Modern systems are designed around a particular kind of person. Not a statistical average or a real human being,but a convenient fiction: a user whose life aligns cleanly with the assumptions embedded in workflows. This figure rarely appears inwriting, yet their outline determines everything—how quickly responses are expected, how rigid a deadline can be, and how manysteps must be completed without interruption.
This is the “reasonable person” as imaginedby modern infrastructures. A person with stable income, predictable availability, continuous attention, consistent documentation, andenough slack in their life to stay perfectly in sync with whatever the system requires.
The problem is not that such aperson doesn’t exist. The problem is that most actual human lives don’t—and can’t—conform to thismodel. When they don’t, the people living those lives are quietly recoded as the problem: the unreasonable people the systemcannot accommodate.
I. The Myth of the Ideal User
Every system simplifies in order to function. But asinstitutions become more automated and optimized, their user-models narrow. Simplification hardens into requirement.
A“reasonable” user becomes someone who:
- can respond within the specified window
- can complete tasks in one sitting
- can navigate updated systems without losing their place
- can gather documents immediately
- can schedule around limited service hours
- can absorb delays without cascading consequences
Beneath each is the same premise: the user’slife is frictionless enough to comply. This is where the gap opens. Real lives collide with system design becausethe system assumes a stability most people simply do not have.
II. How Design Exclusion Creates“Unreasonable” People
When someone deviates from the expected pattern—misses a deadline, shows upwithout a document, responds too slowly—the system performs a familiar attribution error: it fails to see themismatch as a design constraint and instead treats the deviation as a personal failure.
Consider the lives most oftenlabeled “unreasonable”:
- A parent caring for a sick child.
- A shift worker whoseschedule changes weekly.
- A disabled person with fluctuating energy or health.
- Animmigrant navigating conflicting documentation requirements.
- A student juggling work, debt, and irregularhours.
- A gig worker dependent on volatile earnings and algorithms.
None of these livesare unusual. They only look “unreasonable” relative to an infrastructure designed to exclude them.
III. Systemic Rigidity vs.Human Complexity
Systems that demand consistency from inconsistent lives predictably misinterpret normal complexity asdisorder.
A rigid system interacting with a variable world reads variance as noncompliance.
Amissed deadline is interpreted as irresponsibility. A rescheduled appointment becomes noncompliance. A delayed uploadbecomes negligence. A conflicting obligation becomes excuse-making.
It is not people who are failing;it is the system’s tolerance that has evaporated. Because the imagined Reasonable Person is treated as the default standarduser, everyone else gets sorted into an informal category: the “unreasonable people” who supposedly cannot manage theirlives.
IV. The Loss of Human Judgment in Automation
In more flexible eras, mismatches were absorbed byhuman judgment—clerks who understood context, caseworkers who recognized competing demands.
As interpretive layersare replaced by portals, automated triggers, and rigid thresholds, thesystem’s capacity to recognize legitimate variation disappears.
The burden of coherence moves outward: humanvariability is flattened so systemic rigidity can be maintained.
What used to be handled with discretion is nowhandled with denial. There is nowhere in the workflow to register that a “non-compliant” person is simplysomeone whose life does not match the imagined script.
V. Reframing User Failureas Design Flaw
Once this dynamic comes into view, responsibility becomes easier to locate.
The problem isnot that individuals are inconsistent. The problem is that infrastructures demand a level of consistency real life does not allow.What looks like failure is often nothing more than evidence of competing realities that the system refuses to acknowledge.
If a system only works for people whose lives never collide with anything else, then the system is the one that isunreasonable.
Seen this way, “unreasonable people” are often just the ones whose lives reveal where the model breaks. Their so-calledfailure is a description of the system’s narrowness, not of their worth.
1. The AbsorptionPath: Individuals Bend
Continue as we are. People keep absorbing the mismatch, performing heroics to stay compliant. Their compensatory labor is misread ascompetence. Their collapse is misread as personal fault.
“Unreasonable people” are instructed to try harder.
2. The Calibration Path: Broaden the Model Slightly
Add flexibility, widen windows, soften edges.
Expect people to shield one another from the worse elements of thesystem.
This is helpful but brittle. As long as the incentives reward narrowness, broadened models regress toward theReasonable Person's silhouette.
Calibration masks the problem; it does not resolve it.
3. The HumanArchitecture Path: Redesign for Real Life
The only durable option. Build systems that remain stable when people donot.
This means infrastructures with:
- operational slack rather than minimum viable margins
- interpretive capacity rather than binary thresholds
- multiple timelines rather than one correctpace
- accommodation for interruption, conflict, and return
- logic that treats mismatch asdiagnostic, not deviant
It is what accuracy, resilience, and fairness require.
A systemdesigned for an imaginary person will always malfunction on contact with the world—and will keep calling that malfunction“unreasonable people.”