Who Is AI Actually For? What Mortimer Adler Would Ask the Tech Industry
Who Is AI Actually For? What Mortimer Adler Would Ask the Tech Industry
There is a question almost no one in the AI industry is asking, and it might be the most important one: Who is this for, and what kind of human life should it serve?
Not “What can it do?” Not “How fast can it run?” Not “How much revenue will it generate?” But rather — what kind of human life, human judgment, and human dignity should artificial intelligence actually serve?
Mortimer Adler, the philosopher and educator who spent decades insisting that great ideas belong to everyone, not just to elites, has been dead since 2001. But his thinking feels strangely urgent right now, because AI debate keeps getting stuck on technical questions when we really need moral ones.
SEE: What Is Actually Happening
Take a moment to look honestly at where AI is being deployed today.
Hiring platforms use algorithmic screening to eliminate candidates before a human ever reads their name. Predictive policing tools rank neighborhoods — and by extension, people — by calculated risk scores. Students outsource essays to large language models and call it research. Social media feeds are curated by systems optimized not for truth or connection but for engagement, which often means outrage. Surveillance cameras equipped with facial recognition track people in public spaces without their knowledge or consent.
At the same time, AI is doing genuinely remarkable things. It is helping doctors catch cancers earlier. It is giving people with disabilities new ways to communicate. It is making legal and educational resources available to people who could never afford a lawyer or a private tutor.
The technology itself is not the problem. The problem is that we are deploying it without asking the right questions first: What should it serve, and what should it never override? We are asking, can we, and we are measuring success almost entirely by speed, cost, and efficiency — as if those were the only values that matter.
There are other costs that rarely appear in the spreadsheet: the environmental toll of the massive data centers required to run these models, the privacy of people whose information was scraped to train them, and the subtle but real erosion of human judgment when we hand our thinking to a machine.
JUDGE: What Mortimer Adler Would Say About All This
Adler’s life work was built on a single stubborn conviction: human beings are different in kind, not just in degree, from everything else. That distinction is the source of moral status. It is what makes a person a person and not a product.
His 1967 book The Difference of Man and the Difference It Makes was written to push back against reductionist accounts of human nature — the idea that we are nothing more than complicated mechanisms. That argument is even more pressing today, when AI systems can produce fluent prose, generate realistic images, and hold conversations that feel almost human. When machines can imitate the outputs of intelligence, we are tempted to forget that imitation is not the same as thought.
For AI governance, this matters enormously. If we treat the ability to process language or recognize patterns as equivalent to human understanding, we will end up treating human beings as interchangeable with machines — or, worse, valuing people only by what they can efficiently produce. Adler gives us language to resist that: Personhood, he insists, is prior to efficiency.
His educational philosophy deepens the concern. Adler believed the purpose of education was to cultivate the powers of understanding, reasoning, and dialogue — the distinctively human capacities that allow people to think for themselves, question assumptions, and engage seriously with ideas. Learning, for him, was active and communal, not passive and solitary. It required real conversation, genuine disagreement, and the willingness to change your mind.
If that is right, then an AI system that does your thinking for you is not an educational tool. It is an obstacle to education. It may produce something that looks like learning while quietly undermining the real thing.
From an Adlerian perspective, the current moral risks of AI are not side effects to be managed after the fact. They are failures of governance — failures to protect real persons and real communities from real harm. When AI amplifies bias, it harms people who are already vulnerable. When it generates fabricated content with the same fluency as true content, it erodes the shared basis of public discourse. And when it is used for manipulative targeting or covert surveillance, it degrades the freedom and dignity that make a human community possible.
None of this is inevitable. But none of it will be prevented by technical fixes alone. It requires moral judgment, which is precisely what Adler spent his career insisting could not be outsourced.
ACT: What Good Governance Actually Looks Like
Adler’s framework suggests not just a critique but a direction. Here are five principles worth fighting for:
1. Keep humans responsible for high-stakes decisions. AI can inform, flag, and assist, but a human being must be accountable for decisions that affect other people’s lives — employment, housing, healthcare, criminal justice. Automating those decisions is not efficient. It is the evasion of moral responsibility.
2. Prohibit or tightly restrict uses that degrade dignity. Blanket surveillance, manipulative behavioral targeting, and automated systems that sort people by worth or risk should face the highest bar of scrutiny. Some uses may need to be prohibited outright. Others require strict oversight, transparency about how they work, and meaningful recourse for people they affect.
3. Require explainability, auditability, and bias testing. If an institution cannot explain why its AI system made a particular decision, that system should not be making that decision. Regular bias audits should be required, not optional, and the results should be public.
4. Treat AI outputs as provisional until verified by human reason. This is Adler’s educational principle applied directly. AI can generate a first draft, surface a pattern, or summarize a body of evidence — but a human being must interpret, verify, and take responsibility for what gets used. The output of a machine is not the same as the judgment of a person.
5. Build AI literacy that teaches people to question, not just consume. Schools, universities, churches, civic organizations, and workplaces all have a role here. The goal is not to make people afraid of AI, or to pretend it does not exist, but to form people who know how to engage it critically — who can ask whether a source is reliable, whether an output is accurate, and whether a use is just.
In Adler’s spirit, the governing thesis is this: AI should not be governed by what it can imitate, but by whether it supports the full development of human persons in truth, freedom, and moral responsibility.
That is not a technical standard. It is a human one. And it is the standard we most urgently need.
Questions for Reflection and Discussion
When you use AI tools in your daily life — for work, school, or personal tasks — are you using them to deepen your own thinking, or to replace it? How can you tell the difference?
Adler argues that human dignity is grounded in what is distinctively human, not in measurable productivity or intelligence. How does that principle challenge the way AI is currently being used in hiring, healthcare, or education?
The See-Judge-Act method asks us to look honestly at reality before making moral judgments. What aspects of AI’s current impact do you think are being ignored or underreported in public conversation?
Who in your community is most vulnerable to harms from AI — from algorithmic bias, surveillance, or the erosion of human judgment in high-stakes decisions? What would it look like to center their experience in AI policy?
If Adler is right that real education requires active inquiry, dialogue, and the willingness to change your mind, what does that mean for how AI should — and should not — be used in classrooms?
What is one concrete thing you, your institution, or your community could do to ensure AI is serving human flourishing rather than replacing it?