face. A representative from the healthcare sector explained that their current system utilizes real-world data to continuously learn and adapt, aiming to provide equitable care across diverse patient populations.

However, concerns were raised regarding the potential for these tools to inadvertently reinforce existing disparities. One committee member pointed out that despite advancements, Black women still experience worse outcomes in delivery settings. This prompted a call for rigorous analysis of the data being used to train these AI tools, ensuring they do not perpetuate historical biases in healthcare decisions.

The conversation shifted to the need for strong governance and compliance measures to monitor these tools effectively. Committee members stressed the importance of transparency in how these algorithms function and their impact on patient care. They underscored the necessity for ongoing evaluation and adjustment of these systems to ensure they are genuinely improving outcomes for women of color.

Additionally, the meeting explored the implications of algorithms used to predict patient attendance at appointments. It was noted that such algorithms often fail to consider the socio-economic barriers that prevent patients from attending, such as transportation issues or work commitments. Instead of using these predictions to double-book patients, committee members suggested leveraging the data to reach out and support those at risk of missing appointments.

In conclusion, the meeting underscored a collective commitment to addressing racial disparities in maternal healthcare. The committees agreed on the need for continued dialogue and follow-up actions to ensure that technological advancements in healthcare are aligned with the goal of equitable treatment for all women, particularly those from marginalized communities.

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