Beyond Anthropomorphism: a Spectrum of Interface Metaphors for LLMs

TL;DR

This paper explores a spectrum of interface metaphors for LLMs, moving beyond anthropomorphism to promote critical engagement and transparency about their sociotechnical nature.

Contribution

It introduces a theoretical framework and a spectrum of metaphors to reshape how LLM interfaces influence user perception and interaction.

Findings

Proposes a spectrum from anti-anthropomorphism to hyper-anthropomorphism.

Highlights the importance of exposing LLMs as sociotechnical systems.

Encourages interface designs that foster critical engagement.

Abstract

Anthropomorphizing conversational technology is a natural human tendency. Today, the anthropomorphic metaphor is overly reinforced across intelligent tools. Large Language Models (LLMs) are particularly anthropomorphized through interface design. While metaphors are inherently partial, anthropomorphic interfaces highlight similarities between LLMs and humans, but mask crucial differences. As a result, the metaphor is often taken literally; users treat LLMs as if they are truly human. With few safeguards in place, this extreme anthropomorphism drives users to delusion and harm. Users also experience dissonance between the ethics of using LLMs, their growing ubiquity, and limited interface alternatives. We propose repositioning anthropomorphism as a design variable, developing opposing extremes as a theoretical framework for how interface metaphors shape and can disrupt the default metaphor. We introduce a spectrum of metaphors from transparency-driven ''anti-anthropomorphism'' to uncanny ''hyper-anthropomorphism''. These metaphors introduce materiality to interface metaphors, exposing LLMs as sociotechnical systems shaped by human labor, infrastructure, and data. This spectrum shifts interface design away from optimizing usability and toward encouraging critical engagement.