The DOE Asked About AI. Here's How I'd Respond.

Aug 5

by Claire L. Brady, EdD

The Department of Education's recent public letter to Presidents and Boards asks institutions to explain how they will "incentivize rigor in the age of AI, combat grade inflation, and prioritize excellence in teaching and learning."

While the question is framed around artificial intelligence, the underlying issue is much broader. This is an opportunity to demonstrate how your institution will preserve academic quality while preparing students for a future in which AI is commonplace across nearly every profession.

Rather than responding with additional restrictions or focusing primarily on AI detection, I recommend institutions emphasize the following priorities.

1. Position AI as a Catalyst for Better Teaching, Not a Threat to Learning

Avoid framing AI solely as an academic integrity problem. Instead, acknowledge that generative AI requires institutions to rethink how learning is designed, assessed, and supported.

The strongest responses will emphasize educational innovation rather than technological resistance.

2. Clearly Define What Academic Rigor Means in the AI Era

Academic rigor is no longer measured by whether students complete work without AI. It is measured by whether students demonstrate critical thinking, sound judgment, disciplinary expertise, ethical reasoning, creativity, communication, and the ability to apply knowledge to authentic problems.

Define these outcomes explicitly.

3. Commit to Modernizing Assessment

The greatest opportunity lies in redesigning assessment—not simply monitoring student behavior.

Describe how your institution will expand authentic demonstrations of learning through approaches such as applied projects, portfolios, simulations, oral presentations, iterative drafts, reflective practice, experiential learning, and other forms of assessment that require students to demonstrate genuine understanding.

4. Avoid Overreliance on AI Detection Tools

AI detection technologies should not be presented as the institution's primary solution.

Instead, emphasize clear expectations for students, thoughtful assignment design, faculty education, multiple forms of evidence when questions arise, and fair academic integrity processes.

Assessment design is a stronger long-term strategy than technology-based enforcement.

5. Invest in Faculty Excellence

Teaching excellence requires ongoing professional learning.

Highlight investments in faculty development related to AI literacy, assessment design, instructional innovation, discipline-specific guidance, and the thoughtful integration of AI into teaching and learning.

Supporting faculty is essential to maintaining academic quality.

6. Establish Clear Expectations for Responsible AI Use

Students benefit from consistency.

Describe how your institution is developing transparent guidance regarding appropriate AI use, disclosure expectations, documentation practices, instructor discretion, and academic integrity.

Clarity builds trust for both students and faculty.

7. Connect AI Literacy to Workforce Readiness

Graduates will enter workplaces where AI is increasingly embedded into everyday professional practice.

Institutions should emphasize that students will graduate not only knowing how to use AI tools, but also how to evaluate AI outputs, recognize limitations, protect sensitive information, exercise professional judgment, and remain accountable for their work.

Responsible AI use is becoming an essential career competency.

8. Reinforce the Importance of Human Judgment

The goal of higher education is not to produce graduates who can generate AI outputs.

It is to develop graduates who know when AI should be used, when it should not be used, how to evaluate its reliability, and how to make informed decisions.

Human expertise, ethical reasoning, and accountability remain central to academic excellence.

9. Address Grade Inflation Through Stronger Learning Expectations

Rather than focusing solely on grading practices, explain how the institution will strengthen learning outcomes through transparent expectations, evidence-based assessment, calibration across courses and programs, continuous program review, and ongoing evaluation of student achievement.

Academic quality is strengthened by improving learning—not simply lowering grades.

10. Demonstrate Institutional Leadership

Artificial intelligence is not solely an academic affairs issue.

The strongest institutional responses will reflect collaboration among academic affairs, student affairs, information technology, libraries, institutional research, workforce development, legal counsel, governance groups, and institutional leadership.

Responding to AI requires an enterprise-wide commitment to quality, integrity, and student success.

Final Thought

The Department of Education asks institutions how they will preserve rigor in the age of AI.

The most compelling responses will avoid treating AI as the problem to solve. Instead, they will demonstrate how institutions are evolving teaching, assessment, faculty support, and student learning to ensure graduates possess the knowledge, judgment, and skills that matter most in an AI-enabled world.

This is less about writing a stronger AI policy and more about articulating a stronger vision for higher education.

Read the full US DOE letter here: https://www.ed.gov/media/document/national-call-action-university-presidents-and-governing-boards-114351.pdf