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    Home»Meditation»Dan Ziebel of Student Defense on AI in Admissions, student data rights, and the AI ​​Bill of Rights
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    Dan Ziebel of Student Defense on AI in Admissions, student data rights, and the AI ​​Bill of Rights

    adminBy adminMay 25, 2026Updated:May 25, 2026No Comments5 Mins Read0 Views
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    Dan Ziebel of Student Defense on AI in Admissions, student data rights, and the AI ​​Bill of Rights
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    Student Defense Co-Founder Dan Ziebel took charge college investor At the ASU+GSV Summit to talk about how colleges are using AI in admissions, grading and student lending — and why students deserve transparency about it.

    Recorded live at the ASU+GSV Summit in San Diego, robert farrington Student Defense co-founder sits down with Dan Ziebel to talk about how artificial intelligence is reshaping higher education (from admissions decisions to class grading to student loan lending) and what students and families should be asking about it.

    National Student Legal Defense Network is a policy and advocacy organization that works on consumer protection in higher education, including admissions and recruitment, student loan servicing, access to basic needs, and data privacy.

    The group is now pushing for AI Bill of Rights for students This will require institutions to deploy AI transparently and ethically, so that students can understand when and how it is being used in decisions that affect their education and finances.

    episode summary

    • The Case for an AI Bill of Rights for Students and What It Would Ask of Colleges.
    • How schools are using AI to screen applications and shape admissions decisions.
    • Data sovereignty and what happens to student-written work after it is fed into institutional AI systems.
    • AI in student loans, including how fintech underwriting models may carry historical biases.
    • What this means for AI grading and assessment and the value of college degrees.
    • Practical questions students and families should ask during the college search.

    AI Bill of Rights for students

    Ziebel said Student Defense wants institutions to deploy AI”To ensure that both schools and students can benefit from AI in a transparent and ethical manner.“

    The framework recognizes the potential of these tools and asks colleges to disclose how and why they are using them, and what they are trying to achieve.

    AI in college admissions

    With schools like the University of Michigan now reviewing approximately 115,000 applications per year, AI provides efficiency benefits. But Ziebel said questions about what is being sacrificed often remain unanswered. Student Defense wants to flip the script and ask how institutions are using AI in recruiting and admissions decisions, not how applicants are using it to choose schools or write essays.

    He also drew a line between technology and AI. Sort spreadsheets by SAT and GPA are not AI. But when schools use AI to review applications, evaluate essays, or score essays, “One of our biggest efforts is for transparency, which students have the right to know“Has AI played any role in admission decisions.

    Robert also risked prejudice. Large language models are weighted on training data, and applicants have no visibility into what data has shaped the model reviewing their essay.

    student data sovereignty

    The second pillar of the framework is data sovereignty. Students should know how their data is being used, when it is being used, and whether it is informing the institution’s AI models (including the work they produce after enrollment).

    “It used to be that you would give your essay to your professor, they would grade it, it would come back to you,” Ziebel said. “If the essay is now being fed into a machine that is being used for 15 other purposes – what does that mean? And what rights do you have over the data you create as a student?“

    AI in student loans and financial aid

    On the financial assistance side, Ziebel pointed to fintech and alternative underwriting. AI can support new loan products (including no-co-signer personal loans) but the models rely on historical data that may carry biases.

    Robert added the concern of the timing: With new federal student loan borrowing limits and a larger role for private lending, more decisions about who will qualify and at what rates will be driven through AI models trained on data that may no longer reflect current labor-market realities. He pointed to today’s rising computer science unemployment as an example of how quickly the assumptions behind a model can become outdated.

    AI in the classroom and what are students paying for?

    Some of the toughest questions come from inside the classroom. Ziebel said several vendors at the conference were marketing AI tools to professors for grading exams, papers and presentations. This raised a big question for them as to what products the students were buying.

    “Is your professor designing your classes? Are your professors grading your papers and commenting on the work you’re doing? Or are you simply getting some AI software?“Zibel said.”What are you paying for?“

    What should students and families do now

    With a few months left until the next admissions cycle, Ziebel’s advice was straightforward: Ask the schools who are evaluating your application, and expect the schools to actually answer that question. Don’t outsource the college-fit decision to ChatGPIT – where to go to school is a financial, lifestyle, and personal-fit question, not a prompt. And on the school side, don’t let AI be the decision maker on either side of the equation.

    admissions Bill Dan data Defense rights student Ziebel
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