On AI, Homelessness, Proximity, and the Moral Measure of Progress
There is a difference between solving a problem
and moving it beyond our sight.
A tent disappears from a sidewalk.
A person is moved from a doorway.
An encampment is cleared from beneath an overpass.
A bench is redesigned so no one can sleep upon it.
The street appears cleaner. The complaint count falls.
The map changes. The report records improvement.
But one question remains:
Where did the person go?
If we cannot answer that question,
we should be careful about calling what happened progress.
We may have moved the problem.
We may not have moved toward the neighbor.
> The Difference Between Distance and Resolution
Modern institutions possess
extraordinary power to manage visibility.
A city can relocate an encampment.
A corporation can automate an uncomfortable decision.
A government can convert human circumstances into classifications.
And artificial intelligence can make all of these processes faster, more precise, and more scalable.
But efficiency cannot determine
whether the underlying action is just.
A person removed from one sidewalk may appear on another.
A family excluded from one neighborhood may disappear
into a vehicle. A worker rejected by an automated system may
vanish from the applicant pool.
A person denied assistance may disappear from a dashboard
while remaining hungry outside it.
Systems are very good at counting
what remains inside their boundaries.
The neighbor may be standing just beyond them.
This is why proximity matters.
The spreadsheet can tell us that an encampment disappeared.
The street can tell us where the people went.
> AI Can Magnify Whatever We Teach It to See
Artificial intelligence will increasingly
help institutions classify needs, allocate resources,
detect violations, predict risks, manage public spaces,
and recommend actions.
That power can serve people tremendously.
But AI can also inherit the blindness of the culture that deploys it.
If we teach a system that homelessness is primarily a problem of tents, it may become extraordinarily efficient at finding tents.
If we define success as removing tents, the machine may help remove them faster.
But the machine may never ask:
Does this person have somewhere safe to sleep tonight?
That question must come from us.
AI does not determine the moral meaning of its objective.
Human beings do.
And therefore every optimization should carry a second question:
What happens to the person when this metric improves?
> The Neighbor Is Not the Obstacle
The Good Samaritan encountered a wounded man
who interrupted his journey.
The man beside the road could have been treated as an obstacle—
a delay, a danger, someone else's responsibility.
Instead, Scripture tells us that
the Samaritan “came where he was” (Luke 10:33).
That movement is decisive.
He did not solve suffering from a distance.
He crossed the distance.
He saw.
He approached.
He touched.
He lifted.
He carried.
He paid.
The wounded person changed the Samaritan's journey.
That is why the parable remains such a powerful challenge
to technological civilization.
Our systems increasingly ask:
How can we remove the interruption?
The Gospel asks:
How can we become the neighbor?
> Proximity Is an Audit of the System
This is why the street must remain one of the places
where our claims of progress are examined.
If a policy says homelessness declined, go to the street.
If an algorithm says resources were efficiently distributed,
find the people who were denied them.
If a redevelopment project says the neighborhood improved,
ask who can still afford to live there.
If an automated system says its decisions are accurate,
listen to those who carry its errors.
Proximity audits abstraction.
It forces the map to encounter the territory.
It forces the statistic to encounter the person.
It forces policy to encounter consequence.
It forces artificial intelligence to encounter the human being
whose life cannot be completely represented by data.
The street asks what the dashboard cannot:
Who disappeared when the number improved?
> The Moral Measure of AI
As artificial intelligence becomes more capable,
we will hear extraordinary claims about productivity,
optimization, prediction, automation, and efficiency.
Many will be legitimate achievements.
But these cannot become the final measurements of
technological progress.
We must also ask:
Did AI make the vulnerable easier to see or easier to remove?
Did it strengthen human responsibility or distribute responsibility
until no one could be held accountable?
Did it bring resources closer to those who needed them or
merely make institutional management more efficient?
Did it help us recognize the person behind the classification?
Did it shorten the distance between suffering and assistance?
And perhaps most importantly:
Did greater intelligence produce greater proximity?
If not, something essential remains unfinished.
> Do Not Teach the Machine to Look Away
A civilization eventually teaches its machines
what it considers important.
That is why AI culture matters.
If our culture treats inconvenient people as problems to relocate,
our machines may automate relocation.
If our culture treats poverty primarily as disorder,
AI may become very effective at managing
the appearance of disorder.
If our culture treats human beings primarily as economic units, algorithms may optimize accordingly.
But if our culture insists that every human being possesses dignity that cannot be reduced to efficiency, then our institutions can design, govern, and evaluate AI differently.
The first guardrail is therefore not merely code.
The first guardrail is what we believe about one another.
> The Neighbor Must Remain Visible
The future will contain machines capable of seeing patterns
no human being can see.
But there is a terrible possibility:
a machine may see everything except the neighbor.
It may see coordinates.
Risk scores.
Housing status.
Employment history.
Medical records.
Purchasing behavior.
Probability.
Eligibility.
Violations.
It may know thousands of facts about someone
while knowing nothing of what it means to stand beside that person.
That is why human responsibility cannot be surrendered.
The machine may provide the map.
Someone must still walk the street.
The machine may identify the need.
Someone must still come near.
The machine may recommend an intervention.
Someone must still ask what happened afterward.
The machine may count the tents.
Someone must still count the people.
> The Final Question
We should therefore carry one question into city halls, technology companies, universities, courts, churches, and every institution adopting artificial intelligence:
Did we move the problem—or did we move toward the neighbor?
That question can expose false progress.
It can test policy.
It can test technology.
It can test law.
It can test ministry.
And it can test us.
Because a society can become extraordinarily sophisticated at making suffering less visible without becoming any better at
relieving suffering.
AI could make that ability frighteningly efficient.
Or it could help us do something better.
It could help us find the forgotten.
Coordinate care.
Detect unmet needs.
Translate languages.
Connect resources.
Identify patterns of exclusion.
Bring knowledge to those previously denied it.
And help human beings reach one another more effectively.
But the direction must remain ours.
The machine cannot decide whom we are willing to call neighbor.
We must.
And when the maps have been updated, the algorithms optimized, the streets cleared, the reports published, and the officials declare success, let someone still walk beyond the boundary of the statistic and ask: Where did the person go?
If we find the neighbor farther away, carrying the same blanket and the same wound, we have our answer.
We moved the problem.
But if we crossed the distance, shared the burden, protected dignity, and remained until displacement became belonging, then something more profound has happened.
We moved toward the neighbor.
And that—not disappearance, not efficiency, not appearances—
must remain one of the deepest measures of human progress
in the age of artificial intelligence.
Pastor Steven G. Lee
St. GMC Corps
October 3, 2026
https://www.facebook.com/steven.g.lee1/posts/pfbid0QJU3fYRyNRBUB84krEuxqqoPyBEGwD7yKJyNgfV3ByHkcoYcNs61zmt2ahyqREQwl
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