In this episode of Two Doctors and a Twist, Dr. Marilyn Carroll and Dr. Jamie Chesler examine a leadership question every college and university must answer: Who is accountable when artificial intelligence influences an institutional decision?
AI now touches admissions, advising, enrollment, marketing, student support, assessment, human resources, finance, research, and institutional operations. Because its influence extends across the institution, AI governance cannot sit exclusively within the technology department or become someone’s secondary responsibility.
The central message is clear: AI may inform an institutional decision, but a human being must always remain accountable for the outcome.
Key takeaways include:
- AI governance is a leadership responsibility, not simply an IT function.
- Governance should cross academic affairs, technology, human resources, legal, compliance, senior leadership, and the board.
- An AI policy explains what people are permitted to do; AI governance establishes who is responsible for what happens.
- Decisions affecting admissions, financial aid, academic standing, accessibility, discipline, employment, assessment, and opportunity require meaningful human oversight.
- AI recommendations and human decisions are not the same thing.
- Institutions must avoid an “accountability gap” in which no one knows who is responsible for questioning an AI output or making the final decision.
- Colleges should model the same transparency, verification, and accountability they expect from students.
- Leaders do not need to become AI engineers, but they must understand AI well enough to ask informed questions about privacy, bias, data governance, risk, workforce implications, and human oversight.
- Governance structures may vary according to an institution’s size and resources, but accountability cannot.
- Responsible AI governance can become a competitive differentiator by helping institutions earn trust rather than merely attracting attention through early adoption.
The episode also reframes AI procurement as a governance decision. Before purchasing an AI system, institutional leaders should ask:
- What mission-related problem are we solving?
- What data does the system require, and where does that data go?
- What institutional decisions will the technology influence?
- How was the model evaluated?
- What biases and risks have been identified?
- Can its recommendations be explained, challenged, and overridden?
- What happens when the system is wrong?
- What evidence supports the vendor’s claims?
- Who is ultimately accountable?
Four questions every college leader should be able to answer emerged from the discussion:
- Is our AI strategy driven by technology or by mission?
- Who owns AI governance?
- How are faculty and staff being prepared for AI-enabled work?
- What evidence proves that our institution uses AI responsibly?
The rapid-fire round reinforced the episode’s conclusions:
- AI policy or AI governance? Governance.
- Innovation or oversight? Both—innovation without oversight creates risk, while oversight without innovation can leave an institution behind.
- Technology decision or leadership decision? Leadership decision.
- First adopter or most trusted adopter? Most trusted adopter.
- Who is accountable? A human being—always.
The closing message: History may not remember which institutions adopted AI first. It may remember which institutions governed it best.
Technology can inform. People remain accountable.
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