Artificial intelligence (AI) can now flag people who may be at elevated risk of intimate partner violence (IPV) years before they disclose the violence or seek help for it within the health-care system.

But what happens when a health-care system appears to know something about a survivor they haven’t chosen to reveal?

In a recent study, a research team led by researchers from Harvard Medical School in Boston trained AI models using routinely collected electronic health record data to identify patients at risk of IPV. On average, the models identified risk of IPV more than three years before patients enrolled in a hospital-based domestic abuse intervention program.

At first blush, this may sound like a revolutionary breakthrough in care for people who have experienced IPV. If health-care providers can identify patients at elevated risk of IPV victimization, they might be able to offer support or resources before survivors even disclose the abuse.

The findings, however, have their limits: the models were developed using data from female patients at a single U.S. academic health centre, though the researchers did validate the models in three other patient cohorts. The researchers noted that “careful performance evaluation on the more general population of female patients should be conducted before implementing the models for clinical use.”

However, viewed through a trauma- and violence-informed lens, the promise of early detection raises a critical question: what happens to a person’s agency........

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