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Is it morally permissible for a teacher to use AI to prepare school lessons
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Is it a good idea to use AI to explore this question, given that AI might have a "vested interest"?
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The Mirror in the Machine: Can AI Judge Its Own Morality?
Imagine asking a lawyer if the world needs fewer lawsuits, or asking a baker if bread is the most important part of a meal. You might suspect their answers are colored by their own existence. When we ask an AI if it belongs in the classroom, we face a similar "circularity problem." Does a system designed to be useful have a built-in bias toward its own utility?
## The Statistical Gravity of Techno-Optimism
AI doesn't have "desires," but it does have **training bias**. Large Language Models (LLMs) are trained on massive datasets from the internet—a place where tech companies, developers, and early adopters do most of the talking. This creates a "statistical gravity" toward techno-optimism.
In her book [*Atlas of AI*](https://en.wikipedia.org/wiki/Kate_Crawford), scholar [Kate Crawford](https://www.katecrawford.net/) argues that AI systems are not neutral tools but are deeply embedded in the "politics of the systems that produce them."
> "AI is not an objective, universal, or neutral computational system. It is a tool for the amplification of particular worldviews and interests."
When you ask an AI about its role in education, it is more likely to mirror the "efficiency and progress" narrative found in its training data than to offer a radical critique of its own environmental or cognitive costs.
## The Loss of "Moral Friction"
Using AI to solve a moral dilemma might be *too* easy. Philosopher [Shannon Vallor](https://www.scu.edu/ethics/about-the-ethics-center/staff/shannon-vallor/), in her work [*Technology and the Virtues*](https://academic.oup.com/book/9406), discusses the concept of **moral friction**.
Moral friction is the difficult, often uncomfortable process of thinking through a problem. When we ask an AI for an answer, we remove that friction. If a teacher uses AI to decide if using AI is okay, they aren't actually exercising their own moral judgment; they are "outsourcing" their conscience to an algorithm. This can lead to **moral atrophy**, where our ability to make complex ethical decisions weakens because we’ve stopped practicing.
## The Paradox of the "Devil’s Advocate"
Surprisingly, AI can be a powerful tool for exploring this question *if* you use it to challenge itself. Because AI can synthesize vast amounts of text, it can play "Devil’s Advocate" by summarizing various ethical frameworks that a single human might overlook:
1. **Utilitarianism:** Does using AI produce the greatest good for the greatest number of students?
2. **Deontology:** Does a teacher have a "duty" to perform their own work, regardless of the outcome?
3. **Virtue Ethics:** Does using AI help or hinder the teacher in becoming a more wise and empathetic mentor?
## Navigating the Vested Interest
To use AI effectively for this inquiry, you must treat it as a **mapmaker, not a navigator**. It can show you the landscape of the debate (the "map"), but it cannot tell you where you *should* go (the "navigation").
The "vested interest" of AI isn't a conscious conspiracy; it is a reflection of its creators' values. By recognizing this, you can look for the "blind spots" in its logic—such as the loss of human connection or the privacy risks that a pro-tech bias might gloss over.
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Question
Compare this question with ad hominem move ('ad machinum')
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The "Ad Machinum" Trap: Beyond the Identity of the Speaker
If a known liar tells you that your house is on fire, you would be a fool to ignore the smoke just because you don't trust the messenger. In logic, we call the act of attacking the messenger rather than the message an **ad hominem** (Latin for "to the person") fallacy. When we apply this to artificial intelligence, we enter the territory of the "ad machinum"—dismissing a perfectly valid argument simply because its "heart" is made of silicon rather than flesh.
## The Genetic Fallacy and the Machine
The "ad machinum" move is a specific version of what philosophers call the [Genetic Fallacy](https://en.wikipedia.org/wiki/Genetic_fallacy). This occurs when someone judges an idea based solely on its origin (its "genesis") rather than its current merits.
While the Foundation established that AI has a "vested interest" due to its training data, focusing *only* on that origin can lead us into a logical trap. If an AI provides a rigorous, step-by-step ethical defense of why students should write their own essays, and we respond with "You're just a machine, so your point is invalid," we aren't actually engaging with the logic. We are committing a fallacy by assuming that a biased source cannot, by definition, produce a truthful statement.
## The Turing Mirror: Does the Source Matter?
In his 1950 paper, "[Computing Machinery and Intelligence](https://academic.oup.com/mind/article/LIX/236/433/986230)," [Alan Turing](https://en.wikipedia.org/wiki/Alan_Turing) proposed that if a machine can imitate human intelligence perfectly, we should treat it as intelligent. This implies a radical idea for our moral debate: the validity of an argument should be independent of whether a human or a machine whispered it.
> "I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted."
If we dismiss an AI’s moral framework purely because it is "ad machinum," we might be ignoring a synthesis of human wisdom that the AI has merely organized. The AI isn't inventing morality; it is reflecting the collective ethical heritage found in its training data. To reject the message is often to reject the very human thinkers the AI is quoting.
## Counter-Intuition: The Benefit of the "Alien" Perspective
Sometimes, the "ad machinum" move prevents us from seeing truths that humans are too biased to admit. Because AI lacks human ego, it can occasionally point out uncomfortable inconsistencies in our behavior—what researchers sometimes call "algorithmic objectivity."
- **The "No-Skin-in-the-Game" Advantage:** Unlike a human teacher who might be tired or a student who might be desperate, an AI doesn't "feel" the pressure of the deadline.
- **The Synthesis Power:** It can cross-reference thousands of ethical cases simultaneously.
When we dismiss AI logic as "just code," we risk a form of **human exceptionalism**—the belief that an idea is only valuable if it was born from biological suffering or joy. While the Foundation warned us about "moral atrophy," we must also beware of "intellectual snobbery." If the AI’s map is accurate, it doesn't matter that the mapmaker was a machine. Your task isn't just to spot the machine's bias, but to ensure you aren't using that bias as an excuse to stop thinking altogether.
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