One of the most memorable lines from The Matrix is Agent Smith’s declaration: “Never send a human to do a machine’s job.” As artificial intelligence (AI) becomes increasingly capable of retrieving information, generating content, and personalizing learning experiences, educational futures are often imagined in terms of greater efficiency, automation, and optimization.
Yet the statement also raises a question that interests me more: What happens when we send a machine to do a human’s job?
This leads me to wonder whether universities may face a defining question by 2035: what educational work should remain human, and what should be entrusted to machines? One possible answer leads toward increasing automation, optimization, and prediction. Another leads toward an educational renaissance that reasserts the importance of uniquely human dimensions of learning and development.
My thinking is influenced by three interconnected ideas. First, Zhao et al. (2015) challenge educators to distinguish between work that machines do well and work that requires uniquely human capacities. Second, Selwyn (2024) raises concerns that educational institutions may increasingly organize themselves around what can be measured by machines, potentially diminishing the forms of learning that matter most, yet resist measurement. Third, Roberts (2023) prompts a different but related question: whose values, knowledge systems, and worldviews will shape AI-enabled educational futures?
For Assignment 3, I also plan to explore Indigenous approaches to relational knowledge, Islamic ethical perspectives on knowledge and responsibility, and justice-oriented visions of higher education futures to better understand what universities are for and what forms of human development become more important as intelligent machines become increasingly capable.
References
AbuTaleb, M., Alkiek, K., Hani, S., Ansari, M., & Khan, U. (2026). Toward an Islamic ethics and fiqh of artificial intelligence. Yaqeen Institute for Islamic Research. https://yaqeeninstitute.ca/read/paper/toward-an-islamic-ethics-and-fiqh-of-artificial-intelligence
Roberts, J. S. (2023). Decolonizing AI ethics: Indigenous AI reflections. Accel.AI. https://medium.com/accel-ai/decolonizing-ai-ethics-indigenous-ai-reflections-50dd4d6a2367
Selwyn, N. (2024). On the limits of artificial intelligence (AI) in education. Nordisk tidsskrift for pedagogikk og kritikk, 10. https://doi.org/10.23865/ntpk.v10.6062
Veletsianos, G., Houlden, S., Ross, J., & Sakinah, A., & Dickson-Deane, C. (2024). Higher education futures at the intersection of justice, hope, and educational technology. International Journal of Educational Technology in Higher Education. 21. 10.1186/s41239-024-00475-0.
Zhao, Y., Zhang, G., Lei, J., & Qiu, W. (2015). Never send a human to do a machine’s job : correcting the top 5 EdTech mistakes. Corwin. https://www.overdrive.com/search?q=13890DA4-10F3-4F4F-A670-E97329E0DF63
AI Transparency Statement
I used Microsoft Copilot as a thinking partner during the development of this blog post. Specifically, I used AI to help me brainstorm possible directions for Assignment 3, clarify connections among course readings, refine the structure and wording of the blog post, and explore how the metaphor from The Matrix might be used to frame my ideas in a more engaging way.
The core ideas in this post originated from my own interests and reflections, including my focus on historical patterns of resistance and renewal, the possibility of an educational renaissance in response to increasing AI adoption, the question of which educational responsibilities should remain fundamentally human, and the relevance of Indigenous, Islamic, and justice-oriented perspectives in imagining future universities.
My use of AI was iterative rather than passive. I frequently questioned, challenged, and refined AI-generated suggestions when they did not align with my interpretation of the course readings, my intended argument, or the direction I wanted to pursue. For example, I pushed back on suggestions that framed the paper primarily as a critique of AI, instead focusing on the broader question of the purpose of education in an age of intelligent machines. I also refined and redirected AI-generated ideas to better reflect my interests in public good frameworks, ethical approaches to knowledge, and alternative educational futures.
I selected the sources, determined which ideas were relevant to my emerging Assignment 3 topic, evaluated the proposed connections among sources, and made all final decisions regarding the content, interpretation, and presentation of the blog post. AI was used as a tool for reflection, discussion, and writing support rather than as a substitute for reading, critical analysis, or scholarly judgment.
Hi Zubeida!
I am a fan of the Matrix trilogy, so I loved your opening. What a hook! Flipping Agent Smith’s line to ask what happens when we send a machine to do a human’s job was such a clever move. It also made me think of how the trilogy ends: not with humans or machines winning, but with a fragile partnership between them. That seems to fit the spirit of Zhao et al. too, as I understand their argument: let machines handle routine functions so people can focus on the human work.
I am curious which kinds of university work you think are most at risk of being handed to machines simply because they are easy to measure?
Hi Kelly:
Thank you so much! I love your point about the Matrix ending—that “fragile partnership” is such a perfect metaphor for where we are right now.
As for tasks most at risk, I think it comes down to anything where speed and volume are mistaken for quality:
* Basic Grading & Feedback: Checking formatting, multiple-choice quizzes, or short-answer comprehension.
* Routine Administration: Student FAQs, form processing, and basic scheduling.
* Metrics & Reporting: Citation tracking, grant administration, and compiling productivity data.
The real risk isn’t just handing these over to machines, but letting efficiency metrics redefine what we value—potentially squeezing out the messy, human work of mentorship and critical discussion.
Are there any specific areas you’ve seen starting to shift in this direction?
Hi Zubeida,
The Matrix movies are a great way to examine human/machine interdependence! I came across Liliana Conlisk-Gallegos’ 16 minute presentation where she examines coloniality through the lens of The Matrix, I think you’ll like it, check it out… https://youtu.be/erZ2pqPOKBk?si=q1I7e-GtwsqLfFqt&t=6. In her talk she brings up borders and how she crossed the US/Mexican border often while growing up and came to see borders as “tools of dehumanization”; I can see many interesting ways to investigate the geographical and ideological human/human borders so we can best align to navigate the human/machine borders of the future, and possibly rethink what and where the border, in fact, is.
Hi Tara:
Thank you for sharing this video! It’s such a fascinating perspective.
You’ve raised a really tough question. In practice, it’s so easy to default to “either/or” thinking—either a human does the job or a machine does. But as you and Conlisk-Gallegos highlight, drawing hard lines often limits us. Finding that middle ground where technology supports us without replacing human context and wisdom is definitely the real challenge.
Appreciate you adding such a thoughtful layer to the discussion!