Disparate Treatment
Intentional discrimination based on a protected characteristic. In AI systems, disparate treatment occurs when protected attributes like race, gender, or age are explicitly used as input features for decision-making, or when different rules are applied to different groups by design.
Why It Matters
Disparate treatment is the more straightforward form of AI discrimination — and the easier one to detect and prove legally. Even well-intentioned uses of protected attributes (like race-adjusted medical scoring) can constitute disparate treatment.
Example
An insurance pricing algorithm that charges higher premiums to applicants from specific zip codes — used as a proxy for race — constitutes disparate treatment if the intent or effect is to discriminate on the basis of a protected characteristic.
Think of it like...
If disparate impact is accidentally building a door too small for tall people, disparate treatment is putting up a sign that says 'tall people not welcome.'
Related Terms
Disparate Impact
A facially neutral policy, practice, or algorithm that disproportionately harms a group based on a protected characteristic — even without discriminatory intent. In AI, disparate impact commonly occurs when models trained on historically biased data reproduce or amplify those patterns in their outputs.
Bias (AI)
Systematic errors in AI system outputs that produce unfair or skewed outcomes. AI bias can originate from training data (historical, representation, measurement, sampling, or aggregation bias), from model design choices, or from the deployment context. Bias is not always obvious and can compound through the AI lifecycle.
Fairness (AI)
The principle that AI systems should produce equitable outcomes and not discriminate against individuals or groups based on protected characteristics. Multiple mathematical definitions of fairness exist — demographic parity, equalized odds, individual fairness, and others — and they frequently conflict with each other, making fairness a design choice, not a single metric.