As AI in the classroom becomes a mainstay, teaching critical thinking becomes essential

Artificial intelligence (AI) is becoming part of everyday learning in classrooms. Students use it to summarize information, generate ideas, explain concepts and answer questions in real time.

While these tools influence how knowledge is accessed and understood, they are not fully aligned with the linguistic and cultural context in which they are being used.

Most large language models have been trained predominantly on English-language and Western-dominant datasets, limiting their ability to fully capture the richness of other languages and the depth of local cultural context.

In non-English educational contexts, this can affect how concepts are interpreted, how examples are framed and which perspectives are prioritized. The issue extends beyond translation accuracy to whether AI-generated knowledge reflects the realities, nuances and contexts of the learners engaging with it.

The challenge becomes more significant as these systems evolve from support tools into trusted sources of knowledge. For example, as Saudi Arabia continues advancing its digital transformation and future-skills agenda, classrooms are becoming one of the first environments where these tensions are surfacing at scale.

This tension extends beyond technical limitations; it directly affects how students understand and engage with knowledge.

Traditionally, classrooms have often revolved around a single primary source of knowledge: the teacher. Information is delivered, interpreted and validated within a structured environment and students are conditioned to trust that epistemic authority.

As AI becomes more embedded in learning, there is a growing risk that this same dynamic simply transfers to AI-generated information.

Students may increasingly treat AI responses as authoritative answers rather than outputs shaped by training data that may carry linguistic gaps, cultural bias and Western-centric assumptions, particularly in non-English contexts.

When treated as unquestioned authorities, AI systems can introduce subtle but significant distortions, oversimplified explanations, missing cultural nuance or interpretations that do not align with local realities.

The core challenge, therefore, extends beyond AI limitations to the reproduction of dependency on a single source of knowledge in a new form.

Addressing this challenge requires a shift in how AI is used in the classroom. Rather than focusing solely on access to tools, the priority is enabling educators and students to engage with them critically and responsibly as they exist today.

In practice, this means supporting teachers to systematically assess AI-generated content for factual accuracy, linguistic precision, cultural relevance, and contextual appropriateness, and to do so in front of students.

Emerging evidence already points to this role. In 2025, the Centre for the Fourth Industrial Revolution in Saudi Arabia and the country’s Ministry of Education surveyed 44,920 teachers across the Kingdom.

Twenty-eight percent of respondents reported actively correcting or adapting biased AI outputs in their teaching, highlighting how quickly educators are becoming critical epistemic intermediaries between students and AI-generated knowledge.

Students, in turn, can be encouraged to systematically critique AI responses, compare outputs across languages and identify gaps or inconsistencies in how information is presented. These practices reposition AI as a tool to be examined rather than accepted at face value, embedding critical thinking into everyday learning.

This shift does not diminish the role of the teacher; it strengthens it. While teachers may no longer be the sole source of information, their role becomes even more important in guiding inquiry, fostering judgment and helping students develop the skills and confidence needed to navigate information from multiple sources.

Saudi Arabia’s experience reflects how education systems are beginning to navigate a broader shift in how knowledge is interpreted and trusted in the age of AI.

As national efforts around AI adoption accelerate, classrooms are becoming early environments where educators and students are learning how to engage with AI-generated information thoughtfully rather than passively.

This includes growing awareness of linguistic and cultural bias, supported by broader national efforts around responsible AI and contextually relevant AI use.

Educators are now guiding students in evaluating, contextualizing and interpreting AI-generated content within learning environments, reinforcing the importance of human judgment and critical inquiry for learning.

This experience may offer an early signal for many non-English-dominant education systems likely to navigate similar shifts.

As AI adoption increases globally, education systems will need to consider how language, context and cultural perspectives shape AI-generated outputs. In this environment, the ability to question information may become one of education’s most essential skills.