AI detection tools may create bias against English language learners. Image by Thought Catalog on Unsplash.
<h5>By Zachary Amos</h5>
<h2>AI detection tools are gaining traction in schools as a way to spot content generated by platforms like ChatGPT.</h2>
<p>Still, these programmes can have flaws, especially when identifying work from nonnative English speakers. Because many detectors analyse sentence complexity, word choice and flow, they often misinterpret genuine student writing as AI-generated if it doesn’t match native-level patterns.</p>
<p>This poses a real problem in New Zealand’s multicultural classrooms, where learners from migrant, Pasifika and Asian backgrounds bring diverse language styles. When their work is unfairly flagged, it can lead to confusion, unfair consequences, and a breakdown in trust between students and educators.</p>
<h3>The problem with AI detection bias</h3>
<p>AI detectors are built using native English writing patterns, which makes them prone to mislabelling nonnative writing as AI-generated. When students use simpler sentence structures or write in a more formulaic way, which are common traits among English language learners, these tools may flag their work incorrectly.</p>
<p>This is especially concerning in New Zealand, where there were <a href="https://www.enz.govt.nz/news-and-research/ed-news/69000-international-student-enrolments-in-2023" target="_blank" rel="noopener">69,000 international student enrollees</a> in 2023. One study revealed that an AI checker wrongly identified <a href="https://www.cell.com/patterns/fulltext/S2666-3899(23)00130-7#%20" target="_blank" rel="noopener">over half of Chinese students&#8217; TOEFL essays</a> as AI-generated. Meanwhile, the same tool accurately classified essays written by American eighth graders. This highlights a clear bias that can unfairly penalise real student work and mislead educators trying to uphold academic integrity.</p>
<h3>Why this matters in New Zealand classrooms</h3>
<p>New Zealand&#8217;s classrooms are becoming more linguistically diverse, with rising English language learners (ELL) from migrant communities. ELL students may span all levels of language proficiency, from beginners with limited English to those who communicate fluently but are still developing academic writing skills.</p>
<p>AI detection tools, however, often misread this range of expression and flag legitimate student work as AI-generated. Such false positives can harm a student’s confidence, lead to unnecessary disciplinary measures and create tension in the classroom. When edtech models carry built-in language biases, they risk undermining the inclusive, supportive learning environments that New Zealand educators work hard to build.</p>
<h3>How educators should respond</h3>
<p>AI detection tools should support, not replace, a teacher’s professional judgment. Relying solely on them risks proxy discrimination, especially when <a href="https://rehack.com/ai/understanding-3-major-artificial-intelligence-ethical-issues/" target="_blank" rel="noopener">AI is trained on flawed data</a> or patterns shaped by systemic bias. Educators should treat flagged results as a starting point, not a verdict.</p>
<p>Comparing the work with prior writing samples and in-class performance helps contextualise things. It&#8217;s also vital to equip teachers with the training to recognise genuine red flags while appreciating the natural writing differences that come with linguistic diversity. When used thoughtfully, AI detectors can be part of a fairer, more inclusive assessment process.</p>
<h3>Better practices for fair use of AI detectors</h3>
<p>Clear communication around AI use is essential, especially as schools grapple with new challenges in student assessment. Some institutions have already <a href="https://www.rnz.co.nz/news/national/528800/schools-abandon-take-home-assignments-after-artificial-intelligence-used-to-cheat" target="_blank" rel="noopener">eliminated take-home assignments</a> due to concerns that students turn to AI tools to complete their work. Rather than creating a climate of suspicion, schools should focus on building trust by setting transparent AI policies and explaining what is and isn’t allowed.</p>
<p>Encouraging students to seek writing support can promote better learning outcomes. When work from English language learners is flagged, involving English for Speakers of Other Languages specialists ensures a fairer review that considers language development and cultural context.</p>
<h3>Striking the balance between integrity and inclusion</h3>
<p>AI tools offer valuable support in upholding academic standards, but they often misjudge writing from nonnative English speakers. New Zealand schools must use these programmes thoughtfully to ensure fair treatment, protect student confidence and promote truly inclusive education.</p>
<p><em>Article by Zacahry Amos</em></p>

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