1. Introduction
Artificial Intelligence has revolutionized educational practice, introducing tools that analyze data, assess learners, and automate instruction. From adaptive learning platforms to large language models like ChatGPT, AI technologies promise to transform how knowledge is created and transmitted (Luckin et al., 2016). However, this transformation brings critical challenges. As AI systems become increasingly capable, questions arise about whether they will eventually replace teachers or redefine human learning (Seldon & Abidoye, 2018).
Williamson and Hogan (2020), in their seminal work on the commercialisation and privatisation of AI in education, caution that such technologies must function as partners in teaching and learning—not as replacements for educators. Their perspective aligns with the growing discourse on responsible AI use, emphasizing the preservation of pedagogical values, academic integrity, and human creativity within an AI-driven educational landscape.
2. The Argument of Williamson and Hogan (2020)
2.1 AI as a Partner, Not a Substitute
Williamson and Hogan (2020) contend that AI’s role in education should be assistive and collaborative, not substitutive. They argue that AI systems are valuable when they complement teachers’ professional expertise—helping them interpret learning data, customize instruction, and engage students more effectively. However, these systems should never assume the full pedagogical role of the teacher. The authors highlight that education is not merely about information transfer but involves complex social, ethical, and emotional interactions that machines cannot replicate.
Their assertion that AI must remain “a partner in pedagogy rather than its replacement” stems from concerns about depersonalization, loss of teacher agency, and the commodification of learning (Williamson & Hogan, 2020). The teacher, therefore, remains central to the learning process as both a moral guide and an intellectual mentor.
2.2 The Risks of Replacing Human Pedagogy
Williamson and Hogan (2020) emphasize that substituting human educators with AI-driven systems can lead to the mechanization of education. Automated grading, predictive analytics, and algorithmic learning pathways risk prioritizing efficiency over empathy, and metrics over meaning. This shift undermines the relational and dialogical dimensions of teaching that nurture creativity, moral reasoning, and emotional growth (Holmes et al., 2021).
Moreover, the authors warn that the commercial interests driving AI development may lead to data exploitation and educational inequality. If unregulated, AI could reinforce existing biases and reduce learners to data profiles, eroding the democratic and humanistic values of education (Williamson & Hogan, 2020).
3. Pedagogical Implications of the Partnership Model
3.1 Preserving Human-Centered Education
In line with Williamson and Hogan’s argument, a pedagogical partnership model requires that AI enhances—not replaces—the teacher’s role. Teachers interpret AI outputs within social and emotional contexts, exercising judgment and empathy. Human educators bring moral insight, contextual understanding, and creative flexibility—qualities beyond the scope of algorithmic systems (Boud & Molloy, 2013). This aligns with Kasneci et al. (2023), who emphasize human oversight as essential for responsible AI integration.
3.2 Ethical Governance and Teacher Agency
Williamson and Hogan (2020) argue for stronger governance structures to regulate AI’s use in education. Teachers must retain control over pedagogical decisions and data interpretation. Ethical frameworks should ensure transparency, accountability, and fairness in AI applications. As Cotton et al. (2023) note, maintaining integrity in an AI-rich environment requires deliberate design of assessment and learning systems that value authenticity over automation.
3.3 Collaborative Pedagogy and AI Literacy
A balanced partnership between humans and AI demands AI literacy—the ability of educators and students to understand, critique, and ethically engage with AI systems (Kasneci et al., 2023). Rather than fearing replacement, teachers should be empowered to use AI creatively to enhance feedback, adapt teaching materials, and analyze learning outcomes. Such collaboration redefines pedagogy as a shared process between human intelligence and machine assistance.
4. Discussion
Williamson and Hogan’s (2020) vision of AI as a pedagogical partner rather than a replacement offers a balanced response to the growing digitalization of education. Their argument situates technology within the broader moral and social purposes of education. While AI can optimize efficiency and provide individualized learning experiences, it lacks the human capacity for empathy, ethical judgment, and relational understanding.
If AI were to replace teachers, education could devolve into a transactional process devoid of personal meaning. Conversely, when AI functions as a partner, it amplifies teachers’ capacities while preserving the human core of pedagogy. This partnership aligns with what Holmes et al. (2021) describe as “human-machine symbiosis in education,” where technology serves as a cognitive scaffold that supports—not supplants—human learning.
5. Conclusion
Williamson and Hogan’s (2020) argument that AI must remain “a partner in pedagogy rather than its replacement” provides a vital framework for ethical and sustainable educational innovation. Their emphasis on teacher agency, human oversight, and ethical regulation underscores the importance of maintaining human-centered learning. In the age of generative AI, pedagogy must balance technological advancement with human wisdom and compassion. AI’s proper role lies in collaboration—supporting educators, enriching student experiences, and preserving the moral and intellectual essence of education.
References
- Boud, D., & Molloy, E. (2013). Feedback in higher and professional education: Understanding it and doing it well. Routledge.
- Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 60(2), 205–216. https://doi.org/10.1080/14703297.2023.2190148
- Holmes, W., Bialik, M., & Fadel, C. (2021). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Center for Curriculum Redesign.
- Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
- Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.
- Seldon, A., & Abidoye, O. (2018). The Fourth Education Revolution: Will Artificial Intelligence Liberate or Infantilise Humanity? University of Buckingham Press.
- Williamson, B., & Hogan, A. (2020). Commercialisation and privatisation in/of education in the context of AI. OECD Education Working Papers, No. 218. OECD Publishing. https://doi.org/10.1787/efb68af7-en
- Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0
