​When the Machines Ask What It Means to Be Human

There is a certain historical symmetry in watching a pope named Leo issue a major social encyclical about artificial intelligence.

In 1891, Pope Leo XIII confronted the moral dislocations of the industrial revolution in Rerum Novarum. Factories had transformed labor. Capital had become concentrated. Human beings were increasingly treated as interchangeable units within economic systems optimized for efficiency and profit. Leo’s intervention was not a rejection of modernity, but a moral insistence that economic life must remain accountable to human dignity.

Now, more than a century later, Pope Leo XIV has issued Magnifica Humanitas, applying the Church’s social teaching to a different technological revolution. The machinery is no longer steam-powered. The assembly line has become algorithmic. Yet the underlying question remains remarkably familiar: What becomes of the human person when increasingly powerful systems reorganize work, power, and even decision-making itself?

That is not merely a religious question. It is a civilizational one.

Artificial intelligence is often discussed in technical or commercial terms. Can it outperform human labor? Can it increase efficiency? Can it improve prediction, automate decision-making, or reduce costs? These are understandable questions. They are also incomplete.

A more fundamental question is this: Who are we becoming as we build these tools?

Technologies do not merely solve problems. They shape habits of mind. They reorganize expectations. They train us to imagine certain possibilities as normal and others as obsolete. The internet did not simply accelerate communication; it altered attention. Social media did not simply connect people; it reshaped performance, discourse, and identity. Artificial intelligence will do the same.

One of the most compelling aspects of Leo’s intervention is his refusal to treat “AI ethics” as sufficient. A handful of powerful firms promising responsible development is not the same thing as democratic accountability. Ethical self-regulation, especially when concentrated among those with immense commercial incentives, is not governance. The question is not simply whether these systems are “safe,” but who defines safety, whose interests are protected, and who bears the consequences.

That concern extends to labor. The rhetoric surrounding AI often emphasizes liberation from drudgery. Perhaps some of that promise will prove real. Used well, AI may reduce administrative burdens, assist research, and streamline routine tasks. Many professionals, from teachers to clergy, may find space for more distinctly human work.

But the alternative possibility is equally visible. Entire sectors may discover that “efficiency” means replacing workers whose labor once provided income, identity, and meaning.

This is not merely an economic issue. Work is more than production. It is often participation in a shared social world. It can be a source of dignity, contribution, and vocation. A society that optimizes away meaningful human labor may produce greater efficiency while deepening social fragmentation.

The military implications are perhaps even more troubling. Leo’s warning about entrusting irreversible lethal decisions to artificial systems addresses more than science fiction scenarios. Modern warfare increasingly depends on automation, predictive targeting, and technologies that create moral distance between decision-makers and consequences. The further violence becomes abstracted from embodied human judgment, the easier it becomes to normalize.

Yet the deepest issue may not be economic or military. It may be anthropological.

Artificial intelligence implicitly invites us to define intelligence in narrow, mechanistic terms: pattern recognition, language generation, optimization, prediction. If these capacities become the benchmark for human worth, then humanity itself risks being reconceived as a computational problem.

But human beings are not merely information processors.

We are embodied creatures who love, suffer, remember, promise, grieve, worship, and tell stories about who we are. The meaning of human life cannot be reduced to speed, efficiency, or output.

The real danger may not be that machines become too much like us.

It may be that we become too much like the machines we have built.

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