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Artificial intelligence-based student activity monitoring for suicide risk : considerations for K-12 schools, caregivers, government, and technology developers / Lynsay Ayer, Benjamin Boudreaux, Jessica Welburn Paige, Pierrce Holmes, Tara Laila Blagg, Sapna J. Mendon-Plasek.
- Format:
- Book
- Author/Creator:
- Ayer, Lynsay, author.
- Boudreaux, Benjamin, author.
- Paige, Jessica Welburn, author.
- Holmes, Pierrce, author.
- Blagg, Tara, author.
- Mendon-Plasek, Sapna J., author.
- Language:
- English
- Subjects (All):
- Students--Suicidal behavior--United States.
- Students.
- Suicide--United States--Prevention.
- Suicide.
- Children--Suicidal behavior--United States.
- Children.
- Youth--Suicidal behavior--United States.
- Youth.
- Child mental health--United States.
- Child mental health.
- Youth--Mental health--United States.
- Artificial intelligence--Educational applications--United States.
- Artificial intelligence.
- Artificial Intelligence.
- Mental Health and Illness.
- Artificial intelligence--Educational applications.
- Children--Suicidal behavior.
- Students--Suicidal behavior.
- Suicide--Prevention.
- Youth--Mental health.
- Youth--Suicidal behavior.
- United States.
- Local Subjects:
- Artificial Intelligence.
- Children.
- Mental Health and Illness.
- Students.
- Suicide.
- Other Title:
- Artificial Intelligence–Based Student Activity Monitoring for Suicide Risk
- Place of Publication:
- RAND Corporation 2023
- Summary:
- In response to the widespread youth mental health crisis, some kindergarten-through-12th-grade (K–12) schools have begun employing artificial intelligence (AI)–based tools to help identify students at risk for suicide and self-harm. The adoption of AI and other types of educational technology to partially address student mental health needs has been a natural forward step for many schools during the transition to remote education. However, there is limited understanding about how such programs work, how they are implemented by schools, and how they may benefit or harm students and their families. To assist policymakers, school districts, school leaders, and others in making decisions regarding the use of these tools, the authors address these knowledge gaps by providing a preliminary examination of how AI-based suicide risk monitoring programs are implemented in K–12 schools, how stakeholders perceive the effects that the programs are having on students, and the potential benefits and risks of such tools. Using this analysis, the authors also offer recommendations for school and district leaders; state, federal, and local policymakers; and technology developers to consider as they move forward in maximizing the intended benefits and mitigating the possible risks of AI-based suicide risk monitoring programs.
- Contents:
- Chapter One: Introduction
- Chapter Two: Youth Suicide and Artificial-Intelligence-Based Risk Detection
- Chapter Three: How Artificial-Intelligence-Based Tools Are Used for Student Suicide Risk Detection in Schools
- Chapter Four: Benefits and Risks of Artificial-Intelligence-Based Suicide Risk Monitoring
- Chapter Five: Summary of Main Findings
- Appendix A: Methods
- Appendix B: Interview Protocols
- Appendix C: Study Respondents.
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