Preface

This book is a work in progress. It develops a framework for adopting ChatGPT and related tools for the Campus. It is not a complete strategic plan and is not meant to be proscriptive. It is meant to help organize and communicate efforts.

The key component of the framework, in my opinion, is the recognition that, while the campus is a single entity, it is composed of four relatively distinct “Domains” that each have their own needs, requirements, resources, and priorities. The four domains that I have identified are:

The framework is based on the idea that each of these domains has a different set of needs and requirements, and that the campus should develop plans and implementations that are tailored to each domain. The framework includes a set of “principles” that should be applied to each domain, and a set of “strategies” that should be applied to each domain. The principles and strategies are not meant to be proscriptive, but rather to provide guidance and a framework for thinking about how to approach each domain.

The framework is also based on the idea that the campus should adopt a “platform” approach to the development of tools and services. I have included the “platform” concept as a set of identifiable cross-domain workstreams.

I also note that this framework is not meant to be a “top-down” approach. Rather, it is meant to be a “bottom-up” approach that is driven by the needs of the individual domains. The framework is meant to provide a common language and common set of tools that can be used to develop solutions that meet the needs of the individual domains and the campus as a whole.

The framework is also meant to be a living document. It is meant to be updated and revised as new information becomes available and as new needs and requirements are identified. Progress on the framework should be tracked and reported on a regular basis.

Finally, this framework can form the basis for adoption of any AI (or even other technology) on campus. It is not specific to ChatGPT, though I have found that approaching frameworks with concrete examples is key to success. In that regard, time invested in creating robust processes for ChatGPT will pay dividends in the future as other AI technologies are adopted.