04 Jun Digital Advisory Panel guides NDUS in student privacy issues

A year ago, we were starting to talk about a train that was coming straight at us.  While most would say our reaction should be to get out of the way and let it pass, that wasn’t an option because this train was delivering, and whether or not we were interested or ready, arrival was imminent.

The train in this case is technology. The delivery it was bringing was artificial intelligence (AI) capabilities that were scheduled to be released in upcoming updates of common software used for data analysis and analytics. Cognos would have integrated Watson intelligence. Microsoft announced AI features coming to PowerBI. And while on the surface these features seemed exciting, providing new power to researchers using these tools for data analysis, there still hung above a cloud of uncertainty. Now that we would have the potential to analyze student data more quickly and to a greater degree, how do we align this capability with the basic human right to digital privacy? While we all agree that data mining via AI should only be used for “good”, who gets to decide what is good and whether the ultimate outcome of a study is a worth the data privacy tradeoff?

In fall of 2018, the North Dakota University System (NDUS) formed a Digital Advisory Panel. This panel consisted of approximately thirty North Dakotans from across the state who would advise the University System on issues surrounding digital privacy. The panel consists of staff within the university system (students, a registrar, a college president, and professors of law, ethics, and IT) as well as professionals across the state (a judge, legislators, and members from state agencies for employment, IT, and K-12 education).

In January of 2019 the first advisement prompt was sent to members of the Digital Advisory Panel. This prompt asked for input on the issue presented above – Are there limitations to which AI should be utilized on student data within the NDUS? Would a students’ rights policy concerning the use of AI be an issue for the university system, or reserved for each individual institution? What would be the critical pieces to include in a policy or statement regarding the use of AI on student data?

The panel members’ responses were insightful, thoughtful and well-developed. Most exciting to the team conducting the qualitative analysis of responses, there were consistent themes that emerged from the feedback. Themes were as follows:

• There is a need for university system policy surrounding the use of AI on student data
• The use of AI is ultimately a privacy issue and should be treated as such
• Benefits do exist to the use of AI on student data
• Bias can emerge from AI modeling, and this is a concern
• There is a need for transparency regarding AI research being conducted within the university system

A full report is available from the NDUS-IR department. If you are interested, feel free to contact us.

While on the surface this process seems pretty straight forward and anticlimactic, there is a lot to be excited about. First, is the recognition that very little has been done at the post-secondary level regarding the ethics surrounding the use of AI with student data – at least there is minimal information about it available on the internet. Thus there is a absence of models to use when developing policies, practices, and procedures in this domain. This work provides a framework. Second, this framework is specific to North Dakotans, whom we serve in public higher education. We now know what the big darn deals are surrounding this issue. And we would be remiss to not consider them when moving forward in this arena.

This framework developed from the input of the Digital Advisory Panel has already been applied in the university system, where the NDUS Institutional Research Department has developed a code of ethical and responsible use of analytics in reporting. This code of ethics outlines the conditions under which AI modeling and analytics can and cannot be used in research occurring in the NDUS Institutional Research office. More will be shared on that in a later post.

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Dr. Jennifer Weber is the Director of Institutional Research for the North Dakota University system.  Her primary functions are to oversee the department and provide system level enrollment reporting to the State Board of Higher Education.  Jennifer also manages system-wide IR Shared Services, works closely with the State Longitudinal Data System (SLDS) and serves as the state coordinator for federal reporting.   As the NDUS-IR is also contracted through the North Dakota Department of Public Instruction (NDDPI) for data analysis and reporting, the NDUS-IR department is ultimately responsible for the data of all students attending public institutions in the state of North Dakota, pre-kindergarten through graduate school.