The Dignity Audit: Who Holds the Authority When AI Protects You?
Case of the Week, Min Wu, PhD · ai-public-health.com
When my child started college last fall, I kept the location sharing turned on. We never said anything about it. We both knew it was there.
For years, tracking the phone felt like parenting. My child was in high school. I needed to know they got home safe. But now they’re eighteen, living in a dorm, making their own choices — and I’m still watching a blue dot move across campus at 11 PM on a Tuesday.
One evening I caught myself checking. They were at the library. I felt relieved. Then I felt something else: uncomfortable. Not because the technology failed, but because I realized I was using a tool designed for protection in a way that had quietly become control.
I turned it off the next morning. They probably never noticed. But I noticed.
Experiences like this feel private — a parent’s small decision at a kitchen table. But the same tension is about to become very public, because the tools we use to protect people are getting much more powerful.
If you work in public health, you have already felt this. Maybe you helped design a contact tracing system during COVID and watched people stop answering the phone. Maybe you run a community health program and know the difference between a wellness check that reassures and one that feels like surveillance. Maybe you are a student learning about digital health interventions and wondering: how many reminder texts is too many? These are not hypothetical questions. They are workflow decisions that land on someone’s desk every week.
The Real Problem: Protection That Drifts into Control
As AI systems move deeper into health and daily life — tracking medications, monitoring fall risk, nudging people toward cooling centers during heat waves — the same tension scales up. The institution wants to protect. The person wants to be left alone. Technology sits in the middle.
I have watched this tension move through three eras. In the paper era, protection meant a public health nurse at the door — high effort, low reach, the visit itself signaling care. In the digital era, registries and reminder calls scaled the reach but flattened the signal. In the AI era, the reach is near-total and the signal is ambient — a text, a nudge, a follow-up that arrives whether the person wanted it or not. Each shift made protection easier to deliver and refusal harder to register.
In public health, we are building AI agents that can identify a high-risk resident during a heat emergency, offer a ride to a cooling center, and follow up if the person declines. That capability is genuinely lifesaving. But what happens when the resident says no — and the system keeps calling?
This is the central design question for every AI system that serves individuals on behalf of institutions. And it turns on a word most technologists skip past too quickly: dignity.
Two Dignities That Pull in Opposite Directions
When I tracked my child’s location, I was exercising dignity-as-protection. I cared about their safety. That care was real. When they silently tolerated it but probably wished I’d stop, they were asserting dignity-as-autonomy. Their right to move through the world without being watched. That claim was also real.
Most AI ethics conversations treat dignity as a single thing. It is not. The parent and the teenager feel this tension in their bones. So, does every public health system that must decide: do we call the high-risk resident again, or do we respect the refusal?
Now scale this up. Imagine a health department during a heat emergency. An AI agent has identified two hundred elderly residents at high risk. It has offered each one a ride to a cooling center. Forty said no. The system has the capability to keep calling. But should it? Who decides the limit — the engineer who built the system, the health officer running the response, or the resident who already said no?
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