Enrollment prediction services contracts

To Whom It May Concern:

Pursuant to the Michigan Freedom of Information Act, I hereby request the following records:

1) All active contracts and accomanying statements of work the university has entered into for predictive machine learning services that aid in the enrollment and recruitment of students. Specifically, this includes services that feed input data provided by the university about current and historical student enrollment into machine learning models in order to make predictions about the probability of future enrollment by individual students, students from geographic regions (e.g. zip code or high school), and/or students belonging to demographic groups (e.g. Black students or first-generation students). Popular providers of predictive enrollment services include, but are not limited to: EAB, RNL (Ruffalo, Noel, Levitz), Mainstay, Othot, and The College Board.

2) Documentation of the machine learning models included in the responsive contracts. Specifically, this includes documents created by the university or provided to the university by the vendor or a third party that describe:

a) Input data—the data the university provides for analysis by the model
b) Output data—the data the model generates for the university to use (e.g., a numerical score, a probability percentage, a letter grade, or other ranking)
c) Model accuracy—metrics such as AUC, false positive/negative rates, sensitivity, specificity, etc. that demonstrate how the model performs at its intended task

If you have any questions about this request, I would be happy to set up a time to discuss it by phone or Zoom.

I ask that all fees be waived as I am a journalist and intend to used the requested records to publish articles in the public interest and not for any commercial purpose.

If you choose to impose fees, I request a detailed breakdown of the fees, including the hourly wage of each employee involved and an explanation of the employee hours required to fulfill the request.

If you choose to reject this request or redact portions of responsive documents, I ask that you provide a detailed breakdown of the statutory exemptions and associated case law underlying your decision to withhold each/any portions from public review.

The requested documents will be made available to the general public, and this request is not being made for commercial purposes.

In the event that there are fees, I would be grateful if you would inform me of the total charges in advance of fulfilling my request. I would prefer the request filled electronically, by e-mail attachment if available or CD-ROM if not.

Thank you in advance for your anticipated cooperation in this matter. I look forward to receiving your response to this request within 5 business days, as the statute requires.

Sincerely,

Todd Feathers