“My dream is a version of the posthuman that embraces the possibilities of information technologies without being seduced by fantasies of unlimited power and disembodied immortality, that recognizes and celebrates finitude as a condition of human being, and that understands human life is embedded in a material world of great complexity, one on which we depend for our continued survival.”
WHILE THE MACHINE LEARNS: A MANIFESTO FOR AI EDUCATION
By International Communications Studies at the University of Nottingham Malaysia, Class of 2026Preamble: Why We are Writing This
We are writing this because no one else will.
We are writing this because the world has become too complex for the systems we inherited. Climate unraveling. Democracies fracturing. Truth itself is under siege. We need to understand this moment more urgently than any other generation.
As has been proven by the endless headlines about “the crisis of higher education”, the university cannot catch up.
The challenge is further compounded by AI: Built by investment, designed to scale knowledge, we must ensure it serves people, not just profit.
But efficiency has never been neutral. AI's power must be directed responsibly, not assumed benign. Deployed without sufficient thought or oversight, we call for shared accountability.
The technology can neither wait nor embody our ethics. It is being deployed now, in labor, war and countless other theaters we never see, by actors who answer to no one. If we do not understand its logic, limits and power, we will be its objects, not its critics.
We do not condemn the university. We call it back to what it promised.
This manifesto is our challenge.
We will not reject AI. We will not worship it. We will use it with intention, not deference. We claim the right to shape how AI enters our learning. We assert that education belongs to us, not to algorithms.
Principles: Our Non-Negotiables
Let these principles be the measure, not of what the machine can do, but what we refuse to lose.
1
AI education should be critical, not merely instrumental. It should teach how systems work, who builds them, and who they serve.
2
AI education should be transparent and accountable. It should expose training data, assumptions, and limits, and require explanation for outcomes. Teach it as a tool but test it as a system.
3
AI education should be person-centered and participatory. It should place students as co-creators of knowledge, not passive users of tools. Build skills, but defend doubt.
4
AI education must believe that genuine creativity originates from human inspiration, which is rooted in our lived experience and flawed perception of the real world.
5
While AI could be used to understand context, meaning must be grounded in lived reality.
6
No matter AI’s efficiency, understanding must be built through slow, situated exploration across human and nonhuman worlds.
7
We refuse to let AI's convincing surfaces replace the irreducible depth of human encounter. Our learning shall defend what cannot be modelled, computed, or owned.
8
The machine may be able to imitate a character, but it can never be more than a caricature of a human being.
9
AI can generate stories but only consciousness can live them.
10
AI is not reasoning in human terms. It needs to be tested, not trusted.
11
Vulnerability cannot be computed, optimized, or outsourced, and must be lived beyond the machine.
12
Accountability cannot be outsourced. The machine does not answer for wrong, we do.
13
No algorithm holds the final word. We will seek truth with our own doubt, our own error, our own restless wondering. The machine may answer; only we can question.
14
We demand a return to the soul, not as superstition, but as the name for the profundities the machine cannot simulate.
15
The more you let it decide, the less of you remains.
Policies expire.
Principles endure.
We set them here so that when AI shifts, and it will, our judgment does not.