Over the last few months, I’ve been thinking about how AI should be used on our campuses. There’s no question the tools exist and are becoming mainstream. Earlier this summer, I talked about some of the risks that existed for teams when using AI.
Despite these, I think it’s important for marketing and comms leaders to take an active role in shaping how AI is used on our campuses. This past year, our university formed several different committees to explore AI use. I worked diligently to have a member of our team represented in these spaces because I wanted to make sure we were part of the conversation and decisions were not made without us in the room that could impact how our team used AI.
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Wrestling with AI
My university isn’t the only one wrestling with how AI should be used and how it should be governed. During my session at the Engage Summit, over half of the attendees in the room noted their university was both using AI and also trying to develop governance around it.
This aligns with national data as well. According to the latest report from InsideHigherEd, more than half of university presidents surveyed said their university was developing a task force to study how AI should be used on their campuses.
I personally think this is the year the conversation will shift from looking at the tools to a more robust conversation about the ethics and governance of how these tools should be used.
AI Approaches
As I’ve looked at AI governance, there are two differing approaches. One approach is developing guiding principles, which are statements about who the institution is and how AI aligns with its values. Guiding principles are good for centering the AI conversation. The other approach is operational strategy. This is a more tactical approach that offers guidance about AI should be utilized in specific situations.
They are different, but each has an important role. From the research I’ve done, the institutions doing the best with AI are using both guiding principles and operational strategy.
Guiding Principles
- What we believe
- Theoretical
- Values-based
Operational Strategy
- How we operate
- Tactical
- Experience-based
Guiding Principles
In preparation for my Engage Summit presentation, I wanted to understand how universities were thinking about guiding principles. I researched these across multiple institutions and found five common themes that are prevalent in most guiding principles
1. Human Oversight First – Every institution approaches this differently, but this is the idea that AI is a tool or thought partner. It should not be making decisions about the work. Instead, staff are responsible for decision-making functions. This includes ensuring the accuracy and appropriateness of outputs. Also, the final responsibility for the communication, analysis, or decision should always rest with the human thought leader.
2. Data Privacy and Security – The primary tenet of this principle was ensuring the campus community understood the importance of keeping student and employee data confidential and creating awareness of the dangers of inputting this data into public, unsecured AI platforms. Additionally, many institutions spoke about only using AI tools that have gone through proper campus vetting as a strategy to mitigate this risk.
3. Transparency – Most institutions operate with the idea that using AI was acceptable in many situations. However, these cases should be documented and disclosed. Several institutions took this approach a step further, articulating AI use should be cited, much like a source in a research paper to help others better review and reproduce similar work in the future.
4. Equity and Ethics – This principle focused on questioning whether the outputs were reasonable. Specifically, were the outputs logical for the question asked? Also, were there any bias, equity, or fairness issues that surfaced in the outputs. Other institutions noted the importance of making sure that AI tools were not used in ways that could disadvantage, stereotype or misrepresent others. Very few institutions spoke about the environmental impacts here, but I suspect that will become more prevalent in the future.
5. Continuous Learning and Governance – Many guiding principles focused on being life-long learners at the institution, and AI was another part of that commitment. These institutions spoke about how AI was a prevalent tool, so the institution had a responsibility to teach it to their students, but also to the community and employees. Additionally, because of the rapid rate of change, this tenet also spoke about the value of continuous governance and training for university employees as AI evolves.
Operational Strategy
Next month, I’ll dig a bit deeper into operational strategy and provide some working ways to think about using this in your work. If you want that blog post delivered directly to your inbox, be sure to subscribe.
Looking Ahead
AI is changing quickly, which creates a leadership challenge to make sure our institutions use the tools in ways that align with who we (the institution) are and what we value. Good governance won’t slow innovation, but it will help ensure innovation happens purposefully.
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