The Moral Order: Humans, not AI, must retain their authority on ethical problems

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Jul 01, 2026

Gottfried Wilhelm Leibniz was, in many ways, the philosopher of the 21st century. He was pivotal to the invention of calculus, binary arithmetic, and statistics, and his work on organizing information logically undergirds the science that makes computers possible. He was able to see the world this way because he believed the universe was fundamentally rational, much as many modern physicists do when they contend that a single theory could describe all physical phenomena within one coherent framework.

For Leibniz, morality was a matter of debate only because we lacked a sufficiently developed ethical theory. Just as mathematical modeling of the solar system eliminated any need for debate about when eclipses would occur, a young Leibniz dreamed that one day ethicists would resolve their disputes by simply calculating the correct answer.1

It's an especially intriguing idea today. With modern computing, could we arrive at an ethical theory that solves every problem? If so, an app on your phone could tell you what to do, no matter the circumstances. Nobody would ever have to do wrong from a lack of knowledge again. 

Say an AI tool was released that made recommendations aligning with your moral intuition. You could type up a brief description of your problem and get a reliable report on what you should do. Would it be desirable to use such a system to determine your actions?

Though the prospect of moral certainty may seem appealing, ceding ethical decision-making to an algorithm would in reality be both practically dubious and philosophically pointless. Practically, it would put ethics in the hands of a machine that is capable of learning in only limited ways, and which is vulnerable to biases it can’t correct. Philosophically, we gain a lot from contemplating our actions through an ethical lens; the right outcome is only part of the value. If we give too much authority to the machines, we’ll lose our stake in ourselves.

References

  1. Rucker, R. (2013). An Incompleteness Theorem for the Natural World. In Irreducibility and Computational Equivalence : 10 Years After Wolfram’s A New Kind of Science (Vol. 2). https://doi.org/10.1007/978-3-642-35482-3_14
  2. William S. Hein & Co, Inc HeinOnline United Nations Law Collection. (2018). Algorithmic Bias and the Weaponization of Increasingly Autonomous Technologies. New York: United Nations,. http://proxy.library.nd.edu/login?url=https://heinonline.org/HOL/Page?handle=hein.unl/algbwpi0001&collection=unl
  3. Bonderud, D. (n.d.). AI decision-making: Where do businesses draw the line?. IBM.Com. Retrieved https://www.ibm.com/think/insights/ai-decision-making-where-do-businesses-draw-the-line
  4. Heidegger, M., & Schmidt, D. J. (2010). Being and time (; J. Stambaugh, Trans.). State University of New York Press ; Excelsior ; University Presses Marketing [distributor].
  5. MacIntyre, A. C. (1998). A short history of ethics : a history of moral philosophy from the Homeric age to the twentieth century (2nd ed). Routledge Classics. https://archive.org/details/shorthistoryofet0000maci

About the Author

Zakir Jamal

Zakir Jamal is a writer and researcher based in Montreal. He holds a BA in Philosophy from the University of Chicago and is completing his MA in English Literature at McGill. He is currently working on a novel about how we understand chance. In his spare time, he enjoys photography and cross-country skiing.

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