US AI order shows need for student tech tips

The US is finally getting back into the AI ​​regulation game. The new AI executive order unveiled on October 30 shows that policymakers are taking seriously the many risks that AI systems can create, from wrongful arrests to biased fraud detection and large-scale misinformation.

Importantly, the order highlights the need to support educators implementing AI tools in the classroom. However, the key components of education are missing: the students.

Young people have always been early adopters of technology, and the arrival of generative AI (such as ChatGPT) has shown that students often have the knowledge and lived experience that decision-makers lack, but which are critical to deploying technology to its maximum potential.

In addition, students are also experts in their own learning and are on the main stakeholders in the learning process. It is time for universities to create student-led technology councils that empower students to participate in the decision-making processes that affect their education, careers and lives.

These councils can bring fresh perspectives and direct understanding of the challenges and opportunities technology presents in education, serving as a bridge between student bodies and university administrators and faculty, and helping to identify and prioritize student technology needs and issues. This is even more important in the context of AI, where pervasive, large-scale data collection and predictive analytics can impact students’ lives far into the future.

Student-led technology councils can also act as a catalyst for transparency and accountability. They can help oversee the ethical considerations surrounding the use of AI and technology, helping universities navigate data privacy, algorithmic bias, and the responsible use of student data.

Councils should focus on researching AI trends and advising key decision makers on the student perspective on technology commissioning and implementation. To this end, they should include students from different academic backgrounds and levels (perhaps appointed or selected from existing student organizations) and should seek diverse input from the wider student body on technology issues.

Critics may argue that students lack the expertise to make informed decisions about technology delivery and adoption. But students are constant users of AI, especially in educational settings. They are constantly being made to interact with AI systems, from online learning platforms to AI-driven administrative systems, including admissions.

However, both university management and faculty must, of course, retain some form of control over the technology that is used in the institution so that administration is efficient and learning objectives can be achieved. For example, students may argue for extensive use of generative AI in essay writing. But while these systems can help the thinking and learning process, letting AI write an essay prevents students from achieving the all-important learning goal of coming up with an argument, structuring it well, and putting it on paper.

But the student technology council should discuss and formally advise university leadership on how technology can be used responsibly and meaningfully. In particular, the board’s input should be mandated with respect to the potential procurement of technologies that directly or indirectly affect students. These may include artificial intelligence systems that predict student success, analyze student engagement, or interact with students in the context of health and wellness, such as chatbots.

Council members should solicit input from the broader student body while engaging in research into the functionalities and potential benefits and risks of any given technology. This includes liaising with university decision makers who work directly with the technology, from faculty to administrators and librarians. Putting all this together, the council should publish a well-reasoned recommendation.

University management should formally acknowledge these recommendations and, where appropriate, communicate them to the correct stakeholder group (whether faculty, student services teams, admissions or other entities) and direct that they be taken into account when making of solutions. Where procurement and implementation decisions are not in line with the recommendations, the responsible entity must explain why.

In addition to providing students with important lessons in technology policy and governance, student technology councils will help create a more inclusive and responsive environment that quickly and equitably adapts to the evolving technology landscape in ways that align with values ​​and goals of higher education institutions. . This is the kind of fair and collaborative use of AI that President Biden envisions in his executive order.

Around the world, students have long demanded more participation in university decision-making processes, highlighting the need for structural representation that is ongoing rather than ad hoc or tokenised. And in some places, student government has a long and successful history. For example, the honor system at my own institution, the University of Virginia, requires students to pledge not to lie, cheat, or steal. They sign a corresponding undertaking with every work they submit, and violations result in expulsion. The system is implemented by a student-led committee that investigates allegations, provides advice and works with accused students in their defense during the trial – a process administered entirely by students.

Examples like this show that student leadership is not just a pedagogical exercise. Students are willing and ready to be deeply involved in the design and administration of their own learning and university experience – and technology should not be exempt from their input.

Mona Sloan is Assistant Professor of Data Science in the School of Data Science and Assistant Professor of Media Studies in the Department of Media Studies at the University of Virginia (UVA). She runs away Sloan Laboratoryresearch group on the social impact of AI.

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