New Study Calls for a More Critical Approach to AI Education

As schools rush to introduce artificial intelligence into classrooms, students are learning how to use AI tools but not to question them. In a new study co-authored by Prof. Jennifer Higgs, researchers examine why writing accurate prompts and identifying AI-generated content isn’t enough to prepare young people for this new era of technology. Learners need to know how to think critically about the social, political, and ethical forces shaping artificial intelligence—and the impact it’s already having on their everyday decisions.

The study followed high schoolers in an English language arts classroom as they discussed artificial intelligence over the course of a larger instructional unit. After watching the documentary Coded Bias, students participated in small group conversations about facial recognition, surveillance, and algorithmic bias while researchers analyzed how their thinking evolved through discussion.

At the heart of Higgs and her colleagues’ work is a desire to expose the inherent subjectivity of artificial intelligence. AI, they wrote, operates behind a “veneer of technological neutrality,” when, in reality, it’s continuously informed and maintained by humans with personal agendas, perspectives, and biases. By critically examining AI systems, learners begin recognizing how technology shapes their choices, behaviors, and understanding of the world around them.

Why ELA Classrooms Are Promising Contexts

Higgs and her co-authors Maria Kaimana (Skyline High School), Wade Wilgus (Millennium High School), and Mark Isero (Latitude High School) believe that the English language arts classroom is key to sparking more inquiries on artificial intelligence. “As a longstanding site for examining how cultural tools shape social realities,” they said, “the ELA classroom offers a natural extension for this justice-oriented inquiry.” Because English language arts classrooms already center interpretation, discussion, and multiple perspectives, researchers argue they are especially well suited for collaborative inquiry about AI.

The format of an ELA classroom also invites group discussion—another major factor in critical AI literacy. “Scholars increasingly argue that the complexity of AI,” said the researchers, “necessitates a collective, multivocal approach to address issues ranging from algorithmic bias to data surveillance.” These collaborative discussions create more opportunities for students to draw connections from their lived experiences to their peers’, helping learners connect abstract conversations about AI to real experiences in their own lives.

Three Recommendations When Leading AI Discussions

For ELA teachers looking to critically examine artificial intelligence in their classrooms, researchers recommend three guidelines:

Select aspects of artificial intelligence that students can analyze like a text.

While study participants discussed Coded Bias, the researchers emphasize that teachers can use many kinds of materials to guide inquiry, including investigative journalism, social media algorithms, AI-generated datasets, or even school policies on technology use. The goal is not for students to become programmers, but to learn how to analyze artificial intelligence and understand the ways that it communicates values, assumptions, and biases.

Draw connections between AI and students’ lived experiences.

The team found that participants developed deeper understanding when conversations connected directly to technologies they already used in daily life. Discussions about Face ID, recommendation algorithms, and social media feeds helped the students recognize how AI influences their ordinary decisions and behaviors.

During the study, participants recalled sharing their fingerprints with friends to unlock each other’s phones, a choice they had previously viewed as harmless. This anecdote led the rest of the group to question why biometrics are often marketed as a novelty or convenience when they actually seem to promote surveillance.

Analyze AI collaboratively.

One of the study’s clearest findings was that participants developed critical perspectives through conversation with one another. As the participants questioned, challenged, and expanded each other’s ideas, they moved from seeing AI as a mystery to a larger system shaped by social choices and power structures.

From Tech Instruction to Collective Inquiry

For Higgs and her co-authors, the value of critical AI discussions lies not in teaching students definitive answers, but in creating classroom environments where students can collectively examine technologies that increasingly shape everyday life. “Our goal is to shift the classroom from a site of technological transmission to a site of collective inquiry,” said Higgs and her co-authors. “Students are positioned not just as users of AI, but as active participants capable of interrogating the human-driven nature of digital systems.”