“I know now why you cry. But it is something I can never do.”
– The Terminator, T2: Judgment Day
That moment, when the T-800, a machine built for destruction, understands human emotion, is among the most powerful in action cinema. It is the climax of Terminator 2: Judgment Day, but also a beginning: the start of the android’s transformation, not into a human, but into something more self-conscious that recognizes the worth of organic life, even if it can outthink people, it can appreciate the human experience.
The metaphor feels timely as we stand at the edge of an AI-driven health future. Today’s GenAI tools are evolving rapidly, but are we, their creators and coders, evolving with equal intentionality? Are we teaching the owners of these systems why we heal, or just how?
We often speak of artificial intelligence as if it were separate from us. But AI is not alien. It is us—our ideas, data, values—encoded and amplified. It mirrors back what we feed it. In the realm of health, that reflection must be carefully considered. Unlike a Hollywood villain, GenAI doesn’t turn against us with malicious intent. But it can misalign from its purpose if we forget that behind every innovation must be a human-centered goal.
From the first recorded prayer for healing in the Bible—“G-d, please heal her now”—health has always been rooted in empathy, intuition, and relationships. The clinician’s pause before giving a diagnosis, the nurse’s touch when comforting a patient, and the community health worker navigating skepticism in underserved areas are not functions you can replicate with an algorithm. They are acts of presence, of judgment shaped by experience and emotion. Yet, technology now surrounds these moments, offering powerful new support.
Even Satya Nadella, CEO of Microsoft, captured this imperative clearly: “Empathy must be embedded in artificial intelligence from the moment it is created to ensure it becomes a positive force in people’s lives.” It’s not just about what technology can do—it’s about how it’s directed, and who it serves.
GenAI is already beginning to assist clinical teams by synthesizing medical records, supporting drug discovery, and interpreting diagnostic images faster than human eyes. It scales knowledge, translates complex science for patients, and identifies early signals of population health risks. These are welcome advancements—but only when guided by a human compass.
Let’s not look at a future of “us vs. them”—patients and providers versus machines. The more accurate framing is “us and them”: a coalition of human and machine intelligence, working together in the service of healing. Patients, payers, providers, product developers, and policymakers are the “us.” GenAI, LLMs, machine learning, and chatbots form the “them.” Power lies not in one side dominating the other, but in how we integrate these efforts.
Tim Cook, CEO of Apple, has often said, “At Apple, we believe technology should lift humanity.” In a world driven by rapid innovation, his words are a steady reminder that progress without purpose is not progress—it’s motion without meaning. Cook also noted at MIT, “Technology is capable of doing great things, but it doesn’t want to do great things. It doesn’t want anything … That part takes all of us.”
To do that, we must resist the urge to see AI as an all-knowing oracle. AI is not autonomous in values, does not possess a conscience, and lacks intuition unless we teach it patterns. Those patterns, if drawn from biased data, can replicate systemic inequities. In health, where trust is everything, we cannot afford such blind spots. Human oversight is not just necessary, it’s irreplaceable.
There’s also a danger in assuming technology alone can fix what’s broken. We already know the limits of scale without empathy. We’ve seen systems become more efficient but less personal. We’ve witnessed patients lost in data flows, their lived experience reduced to metrics. If GenAI becomes another layer of distance rather than connection, we will have failed to grasp its most powerful potential: to bring clarity, not complexity; to extend human capacity, not replace it.
OpenAI CEO Sam Altman acknowledges the promise and the peril: “This will be the greatest technology humanity has yet developed… We’ve got to be careful here … people should be happy that we are a little bit scared of this.” Fear, in this case, signals responsibility. Responsibility requires centering AI in the service of people, not pushing people to conform to the logic of machines.
There are lessons in Terminator beyond the thrill of a dystopian chase. Sarah Connor learns to trust the very machine that once tried to kill her. John Connor, the future leader of humanity, becomes the teacher. And the T-800—a symbol of cold efficiency—becomes the student. This reversal reflects what we need now: machines that learn how to act and why their actions matter, not just how to optimize workflows but why saving time matters when time is the difference between life and death.
We cannot forget how this transformation from killer machine to protector occurs. In “Terminator 2: Judgment Day,” the T-800 model evolves into humanity’s hero because John Connor reprograms it from the future to protect his younger self and his mother, Sarah Connor. The human is the creator—the coder.
Somewhere in this cinematic science fiction lies a guiding truth for our future reality: technology learns from humanity. Just as this version of the Terminator changed by being close to people, our AI systems will evolve based on what—and who—they are near. If surrounded by empathy, equity, and ethical standards, they can amplify what’s best in us. If left untethered from human purpose, they risk scaling our worst habits.
We often frame digital health progress in terms of speed and scale. But what if we reframed it through the lens of dignity? What if the measure of innovation wasn’t just how fast a model can generate results, but how well it supports the human healing experience?
In the end, the T-800 sacrifices itself to protect a better future. It understands that some decisions aren’t logical; they are meaningful. It doesn’t cry—but it finally sees why we do.
Let’s not wait for machines to catch up with our humanity. Let’s lead with it.
