Authors
Gates, Susan M., Huang, Wenjing, Mattock, Michael G., Gulden, Timothy R., Collopy, Arianne, Moon, Alvin, Robson, Sean, Todd, Ivy, Wong, Jody Chin Sing, De Bruhl, Brandon, Price, Carter C., Bandini, Julia, Martin, Laurie T., Wang, Jessie, Dinh, Tuyen, Miner, Skye A., Maslov, Nikolay, Lytell, Maria C., Slama, Rachel, Goldman, Charles A., Lim, Nelson, Bakhshi, Rushil, Sahoo, Srikant Kumar, Hyde, Kelly, Pathak, Ojashwi, Shenk, Anton, Karam, Rita T., Clague, Angela K., Williams, Madison, Kushner, Jonah, Sandler, Morgan, Yeung, Douglas, Krueger, Tracy C., Vahedi, John, Sousa, Éder M., Butler, Dwayne M., Calkins, Avery, Lee, Mary, Esteves, Fernando, Pokhriyal, Neeti, Alhajjar, Elie, Crosby, Brandon, Sytsma, Tobias
- Division
- RAND Education and Labor RAND Homeland Security Research Division RAND Project AIR FORCE
- Pages
- 90
- Published in
- United States
- RAND Identifier
- PE-A3414-1
- RAND Type
- commentary
- Rights
- RAND Corporation
- Series
- Expert Insights
- Source
- https://www.rand.org/pubs/perspectives/PEA3414-1.html
Table of Contents
- About This Paper 3
- RAND Education and Labor 3
- RAND Homeland Security Research Division 3
- RAND Project AIR FORCE 4
- Funding 4
- Acknowledgments 4
- Contents 5
- Summary 7
- Issue 7
- Approach 7
- Key Findings and Policy Implications 8
- Section A Integrating AI into the Workforce 8
- Section B Use CasesApplying AI in the Workforce 8
- Section C Educating and Training the Workforce to Use AI 9
- Section D Building a More Resilient and Diverse AI Workforce 9
- References 10
- Introduction 11
- Leveraging the Promise of AI in the Workforce and Mitigating Its Harms 12
- Federal Efforts on AI in the Workforce 12
- Purpose of This Publication 13
- Contributors and Their Perspectives 13
- Structure of This Publication 14
- Notes 14
- References 15
- Section A 17
- INTEGRATING AI INTO THE WORKFORCE 17
- Taxonomy of AI Adoption Risks and Effect on Adoption in the Workforce 18
- References 20
- Supply and Demand in the AI Ecosystem 21
- The AI Ecosystem 21
- Conclusion 24
- Notes 24
- References 24
- Section B 25
- USE CASESAPPLYING AI IN THE WORKFORCE 25
- The Prototype Tool 26
- Rapid-Development Chatbots for Workforce Training and Support 26
- Principles for Success 27
- Security First 27
- Transparency Matters 27
- Maintain Human Responsibility 27
- Train on Policy Documents 28
- Flexibility Is Key 28
- Implementation Architecture 28
- Conclusion 29
- To Chat or Not to Chat Using AI to Communicate with Patients and Relieve the Burden on the Health Care Workforce 30
- AI Chatbots May Assist with Administrative Tasks to Decrease Burdensome Touchpoints 31
- AI Chatbots May Be Used to Better Streamline Patient Care Interactions 31
- AI Chatbots May Create Problems or Exacerbate Existing Problems in Health Care Communication 31
- Considerations for the Future 32
- References 33
- HR Tasks That Lend Themselves to AI 34
- Applying AI Tools to Complete Common Human Resource Management Tasks 34
- Overview of Embeddings and Generative AI for HRM 35
- Embeddings 35
- Generative AI 35
- Conclusion 37
- Navigating the AI Landscape Choosing the Right Tool for the Job 38
- How to Choose the Right Type of AI 39
- Conclusion 41
- Notes 41
- References 42
- Section C 43
- EDUCATING AND TRAINING THE WORKFORCE TO USE AI 43
- Upskilling and Retraining the Federal Workforce for AI Adoption 44
- Implement a Broad Collection of Training Programs 45
- Invest in the Right AI Tools and Infrastructure 45
- Foster a Culture of Continuous Learning 46
- Conclusion 46
- References 47
- The Promise of AI to Transform Teaching Will Fail If School Systems Do Not Transform Too 48
- References 50
- Helping Postsecondary Education and Training Institutions Overcome Barriers to Preparing the New AI Workforce 51
- Strategically Partner with AI Industry 52
- Better Align Education and Training with AI Labor Market Needs 53
- Attract Students 53
- Redesign Curriculum and Career Pathways 53
- Attract Develop and Retain Faculty 54
- Acquire New Facilities and Infrastructure 54
- Support Minoritized Students 54
- Establish Monitoring and Evaluation Systems 54
- Support Institutions with Policies and Funding to Overcome Barriers 54
- Leveraging AI in the Military Leader Development Framework 55
- Setting Conditions for Integrating AI into PME 56
- Future Considerations for AI in PME 56
- Matching AI Instruction with the Level of Leadership Development 57
- Conclusion 57
- References 58
- Notes 58
- Section D 59
- BUILDING A MORE RESILIENT AND DIVERSE AI WORKFORCE 59
- Retaining Workers with AI Skills in the Federal Workforce 60
- Raise Compensation 61
- Improve Future Opportunities 61
- The Way Forward 61
- References 63
- Notes 63
- Is the Domestic AI Talent Pool Sufficient to Meet Public Sector Demand 64
- A Disparity in Degrees 65
- Limits on Foreign-Born Employment 65
- Competition with Private Businesses 66
- Recommendations 66
- References 66
- Notes 66
- Building a Diverse Pool of AI Talent for DHS Recruitment 67
- Recommendations 70
- References 71
- Identifying Resilient Skills in an AI-Enhanced Economy 72
- Key Findings 73
- Recommendations 75
- Notes 75
- References 75
- Engaging the Federal Workforce in AI Implementation 76
- How to Clear the Hurdles 77
- Conclusion 78
- References 79
- Notes 79
- Understanding and Addressing Resistance to the Adoption of New Technologies in DoD 80
- Factors Contributing to Resistance 81
- Fear of Job Displacement 81
- Lack of Trust in AI Systems 81
- Skill Gaps 82
- Strategies to Address Resistance 82
- Transparent Communication and Collaborative Implementation 82
- Comprehensive Training and Support 82
- Ethical and Safety Concerns 82
- Conclusion 82
- References 83
- Principles on AI Implementation for Federal Leaders 85
- References 86
- About the Authors 87
