Seven guiding principles for practical application

In the rush to deploy AI at higher education institutions, crucial considerations are overlooked. Tools are layered onto legacy systems. Pilots are running in isolation across departments. And in some cases, vendors are shaping the implementation strategy. As AI activity expands, so does the need for institutional accountability.

Responsible AI practices provide that. They establish a framework for safely and ethically designing, implementing, and governing AI. They also help colleges and universities build trust, protect institutional and stakeholder interests, comply with evolving regulations, and stay ahead of emerging threats.

Guiding principles for responsible AI are not optional. They are essential to ensuring AI delivers on its promise: freeing people to focus on problem-solving and strategic thinking in service of institutional priorities.