Part of the e-AA Award Winners Series
The Duolingo English Test (DET) is an online, remotely administered high-stakes assessment of English language proficiency. A test taker can take it on their own computer, anywhere and any time, with results returned within 48 hours. Because every session is recorded and reviewed rigorously after submission, our security system has even more signals to work with than a live proctor does.
In this talk, we present our multi-layered security system that leverages human-in-the-loop AI to protect the integrity of the Duolingo English Test. It spans multiple signal sources and modalities: the responses a test taker submits, where we detect AI-generated responses; the way those responses were produced, where typing behavior separates transcription from organic writing; the patterns that connect one session to another, which reveal impersonation and collusion; and what the cameras show, where we direct proctors to the moments worth further examining. Each layer brings additional robustness to the overall security posture.
The presentation goes through a representative set of these security layers in practitioner detail: the threat that motivated the work, how the detector was built, and how it is evaluated and applied in practice, supported by our peer-reviewed research at EMNLP, AAAI, HCOMP, NCME and AIME-Con. We will also present the human oversight on top of the AI system, and how we ensure that final decisions are accurately made with human judgment in combination with AI signals.
We hope to provide insights that can inform the design of human-in-the-loop AI systems that secure the integrity of high-stakes assessments.
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