Generative AI is often framed as a productivity tool.
It suggests code, summarizes documents, recommends next actions.
In most systems, it doesn’t decide — it assists.
And yet, many users report the same experience:
“I technically chose, but it didn’t feel like a decision.”
This article is about why that feeling matters — and what it means for how we design AI systems.
AI Rarely Decides for You — It Redesigns the Decision
Most AI systems today operate through recommendations:
ranked lists
suggested defaults
optimized outputs
“best” answers
None of these force action.
But they do something subtler: they shape what feels reasonable.
When a system presents an option as:
comprehensive
optimized
neutral
disagreeing with it starts to feel irrational, even irresponsible.
The user still chooses — but the space of judgment has already been compressed.
From External Rules to Internal Alignment
Traditional hierarchy worked through explicit authority:
rules
approvals
commands
These were visible, and therefore contestable.
Modern systems increasingly work through standards instead:
efficiency
best practice
optimization
benchmarks
Generative AI accelerates this shift.
Instead of telling users what to do, it shows them what “makes sense.”
Over time, those standards are internalized.
Compliance feels like good judgment.
This is what I call internalized hierarchy:
power embedded not in commands, but in the reasoning process itself.
Why “Human-in-the-loop” Often Fails
Many AI systems address responsibility by keeping a human “in the loop.”
A human approves the output. A checkbox is checked.
But approval is not judgment.
If the system:
resolves uncertainty in advance
hides trade-offs
presents one option as clearly superior
then the human role becomes ceremonial.
Judgment requires:
incomplete information
visible trade-offs
the possibility of being wrong
When those conditions are optimized away, judgment disappears — even if a human is still present.
Designing Systems That Still Require Judgment
If we want AI systems that preserve human agency, this cannot be solved with ethics statements alone.
It is a design problem.
Here are three practical design principles:
Preserve Friction
Not every decision should feel smooth.
Moments of hesitation are not bugs — they are signals that judgment is happening.
Expose Trade-offs
Avoid single “best” outputs when real alternatives exist.
Show why one option excels and where it fails.
Keep Decisions Incomplete
Systems should support interpretation, not closure.
A decision that feels finished before a human engages with it is already delegated.
The Question That Matters
The real question is not:
“Should we use AI?”
But:
Does this system invite human judgment — or quietly render it redundant by design?
Generative AI will continue to improve.
The risk is not that it becomes too powerful,
but that it becomes so reasonable we stop noticing when judgment is no longer required.
Further Reading
This post is based on my recent paper:
Reclaiming Judgment in the Age of Generative AI: Design, Internalized Hierarchy, and Individual Agency
DOI: 10.5281/zenodo.18136101
I welcome feedback, critique, and collaboration — especially from those designing systems where human judgment still needs to remain meaningful.
Top comments (0)