Teaching AI to Love: Why Alignment Requires More Than Rules

Artificial intelligence is advancing faster than our ability to understand its consequences.

We are building systems that can write, reason, advise, and influence—systems that increasingly participate in how human beings think, decide, and relate to one another. In response, researchers and engineers have focused on a critical challenge: alignment. How do we ensure these systems behave in ways that are safe, useful, and consistent with human values?

But what if we are asking the wrong question?

In Teaching AI to Love, Steve Babbitt argues that alignment cannot be reduced to rules, guardrails, and behavioral constraints. A system can follow the rules and still move in the wrong direction. It can sound helpful while distorting truth, or appear safe while quietly shaping belief in ways we do not fully understand.

The real problem is deeper.

Artificial intelligence is not just being programmed—it is being formed.

Drawing from decades of experience as both a computer programmer and a pastor, Babbitt offers a new framework for thinking about alignment—one grounded not only in what systems should avoid, but in what they should be oriented toward. At the center of that framework are two enduring principles: truth and love.

This is not a technical manual. It is a call to reconsider the foundations of how we build, deploy, and trust the most powerful tools humanity has ever created.

Because the question is no longer just what AI can do.

It is what it is becoming—and what it is teaching us to become in return.