Preparing School Psychologists for the Age of AI: A Look at Current Policies
It's been a while since I posted—things got busy with the start of the new semester. But I'm excited to share insights from a new study I co-authored with Dr. Cara Dillon, Dr. Daniel Newman, Dr. Julia Villarreal, Jakayla Fulwood, M.Ed., and Dr. Dowon Choi. Our preprint, Artificial Intelligence Governance in School Psychology Programs: Institutional and Programmatic Policies, explores a critical question: Are school psychology training programs prepared for the age of AI?
Why This Study Matters
AI is already embedded in our daily work—from writing reports and managing data to supporting students. But with that integration comes a growing list of legal and ethical challenges. We're handling confidential data, operating under FERPA and HIPAA, and expected to uphold APA standards. AI tools introduce risks such as bias, opacity, and reliability issues. Our professional responsibility includes staying within our scope of competence while helping students navigate this fast-changing landscape.
That means our training programs need to be proactive. They should equip future school psychologists with clear policies and ethical guidance around AI. We wanted to know: Are they doing that?
What We Did
We surveyed 96 faculty members in U.S. school psychology programs and collected institutional, college, and program-level AI policy documents. Then, we analyzed these policies using a detailed coding system covering 16 key ethical and practical domains, from academic integrity and attribution to data privacy and equitable access.
What We Found
General Policy Landscape
27.1% of institutions had an AI policy.
6.3% of colleges had an AI policy.
22.9% of programs had an AI policy.
Many institutions (26%), colleges (16.7%), and programs (17.7%) were still "in development."
Policy Audiences
Institution-level policies (n = 21):
66.7% targeted both students and faculty/staff.
23.8% targeted faculty/staff only.
9.5% targeted students only.
Program-level policies (n = 17):
82.4% targeted students.
17.6% targeted both students and faculty/staff.
0% targeted faculty/staff only.
Depth and Breadth of Policy Coverage
On average, institution-level policies addressed 11 of 16 key content areas (~68.8%), while program-level policies addressed only 6 of 16 (~37%). No program-level policy covered all 16 areas.
Topics like ethical considerations, use guidelines, and academic integrity were common in both.
But topics like data privacy, equitable access, and training/awareness were far less common—especially at the program level.
For example:
Only 11.8% of program policies defined what AI is.
Just 5.9% of program policies mentioned training or transparency.
0% of program policies included monitoring and evaluation plans.
What This Means for the Field
This gap is concerning. Program-level policies are closest to the day-to-day experiences of school psychology students, but they are the least developed. Without clear guidance, students and faculty are left to navigate this complex space alone.
In a field like ours, where ethics, equity, and data security are paramount, we need policies that reflect our values. That includes:
Clear definitions of AI use.
Protections for privacy and fairness.
Training on ethical AI use.
Ongoing evaluation as tools evolve.
A Call to Action
We strongly encourage school psychology programs to:
Develop or revise their AI policies now.
Include both students and faculty in the conversation.
Use frameworks grounded in ethics and equity.
The AI revolution isn't coming—it's here. Let’s make sure our training programs are ready.
This blog post is based on findings from the preprint:
Dillon, C. (Miami University), Lockwood, A. B. (Kent State University), Newman, D. S. (University of Cincinnati), Villarreal, J. N. (University of Cincinnati), Fulwood, J. (University of Cincinnati), & Choi, D. (Texas Woman’s University). (2025). Artificial Intelligence Governance in School Psychology Programs: Institutional and Programmatic Policies. PsyArXiv. https://osf.io/cjm3t_v1