AI in Education: Balancing Technology and Humanity to Create Equitable Learning

By: Ivory A. Toldson, Ph.D.

In my 2020 report to the National Science Foundation, "The Post-Reform Education Era: Mitigating Institutional Racism in Education at the Human-Technology Frontier," I explored how we can reimagine education by leveraging technology to address systemic inequities and improve outcomes for all students. Writing before the widespread emergence of large language models and generative AI, I focused on how technology could augment human performance in classrooms, workplaces, and beyond.

Now, as Bill Gates notes in his 2023 article "The Age of AI Has Begun," artificial intelligence is poised to fundamentally transform how people work, learn, and interact. The rapid advancement of AI tools since my report has only strengthened my conviction that we must rethink decision-making, task distribution, and how we prepare students for the jobs and skills of the future. But to make this technological revolution work for everyone—especially socially, culturally, and economically diverse (SCED) students—we need to approach it with equity, intentionality, and a commitment to democratizing knowledge.

How AI Can Enhance Teaching and Learning

AI-driven tools have the potential to transform classrooms by expanding cognition—essentially extending the mental processes of both students and teachers. For example, AI can take over repetitive tasks like grading or tracking student progress, freeing up teachers to focus on what really matters: building relationships, fostering creativity, and addressing the unique needs of their students. This is where the concept of humanistic distributed agency comes in. By using AI to democratize knowledge and distribute decision-making power, we can give teachers more autonomy to adapt their teaching to the needs of their students, rather than being bound by rigid, top-down standards. For students, AI can provide personalized learning experiences. Imagine a math program that not only identifies where a student is struggling but also adapts its teaching style to match how that student learns best. This kind of expanded cognition allows students to engage with material in ways that feel intuitive and empowering. It’s like having a tutor who knows you inside and out, but one that’s available to every student, regardless of their background.

Addressing Educational Opportunity Gaps Through Technology

The persistent disparities in educational outcomes between different student populations aren't simply "achievement gaps"—they're opportunity gaps that reflect systemic inequities in access to resources, quality instruction, and culturally responsive education. For Black, Latino, and low-income students in particular, these opportunity gaps manifest in mathematics education through limited access to advanced coursework, experienced teachers, and technology-enhanced learning experiences.

AI can help democratize educational opportunities by expanding access to high-quality, culturally responsive learning resources. For example, AI-powered platforms can provide personalized math instruction that connects to students' lived experiences and cultural frameworks, making the content more engaging and meaningful. This is crucial because traditional math curricula often fail to reflect diverse perspectives and ways of knowing, inadvertently creating barriers to engagement and mastery.

However, AI's role must go beyond just content delivery—it needs to be a tool for expanding opportunities and empowering both students and teachers. This is where distributed agency becomes essential. By involving educators, students, and communities in the design and implementation of AI tools, we can ensure these technologies enhance rather than replace human connections. The goal is to use AI to augment human cognition so we can prioritize relationship-building, cultural responsiveness, and individualized support in education.

For instance, teachers could use AI-generated insights not to label student "deficits," but to identify opportunities for growth and connection. This kind of data democratization allows educators to make informed, culturally responsive decisions that expand learning opportunities for all students. When we shift from a deficit-based view of "achievement gaps" to addressing systemic opportunity gaps, we can better leverage technology to create more equitable and inclusive learning environments.

Balancing Technology with Humanity

One thing I emphasize in my work is that technology should never replace the human connection that’s at the heart of education. Instead, it should enhance it. This is where humanism and humanistic agency come into play. AI can handle the technical aspects of teaching—like analyzing data or delivering personalized lessons—but it’s the teacher who brings empathy, encouragement, and a sense of belonging to the classroom. For example, while an AI might flag a student who’s struggling with fractions, it’s the teacher who can step in to provide emotional support and help that student build confidence.

We also need to think about how AI can help students develop not just academic skills but also social-emotional skills. This is part of what I call humanistic reprioritization—using technology to shift the focus away from rote memorization and toward deeper, more meaningful learning experiences. For example, AI could facilitate peer-to-peer learning by connecting students from different backgrounds, helping them build cross-cultural understanding and collaboration skills.

At the end of the day, the goal isn’t just to improve test scores—it’s to create an education system that works for everyone. This means addressing systemic barriers like institutional racism, which has long shaped educational outcomes in this country. AI can help by making data more transparent and accessible, allowing us to identify and address inequities at every level of the system. For example, data democratization can help schools track disparities in resources, teacher quality, and student outcomes, and then use that information to drive systemic change.

