Why Doctors, Judges, and Teachers Need Different Kinds of Explanations

 

Article 3: Why Doctors, Judges, and Teachers Need Different Kinds of Explanations

Not all explanations are created equal. A doctor, a judge, and a teacher may all use AI, but the explanations they need are radically different.

Doctors: Causal reasoning

Doctors need to know: What symptoms or features led to this recommendation? If an AI suggests pneumonia, the doctor must see the path from data to diagnosis. Otherwise, they cannot justify treatment decisions—or maintain patient trust.

Judges: Procedural fairness

Judges are not only making decisions; they are upholding legitimacy. They need to know: Did the AI apply rules fairly and consistently? For them, explanations must emphasize due process, not just outcomes.

Teachers: Pedagogical insight

Teachers want to understand student thinking. If an AI marks an essay low, the teacher needs more than “grammar errors detected.” They need insight into the learning process—so they can guide growth, not just assign grades.

Case study: COMPAS in U.S. courts

The COMPAS risk-scoring algorithm has been criticized for opaque decision-making. Judges often receive risk labels (low/medium/high) without clear explanations. For legitimacy, explanations would need to highlight which factors weighed most—and whether those factors align with legal fairness.

Case study: AI in medical imaging

Some modern radiology AIs include heat maps that highlight regions of an image influencing the decision. This form of visual explanation is tuned to what doctors need: a bridge between machine reasoning and human diagnostic reasoning.

Case study: AI in education

Adaptive learning platforms (e.g., DreamBox) give teachers dashboards that track learning progressions. Explanations here are less about accuracy and more about developmental narratives—how the student reached an answer and what misconceptions persist.

Takeaway

Explanations must be domain-sensitive. XAI cannot be one-size-fits-all; it must adapt to the values, accountabilities, and practices of different professions.

👉 Reflection: What would an “explanation template” for your field look like? Would it highlight causes, procedures, or growth?

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