The Future of Decolonial Education: Can Humanoid AI-Robots Transform Our Classrooms?
In the push toward decolonial education, teachers play a crucial role in challenging the current colonial system and reshaping their teaching practices to center the worldviews of marginalized and oppressed communities. To achieve this, teachers need years of unlearning the colonial mindset embedded in mainstream education and relearning decolonial practices. This process requires teachers to continue their commitment to decolonial approaches in the classroom, which includes adopting pedagogies that emphasize cultural inclusivity, mutual respect, and social justice. However, the challenges of reorienting an entire educational system are immense and may demand new, innovative solutions to address biases and gaps in student experiences.
Psychological research highlights that implicit bias—automatic, subconscious attitudes that affect perceptions and decisions—exists in everyone and has a profound impact on students from disadvantaged backgrounds. For instance, studies have shown that teachers may unconsciously lower expectations for students of color, inadvertently diminishing their academic achievements and limiting their potential. Similarly, Black students in the United States and Indigenous students in Canada are more likely to face harsher discipline than their white peers, which can negatively affect their self-esteem, reduce their engagement in school, and contribute to higher dropout rates. Unfortunately, a large portion of teachers in Western countries are white, middle-class women, who may lack the lived experience or cultural background to relate fully to the diverse experiences of their students. This lack of diversity among teachers can, over time, reinforce a hidden curriculum—implicit lessons that shape students' understanding of their place in society. Boys, too, are increasingly affected by these implicit biases, as the gender gap in education grows with more women entering universities while young men, facing their own struggles in identity and educational attainment, are increasingly marginalized.
One potential solution to these biases could be found in the application of AI-robot teachers. With the right programming and ethical oversight, AI-robots could eliminate the implicit biases and detrimental effects of hidden curricula. AI-robots could be programmed to treat each student equitably, celebrating diverse cultural backgrounds and offering balanced representations of different worldviews without personal or systemic bias. For instance, AI-robots could incorporate Indigenous and marginalized perspectives into science or history lessons, ensuring that students learn a pluralistic understanding of knowledge rather than the dominant, often Eurocentric perspective.
The notion of AI-robots in classrooms might sound futuristic, but it holds transformative potential. Indigenous scholars and Elders have shared that healing from colonialism may take seven generations, an acknowledgment of the slow, generational process that humans need to change ingrained perspectives and heal from historical trauma. AI-robots, however, could bypass this generational healing process. With a simple software update, AI-robots could adopt new perspectives, methodologies, and values instantly, eliminating the need for decades of unlearning and relearning. While this instant change may challenge one of the core principles of Indigenous teachings—reciprocity, or the concept that growth and understanding are best achieved through meaningful relationships and time—it may be argued that such a radical transformation is what public education needs to address the biases and inequities that continue to persist and be reproduced.
Even with the formal end of oppressive systems such as Residential Schools and greater emphasis on critical theories that examine power imbalances, the pace of change in education remains slow. Despite increased awareness and intention, systemic change is proving to be challenging to implement due to societal resistance and deeply rooted biases. AI-robots, with their capacity for immediate updates and vast data processing capabilities, could support a more equitable and inclusive education system. Imagine an AI-robot designed to relieve teacher burnout and reduce stress by managing administrative tasks, grading, and lesson planning, so the human teacher could spend time meaningfully building relationships with all students in smaller groups. Consider an AI-robot programmed to address teacher shortages and high attrition rates, by providing consistent teaching and mentorship to larger groups of students without the fatigue and stress that human teachers often experience. These capabilities would allow human teachers to focus on students, nurturing creativity, and guiding students’ personal growth, while AI-robots handle tasks that lead to burnout.
AI-robots could also have a transformative effect on learning outcomes, particularly for disadvantaged students. With access to advanced data analytics, AI-robots could monitor student progress in real time and provide individualized learning experiences, adjusting teaching methods to cater to each student's unique learning style and needs. Imagine an AI-robot that could instantly recognize when a student is struggling with a concept and provide targeted support to help them catch up. Each year with a new grade, teachers and students have to learn the established patterns in each other, which is a waste of time and resources. If all past interactions and behaviour patterns of each student could be sent to the next grade's AI-robot teacher, it would be more efficient when addressing issues when they arise again. Such uniform technology could offer a level of personalized instruction that is currently challenging to achieve in overcrowded classrooms and could bridge achievement gaps that persist among marginalized groups.
The concept of AI-robots in classrooms may feel controversial, particularly within the teaching profession, where teachers’ unions and professional organizations can be seen as rigid structures that prioritize job security and stability over rapid change. However, it is essential to reflect on how this profession can evolve to better serve all students. AI-robots have the potential to reshape our educational systems, reduce teacher burnout, and empower human teachers to focus on fostering the personal connections and creative problem-solving that students need. The time may have come to consider the ways in which AI-robots can address the persistent inequities in education and imagine a future where the challenges of bias, burnout, and stagnation are no longer obstacles to student learning and educational progress.
By rethinking the possibilities of AI in education, we might discover pathways to a more inclusive, accessible, and decolonized education system. AI-robots could very well be the key to a more equitable and effective system of learning—one that nurtures students' unique backgrounds and perspectives while breaking down the barriers that hold so many back. This bold new vision challenges us to rethink our assumptions about education and to explore what might be possible if we invite AI into our classrooms. The time to reflect on these possibilities is now.