As instructional staff, many of us are exploring cutting-edge ways to integrate AI tools like custom chatbots and generative AI frameworks into our courses. These innovations can enhance efficiency, creativity, and engagement—but they also come with risks. Recent research from Microsoft and Carnegie Mellon highlights a troubling trend: over-reliance on AI can erode critical thinking skills, especially when students trust outputs without scrutiny.

So, how do we strike the right balance? Here are some strategies we’ve been discussing:

• AI as a Catalyst for Inquiry: Design assignments where students must critique or improve AI-generated outputs.
• Transparency in Use: Require students to disclose how they’ve used AI and evaluate its limitations.
• Socratic Prompts: Use AI to simulate debates or flawed arguments that challenge students to think critically.

At our college, we’re piloting frameworks that combine these approaches while developing policies to guide responsible AI use. But this is just the beginning—we need collective insights!

💡 How are you using AI in your teaching? What strategies are you employing to ensure it enhances, rather than replaces, critical thinking?

Let’s collaborate and share ideas below! 👇 #AIinHigherEd #CriticalThinking

I thought I’d share some insights from a recent project I’ve been working on. It’s an interactive assignment designed to give students a taste of screening interviews, with a little help from AI. Here’s the setup:

• Students pick a job from a list (or choose their own), and the AI generates a job description.
• The AI conducts a quick three-question screening interview and provides feedback on the student’s performance.
• It even explains whether they’d be selected for the next interview and why.

I decided to test it out by choosing the role of a marketing specialist. The AI gave me a decent job description and asked me to describe a successful marketing campaign I’d worked on. I gave a vague response about a social media campaign, and to my surprise, the AI started coaching me through the process, asking for more details about the goals, strategies, and tactics. Even when I pushed back with minimal information, the AI continued to guide me, breaking down the question further and helping me formulate a better answer.

This level of interaction and coaching was not something I had initially intended, but it turned out to be a fascinating aspect of the exercise. Overall, this AI-driven interactive assignment has shown potential in providing students with valuable practice and feedback in a simulated interview setting. I’m excited to see how this approach can further enhance student learning and development.

Check out the video below to see some of the results of the AI conversation:

Watch the video

Stay tuned for more updates and insights.

“Whole communities suddenly fix their minds upon one object, and go mad in its pursuit.”
— Charles Mackay, Extraordinary Popular Delusions and the Madness of Crowds (1841)

This quote—shared in Gary Marcus’s critique of today’s AI frenzy—makes me want to read Mackay’s 1841 study of mass hysteria. Though I haven’t yet explored his analysis of tulip mania or witch trials, its relevance to our AI moment is unmistakable:

Three Echoes Across Centuries

• Gold Rushes: From Dutch tulip bulbs to AI startups, speculative fever repeats.
• Herd Dynamics: Social media amplifies today’s AI debates, mirroring Mackay’s “madness in herds.”
• Ethical Alchemy: Visionaries promise transformation; critics warn of unintended consequences.

Mackay’s work whispers: Question hype, seek nuance, and remember—we’ve danced this dance before.

#AIHype #CollectiveMadness #HistoryRepeats

A nudge from Gary Marcus’s writing to revisit old wisdom. Explore more at Humanovate.com.

When I think about the future of education, I find myself both curious and cautious. Artificial intelligence (AI) is being heralded as a transformative force across industries, and education is no exception. But is it truly the “killer app” that justifies the billions being poured into AI development? Or are we still searching for the breakthrough that will make all this investment feel inevitable?

One intriguing possibility lies in AI tutors. These systems promise to personalize learning, adapt to individual needs, and scale education in ways we’ve never seen before. But as I reflect on this potential, I can’t help but wonder: Is this the future of higher education—or just one possible path forward?

The Promise of AI in Education

AI tutors are designed to provide personalized learning experiences by analyzing student performance in real time and offering targeted support. Imagine a tutor that knows exactly where you’re struggling and can guide you through complex concepts at your own pace—available 24/7.

In higher education, this could mean:

• Personalized Support: AI systems could adapt to each student’s learning style, providing tailored feedback and resources.
• Scalability: Unlike human instructors, AI tutors can assist thousands of students simultaneously without compromising quality.
• Accessibility: Students from diverse backgrounds could benefit from on-demand support, breaking down barriers to education.

Institutions like Arizona State University (ASU) are already experimenting with AI tools to enhance learning outcomes. For example, ASU uses adaptive learning platforms to provide personalized feedback while allowing faculty to focus on mentoring students through more complex challenges.

The Role of Educators in an AI-Driven Future

While the benefits of AI tutors are compelling, they also raise important questions about the role of educators. If routine tasks like grading or answering basic questions are handled by AI, instructors could focus more on mentoring and fostering critical thinking. However, this shift prompts deeper concerns:

• Will we lose the personal connection between teachers and students?
• Do we need as many educators as we did in the past?
• What are the skillsets that educators will need in the future?
• How do we ensure that educators remain central to the learning process?

AI should augment—not replace—the human elements of teaching. The best outcomes will likely come from collaboration between educators and AI, where technology handles repetitive tasks while teachers focus on creativity, empathy, and mentorship.

Challenges and Risks

As exciting as these possibilities are, they come with risks:

• The Human Element: Can AI truly replicate the inspiration and connection that great teachers bring to their students?
• Data Privacy: AI systems require vast amounts of personal data to function effectively. How do we protect this sensitive information?
• Over-Reliance: Could students become too dependent on AI tutors, potentially hindering their ability to develop self-directed learning skills?

These challenges aren’t just technical—they’re deeply human. As we integrate AI into education, we must tread carefully to ensure it enhances rather than diminishes the learning experience.

A Work in Progress

AI hasn’t yet delivered its “killer app” for education—but it might be getting closer. AI tutors represent one possible future for higher education: a future where technology empowers students and educators alike. But whether this vision becomes reality depends on how thoughtfully we navigate these changes.

For now, I remain curious—and cautious. We’re navigating uncharted waters in education. And while AI may help us map new paths forward, it’s up to us to ensure those paths remain deeply human.

This article was developed in partnership with AI as a collaborative tool for research and organization. Together, we are exploring an AI-augmented future—one where technology supports human creativity rather than replaces it.