Artificial Intelligence, Authentic Voices
Artificial Intelligence, Authentic Voices examines what student work can legitimately tell us about learning when generative AI can participate in production. The book argues that authentic voice is expressed through the consequential judgments students make and take responsibility for, and that evidence of learning must increasingly be designed rather than assumed from a finished product.
What Changes When AI Can Produce the Work?
Production is not the same as learning.
A polished finished product may no longer tell us how much of the underlying intellectual work a student actually performed.
Authentic voice resides in judgment.
What matters is not simply whether students produced every word or component themselves, but whether they originated and retained responsibility for consequential intellectual decisions.
Evidence has to be designed.
Rather than trying to detect how work was produced, assignments can be designed to make meaningful student judgment more interpretable.
Making Thinking Visible
Finished product
What the student ultimately submits.
Process record
Evidence of activity: drafts, prompts, revision histories, notes, transcripts, screenshots, disclosures.
Designed evidence
Evidence deliberately built into the assignment so that a faculty member can make a more meaningful inference about student judgment and learning.
The goal is not to document everything a student does, but to make the consequential thinking in an assignment more visible.
Diagnosing an Assignment
What important decision must the student make?
Are there genuinely plausible alternatives?
What criteria should guide the decision?
Does the decision change what happens next?
Will the student have to revisit that decision when evidence, feedback, or conditions change?
What evidence of the student’s judgment will the instructor actually see?
If the assignment has already made the important choices, students may be left mainly to execute a predetermined path. Redesign begins by locating a decision that matters and deciding what evidence would make the basis of that decision interpretable.
From Authentic Voices to Refractive Design
Refractive Design is the practical approach that grows from that argument. It helps faculty separate an assignment into the design decisions underneath it, examine those decisions deliberately, and recombine them to generate new assignment architectures.