What Ethical AI Actually Looks Like
- teegemettille
- Jul 31
- 2 min read
If you joined us earlier today for “Planning for Ethical AI in Admissions,” thank you. If you didn’t—there’s still time to catch up, because this conversation isn’t a one-day event. It’s a directional shift in how enrollment leaders think about data, equity, and action.
Throughout July, we’ve made the case that ethical AI in admissions isn’t just about avoiding bias. It’s about prioritizing attention with integrity. It means using behavioral signals to help counselors focus on students who are engaged but undecided, drifting but not gone, or committed but at risk of melt. It means doing more than reporting. It means responding—with precision and purpose.
In Tuesday's video podcast, Elizabeth Kirby helped bring that vision to life. Drawing on her work leading ethical AI conversations in higher education, she challenged us to go beyond compliance and think in terms of student trust, institutional alignment, and responsible deployment.
When AI is built and applied thoughtfully, it doesn’t just help us act faster. It helps us act better.
That distinction matters.
Ethical AI isn’t a theoretical concept at enroll ml. It’s embedded in how we:
Detect behavior-action mismatches and prevent melt.
Prioritize “swing students” before they slip through the cracks.
Free up counselors from manual work so they can build real relationships.
Keep humans at the center—always—in the decision-making loop.
If your team is facing the dual pressures of too many applicants and not enough time, this video podcast is the best 45 minutes you’ll spend this summer. It’s not about AI replacing your team—it’s about AI making your team more human in the moments that count most.
And if you’re ready to see what this looks like inside your own enrollment strategy, we’d be glad to show you. The ethical conversation doesn’t end today—it starts showing up in your funnel tomorrow.
