Artificial Intelligence and Data Science As a Therapeutic Intervention: Practice Implications

Abstract This workshop will train attendees on using Artificial Intelligence and Data Science as a therapeutic intervention and workforce development tool for survivors of trauma and re-entry populations. The aim is for social workers to learn to conceptualize sampling frames and principles from design thinking models which they may bring back to their own communities and agencies to develop their own Communities of Practice (CoP). Data science is becoming increasingly popular in various fields, including healthcare, business, and government. However, its potential as a clinical tool for personal growth and empowerment is less understood. Trauma survivors and the re-entry populations often face unique challenges with expression and emotional regulation, low self-esteem, and barriers to obtaining employment in the workforce. The theoretical rationale for using data science as a therapeutic intervention for trauma survivors is based on the idea that exposure to traumatic events may cause long-lasting changes in brain functioning and physiology that may negatively impact an individual's mental and physical health. The workshop will be structured into three segments: An introduction to data science session will provide attendees with an overview of data visualization as an expressive art modality that induces corrective healing processes in trauma survivors. Attendees will learn about virtual and augmented reality technologies that create immersive experiences that allow trauma survivors to revisit traumatic events in a controlled and safe environment. These technologies simulate real-world situations and help individuals learn to manage their reactions to triggers. Moreover, clinicians can assist trauma survivors with developing their expressive abilities using AI to help boost their confidence, induce corrective experiences, improve verbal communication such as letter writing that will prepare them for the workforce. The second section will focus on practical skills development, including hands-on exercises in using data science tools and techniques. The presenters will utilize simulations from their clinical and research practices. Practice and policy implications will be explored in addition to collective strategies and allyship. The final section will focus on the application of data science in real-world simulations and its benefits for personal growth and empowerment. Attendees will participate in small group exercises, to stretch their understanding about the lived experiences. Pedagogical methods used will include case study simulations. Attendees will be assigned to small groups that encourage participants to align their prior skills and practice knowledge to the vignettes. Attendees will gain a deeper appreciation for the democratization of emergent AI technologies and understand barriers to digital justice. The small groups will report their findings to the large group, generating diversity in thought. By the end of the workshop, participants will have gained knowledge and skills in data science, learned how to apply data science in real-world scenarios, and be more prepared to apply these skills in their agencies and practical settings. Attendees will be oriented on how to intervene with trauma healing and data science approaches to improve outcomes for survivors of trauma. Keywords: data science, trauma informed intervention, circle of insight, machine learning