Name: To transform child welfare, take race out of the equation
Uploaded: 2018-08-21T19:44:43Z
Duration: 7 min 31 s
Description: In this eye-opening talk about the impact of race and neighborhood on foster-care decisions, social worker Jessica Pryce shares a promising solution to help child welfare agencies make bias-free assessments about when to remove children from their families. "Let's work together to build a system that wants to make families stronger instead of pulling them apart," Pryce says.

In this eye-opening talk about the impact of race and neighborhood on foster-care decisions, social worker Jessica Pryce shares a promising solution to help child welfare agencies make bias-free assessments about when to remove children from their families. "Let's work together to build a system that wants to make families stronger instead of pulling them apart," Pryce says.

Jessica Pryce: To transform child welfare, take race out of the equation

To transform child welfare, take race out of the equation

Blind removal meetings in Nassau decreased black children in foster care from 57% to 21%, spotlighting bias correction in child welfare.

Exploring implicit bias, the disparity in child removal rates reveals systemic issues, urging an ethical, unbiased approach to foster care.

Artificial intelligence and machine learning proposed to scale bias-free assessments in child welfare, aiming for a fairer system.