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Join us for a candid debate between two colleagues who view the future of AI in education through very different lenses. We are joined by Dr. Jason Margolis, an AI skeptic who worries about the atrophy of critical thinking, and Dr. Nicole Schilling, an AI optimist who sees these tools as essential scaffolds for complex problem-solving.
Together, they model the concept of "Critical Friends," engaging in respectful but challenging dialogue on a polarizing topic. We dive deep into the ethics of the "8-minute dissertation," the tension between efficiency and the learning process, and why we might need flexible guidelines rather than rigid policies in this rapidly changing landscape. Whether you are an educator, a leader, or just someone trying to figure out where the human ends and the machine begins, this conversation offers a roadmap for navigating the grey areas of innovation.
Key Discussion Points:
Skeptic vs. Optimist: Jason’s concern about "outsourcing our brains" versus Nicole’s vision of AI as a partner in social constructionism.
The "8-Minute Dissertation": A critical look at what is lost when we prioritize the product (the degree) over the process (the struggle of learning).
Ethical AI Use: Examples of high-level use, such as training an AI model to act as a rigorous dissertation committee rather than writing the paper for you.
Bias and Power: Addressing the "racist undertones" in algorithms and questioning whose interests are really served by the rapid adoption of AI.
Policy vs. Guidelines: Why creating rigid policies for fast-moving tech is often futile, and the argument for developing ethical "guidelines" instead.
The Critical Friends Model: How to disagree productively and maintain professional relationships in an era of polarized viewpoints.
By Lydia KumarJoin us for a candid debate between two colleagues who view the future of AI in education through very different lenses. We are joined by Dr. Jason Margolis, an AI skeptic who worries about the atrophy of critical thinking, and Dr. Nicole Schilling, an AI optimist who sees these tools as essential scaffolds for complex problem-solving.
Together, they model the concept of "Critical Friends," engaging in respectful but challenging dialogue on a polarizing topic. We dive deep into the ethics of the "8-minute dissertation," the tension between efficiency and the learning process, and why we might need flexible guidelines rather than rigid policies in this rapidly changing landscape. Whether you are an educator, a leader, or just someone trying to figure out where the human ends and the machine begins, this conversation offers a roadmap for navigating the grey areas of innovation.
Key Discussion Points:
Skeptic vs. Optimist: Jason’s concern about "outsourcing our brains" versus Nicole’s vision of AI as a partner in social constructionism.
The "8-Minute Dissertation": A critical look at what is lost when we prioritize the product (the degree) over the process (the struggle of learning).
Ethical AI Use: Examples of high-level use, such as training an AI model to act as a rigorous dissertation committee rather than writing the paper for you.
Bias and Power: Addressing the "racist undertones" in algorithms and questioning whose interests are really served by the rapid adoption of AI.
Policy vs. Guidelines: Why creating rigid policies for fast-moving tech is often futile, and the argument for developing ethical "guidelines" instead.
The Critical Friends Model: How to disagree productively and maintain professional relationships in an era of polarized viewpoints.