Reasons for User Concerns About AI in Education

AI isn’t just the future, it’s now mandated to be part of the curriculum. A new executive order, "Advancing Artificial Intelligence Education for American Youth", is pushing to embed AI education across all levels of learning While preparing students for an AI-driven future is necessary, I'm deeply concerned about implementation without careful consideration. History offers cautionary tales. From "No Child Left Behind" to standardized testing mandates, we've seen educational reforms create unintended consequences. Now, we risk prioritizing AI fluency over human development which can reshape curriculum around technology rather than the learner. As both a tech advocate and parent, I'm troubled by the nuanced questions being overlooked: 1️⃣ Data Sovereignty: Every interaction our children have with AI systems creates valuable data. Who owns it? How is it protected? Are our classrooms becoming extraction grounds for tech companies building proprietary systems? 2️⃣ Truth Discernment: AI makes confident assertions regardless of accuracy. We're asking children to develop critical thinking skills while simultaneously introducing tools that blur the line between fact and fabrication. 3️⃣ Human Intelligence: Teaching isn't merely content delivery – it's relationship-building, emotional intelligence, and personalized guidance. What irreplaceable human elements are we sacrificing at the altar of technological efficiency? 4️⃣ Power Dynamics: Private corporations develop most educational AI systems with profit motives and proprietary algorithms. Are we embedding corporate interests into the fabric of public education? The contradiction is striking: an administration advocating for local educational control (ala DOE dismantling) while imposing sweeping federal directives on AI integration. Technology can transform education positively, but implementation requires deliberate care, not rushed mandates. This is just the beginning of many conversations we need to be having. While the answers aren't crystal clear today, I'm committed to navigating this landscape alongside you. Through Mother AI, I'm dedicated to keeping parents informed and empowered to engage meaningfully with school systems and local policymakers about AI in education. In tomorrow's newsletter (link to join in comments), I'll be diving deeper into practical ways parents can start these conversations with educators and administrators. The questions we ask today will determine whether technology amplifies human potential or diminishes it. What, if any, conversations are happening in your child's school about AI implementation? What are you most concerned about when it comes to AI and its impact on your child's education? #FutureOfEducation #AIEthics #DigitalChildhood #MotherAI #ShePowersAI

🎓 Bullshit Universities: The Future of Automated Education This sharp and provocative essay by Sparrow and Flenady challenges the utopian narratives surrounding AI in higher education. The authors argue that AI outputs—lacking truth, meaning, and moral accountability—are unfit for replacing human teaching. While automation promises efficiency and access, it risks hollowing out the essence of education: learning by example, dialogue, and critical inquiry. To defend education’s social and transformative role, universities must reinvest in people, not platforms. ⚖️ 5 Key Trends, Trade-offs, and Contradictions: 1. 🚀 EdTech Hype vs. Pedagogical Reality History shows that "assistance" is often the first step toward labor displacement. Once AI designs lessons and grades essays, the rationale for keeping educators weakens. The tech utopia may actually be a cost-cutting dystopia. 2. 📦 Content Delivery vs. Human Formation AI excels at packaging and distributing content, but real education involves identity, ethics, and intellectual rigor. Teachers inspire, challenge, and mentor—not just instruct. 3. 🌍 Access vs. Quality AI can extend access to learning, especially in underserved areas—but what kind of learning? If AI replaces meaningful teacher interaction, we risk offering a second-class education to marginalized groups. 4. 🤖 Automation Bias Once AI systems become routine, users tend to trust them too much—even when they’re wrong. Teachers may stop reading student work critically, while still being held responsible for errors. Over-reliance on machines erodes professional judgment. 5. 🧠 Learning that vs. Learning how Knowing facts (“that”) is not enough—students must develop skills and judgment (“how”). Writing, critical thinking, and discussion require human modeling and feedback. 🛠️ 5 Policy Recommendations 1. 🧑🏫 Reinvest in Human Teachers: Fund smaller classes with passionate, expert human teachers. Teachers are not content deliverers—they are mentors, models, and guides. Smaller classes mean more dialogue, personalized feedback, and intellectual engagement. 2. 🧰 Use AI Only in Dedicated Skills Units: Let students learn how to use AI tools responsibly—just like learning to use a library or a bibliography. But don’t let AI replace disciplinary teaching or feedback. 3. 📋 Protect Assessment Integrity: Avoid AI-based grading; protect integrity through human assessment. AI lacks the judgment, context, and accountability that grading demands. 4. 🔁 Prioritize Human Mentorship and Feedback: Mentorship builds trust, motivation, and deep thinking. 5. 🎓 Resist the Temptation to Mass-Produce Education: Incentivize deep learning, not scalable content delivery platforms. https://lnkd.in/eE9Vvni3

The rush to implement AI into schools has hit a fever pitch. Much of this urgency is fueled by fears that taking a slow, contemplative approach to AI will “harm the most vulnerable students” who will fail to learn the AI skills and literacies needed to avoid being “left behind” and “further marginalized.” There is also hope that these tools will “level the playing field” and bring about educational excellence and opportunity for all students. This is because these tools are often positioned as less biased and more efficient than human educators, and thus better at supporting the diverse needs of our diverse student body. While I appreciate these altruistic assumptions, and share the goal of advancing educational opportunity and excellence for all students, the taken-for-granted assumptions about AI’s inherent ability to “revolutionize education,” and "level the playing field" for all students needs to be more thoroughly interrogated. In my recent keynote for the Berkeley Leadership Programs I unpacked the past decade or so of transdisciplinary research on AI in education, and showcase some of the disparate harms these tools have levied against some of our most vulnerable students - the very students we are told these tools will inherently support. Unfortunately, in many ways, AI is quietly automating educational inequity, exacerbating the school-to-prison nexus, further reinforcing tracking and within-school segregation, and creating “synthetic” gaps in achievement and opportunity (see attached slides for examples) It is my hope that we become bold enough to slow down, ask questions, and investigate these tools before adopting them at scale. We can’t keep repeating Big Tech’s approach of “move fast and break things” when the “things” that are at risk of being broken are our students, our educators, and our communities. If you’re interested in watching the full keynote, you can access it here: https://lnkd.in/gGjsJWM6

While most industries are embracing artificial intelligence, citing profit and efficiency, the tech industry is pushing AI into education under the guise of ‘inevitability’. But the focus on its potential benefits for academia eclipses the pressing (and often invisible) risks that AI poses to children – including the decline of critical thinking, the inability to connect with other humans, and even addiction. With the use of AI becoming more ubiquitous by the day, we must ask ourselves: can our education systems adequately protect children from the potential harms of AI? In this episode, I'm joined once again by philosopher of education Zak Stein to delve into the far-reaching implications of technology – especially artificial intelligence – on the future of education. Together, we examine the risks of over-reliance on AI for the development of young minds, as well as the broader impact on society and some of the biggest existential risks. Zak explores the ethical challenges of adopting AI into educational systems, emphasizing the enduring value of traditional skills and the need for a balanced approach to integrating technology with human values (not just the values of tech companies). What steps are available to us today – from interface design to regulation of access – to limit the negative effects of Artificial Intelligence on children? How can parents and educators keep alive the pillars of independent thinking and foundational learning as AI threatens them? Ultimately, is there a world where Artificial Intelligence could become a tool to amplify human connection and socialization – or might it replace them entirely? Watch/listen: https://lnkd.in/dfjdiV39