Artificial Intelligence: Practical Applications for Human Services.

Author:Hussey, Carole
Position:Technology speaks

It wasn't so long ago that the term "artificial intelligence" (AI) conjured up Matrix-like images of an alternate reality, something that was so far into the future that it wasn't a realistic solution. There was no thought given to how this technology could affect human services organizations, either positively or negatively. While concerns of potentially removing critical human elements of engagement and decision-making in cases as well as the ethical use of AI remain and are certainly legitimate, the choice to ignore the benefits that could be derived from AI is myopic, at best. It's not just hype. There are practical applications and benefits for using AI in human services.

We experience AI around us every day whether by using an Alexa device at home, Siri[R] on your phone, or shopping recommendations on Amazon. As individuals and organizations, we determine if we want to use these solutions or not. Human services is no different. These decisions are made based upon risk-reward analyses. So, rather than fully reject AI as a viable solution for solving immediate problems in human services, why not evaluate where the technology can be applied, without negatively impacting children and families?

Most human services organizations struggle with similar issues, many of which point back to capacity as one of the root causes. These issues include workforce retention, caseloads, licensing, service provisioning, accuracy, and timeliness. By expanding capacity with AI, organizations can work toward mitigating many of the problems that challenge human services programs every day. With more capacity, workers and supervisors can focus on improving outcomes and doing the work they are passionate about.

In human services, some practical AI applications might include the following:

* Summarization--pulling from vast data sources (structured and unstructured) key trends or data points such as events, persons of interest, or risk indicators

* Planning and Decision Support--care plan recommendations, and resource or placement matching

* Alerting--changes in client circumstances, deviations from care plan

* Quality Control--policy and procedure adherence, timeliness, and identification of conflicting services

These examples still rely on the caseworker to make ultimate decisions, but AI provides the insights needed to make decisions confidently. The use of AI is effective in improving operational efficiency, reducing training time, ensuring consistency in...

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