  Statistics are bleak for youth aging 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 personalized goals and access curated content specific to aging out of
the foster care system. In this paper, we 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 towards their
specific needs. Finally, we examine machine learning as a support system and
aid for caseworkers to buttress and protect vulnerable young adults during
their transition to adulthood.
