The Silent Curriculum: How Does LLM Monoculture Shape Educational Content and Its Accessibility?

TL;DR

This paper investigates how Large Language Models may create a monoculture in educational content, especially affecting children, by propagating stereotypes and biases, and emphasizes the need for diversity in AI training data.

Contribution

It introduces the concept of the 'Silent Curriculum' and provides experimental evidence of shared biases across LLMs, highlighting the societal implications of AI monoculture.

Findings

Strong cosine similarity (0.87) of biases across models.

Models exhibit similar ethnic stereotypes in occupational contexts.

LLMs tend to reinforce cultural stereotypes in storytelling.

Abstract

As Large Language Models (LLMs) ascend in popularity, offering information with unprecedented convenience compared to traditional search engines, we delve into the intriguing possibility that a new, singular perspective is being propagated. We call this the "Silent Curriculum," where our focus shifts towards a particularly impressionable demographic: children, who are drawn to the ease and immediacy of acquiring knowledge through these digital oracles. In this exploration, we delve into the sociocultural ramifications of LLMs, which, through their nuanced responses, may be subtly etching their own stereotypes, an algorithmic or AI monoculture. We hypothesize that the convergence of pre-training data, fine-tuning datasets, and analogous guardrails across models may have birthed a distinct cultural lens. We unpack this concept through a short experiment navigating children's storytelling, occupational-ethnic biases, and self-diagnosed annotations, to find that there exists strong cosine similarity (0.87) of biases across these models, suggesting a similar perspective of ethnic stereotypes in occupations. This paper invites a reimagining of LLMs' societal role, especially as the new information gatekeepers, advocating for a paradigm shift towards diversity-rich landscapes over unintended monocultures.