Book/Printed Material Artificial intelligence-based student activity monitoring for suicide risk : considerations for K-12 schools, caregivers, government, and technology developers

Title

• Artificial intelligence-based student activity monitoring for suicide risk : considerations for K-12 schools, caregivers, government, and technology developers

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.

Names

• Ayer, Lynsay, author
• Blagg, Tara, author
• Boudreaux, Benjamin, author
• Holmes, Pierrce, author
• Mendon-Plasek, Sapna J., author
• Paige, Jessica Welburn, author
• Rand Corporation
• RAND Education and Labor (Program)

Created / Published

• Santa Monica, Calif. : RAND Corporation, [2023]

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.

Headings

• -  Artificial intelligence--Educational applications--United States
• -  Child mental health--United States
• -  Children--Suicidal behavior--United States
• -  Students--Suicidal behavior--United States
• -  Suicide--United States--Prevention
• -  Youth--Mental health--United States
• -  Youth--Suicidal behavior--United States
• -  Artificial Intelligence
• -  Children
• -  Mental Health and Illness
• -  Students
• -  Suicide
• -  Artificial intelligence--Educational applications
• -  Child mental health
• -  Children--Suicidal behavior
• -  Students--Suicidal behavior
• -  Suicide--Prevention
• -  Youth--Mental health
• -  Youth--Suicidal behavior
• -  United States

Notes

• -  Includes bibliographical references (pages 67-75)
• -  Description based on print version record; resource not viewed.

Medium

• 1 electronic resource (ix, 75 pages )

Call Number/Physical Location

• HV6545.8

Digital Id

• https://hdl.loc.gov/loc.gdc/gdcebookspublic.2024738933

Library of Congress Control Number

• 2024738933

Reproduction Number

• $19.00 £14.99

Rights Advisory

• This is non-restricted, fully open content that may be accessed on and off of the Library of Congress campus, with no restrictions, by an unlimited number of users

Access Advisory

• Unrestricted online access

Online Format

• image
• pdf

LCCN Permalink

• https://lccn.loc.gov/2024738933

Additional Metadata Formats

• MARCXML Record
• MODS Record
• Dublin Core Record