Can machine learning create an advocate for foster youth?

BRINDLEY Meredith, HEYES James P., BROOKER Darrell
Journal article citation:
Journal of Technology in Human Services, 36(1), 2018, pp.31-36.
Taylor and Francis
Place of publication:
Philadelphia, USA

Statistics are bleak for youth ageing out of the United States foster care system. They are often left with few resources, are likely to experience homelessness, and are at increased risk of incarceration and exploitation. The Think of Us platform is a service for foster youth and their advocates to create personalised goals and access curated content specific to ageing out of the foster care system. In this article, the authors propose the use of a machine learning algorithm within the Think of Us platform to better serve youth transitioning to life outside of foster care. The algorithm collects and collates publicly available figures and data to inform caseworkers and other mentors chosen by the youth on how to best assist foster youth. It can then provide valuable resources for the youth and their advocates targeted directly toward their specific needs. Finally, the authors examine machine learning as a support system and aid for caseworkers to buttress and protect vulnerable young adults during their transition to adulthood. (Edited publisher abstract)

Subject terms:
social networks, internet, social media, leaving care, digital technology, foster children, care planning, information needs;
Content type:
practice example
United States
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