But we also need to be cautious. AI is only as good as the data it’s trained on, and if that data reflects existing biases, the technology will too. That’s why it’s so important to involve diverse voices in the development of AI tools and to ensure that these tools are trained on data that reflects the full spectrum of human experiences.

The Path Forward: From Revolution to Reality

The promise of AI in education isn't just about technological advancement—it's about human evolution. At this pivotal moment in history, we stand at the intersection of tremendous possibility and profound responsibility. The tools we're developing today will either perpetuate the inequities of the past or forge a new path toward genuine educational justice.

By leveraging the Human-Technology Frontier thoughtfully and intentionally, we can create something unprecedented: a learning ecosystem where technology amplifies our humanity rather than diminishing it. Where distributed agency empowers educators to be architects of change rather than custodians of the status quo. Where expanded cognition frees us to focus on what matters most—the human connections that make learning transformative.

But let us be clear: this is not a future that will unfold automatically. It must be built with purpose, with equity at its foundation, not as an afterthought. We must be willing to dismantle systems that have calcified inequality and replace them with frameworks that distribute power and opportunity more justly. The technology we deploy must serve our highest aspirations for education—not just efficiency, but empathy; not just achievement, but authentic learning; not just compliance, but creativity and critical thinking.

As we stand on the threshold of this new era, we face a choice. We can use AI to reinforce the walls that have long divided us, or we can use it to build bridges to a more equitable future. The revolution I envision isn't just about better tools or smarter systems—it's about fundamentally reimagining what education can be when we combine the power of technology with the wisdom of human experience.

This is our moment to be bold. To move beyond incremental reforms and embrace transformative change. To create an education system that doesn't just accommodate diversity but celebrates it, that doesn't just measure success but redefines it, that doesn't just prepare students for the future but empowers them to shape it.

Further Consideration

The concerns about AI making mistakes or experiencing "hallucinations" reflect valid but ultimately addressable technical challenges. As I discussed in my 2020 NSF report on education at the human-technology frontier, the key is to approach AI not as a replacement for human judgment, but as a tool for expanding human cognition and agency. When we frame AI this way, the goal isn't to achieve perfect AI performance, but rather to thoughtfully integrate AI capabilities with human wisdom and oversight.

Regarding privacy, bias and legal concerns - these are critical issues that require proactive attention. My research emphasizes the importance of distributed agency and democratized data. This means ensuring that AI systems are developed with input from diverse stakeholders, especially those who have been historically marginalized. We need robust frameworks for data governance that protect privacy while allowing beneficial uses of data to improve educational equity.

As for the question of superintelligent AI and potential conflicts with human interests - while this is an important long-term consideration, I believe our immediate focus should be on using current AI capabilities to address pressing inequities in education. The concept of "humanistic distributed agency" that I've developed emphasizes keeping humans at the center of decision-making while using AI to expand our cognitive capabilities and free up time for more meaningful human interaction.

Rather than trying to prevent the development of advanced AI, we should focus on building AI systems that align with human values and educational goals from the ground up. This means moving beyond simplistic notions of AI as either a threat or a savior and instead thinking carefully about how to integrate AI into educational systems in ways that enhance rather than diminish human agency and promote equity.

The key is maintaining what I call "humanistic reprioritization" - using AI to handle routine cognitive tasks while elevating the human elements of education that machines cannot replicate: empathy, cultural responsiveness, and meaningful human connection.

Dr. Ivory A. Toldson is a Professor of Counseling Psychology at Howard University, Chief of Research for Concentric Educational Solutions and Editor-in-Chief of The Journal of Negro Education. A nationally recognized advocate for educational equity and inclusion, Dr. Toldson is the bestselling author of "No BS (Bad Stats): Black People Need People Who Believe in Black People Enough Not to Believe Every Bad Thing They Hear About Black People." As the author of the groundbreaking 2020 report to the National Science Foundation, "The Post-Reform Education Era: Mitigating Institutional Racism in Education at the Human-Technology Frontier," Dr. Toldson explores innovative approaches to addressing systemic inequities through technology-enhanced education. His work focuses on reimagining education systems to better serve socially, culturally, and economically diverse (SCED) communities through humanistic distributed agency and expanded cognition. Previously appointed by President Barack Obama as Executive Director of the White House Initiative on Historically Black Colleges and Universities, Dr. Toldson is ranked among the nation's top education professors in Education Week's Edu-Scholar Public Influence Rankings. He is currently expanding his expertise in artificial intelligence by pursuing a certificate in Applied Generative AI for Digital Transformation at MIT.