Translation in the Hands of Many:Centering Lay Users in Machine Translation Interactions

TL;DR

This paper explores how the widespread use of machine translation by lay users with little expertise impacts user interaction, emphasizing usability, trust, and literacy to improve user-centered MT development.

Contribution

It analyzes the evolution of non-expert user profiles and highlights key factors influencing their engagement with multilingual systems, guiding more user-centered MT design.

Findings

Identifies usability, trust, and literacy as central to user interactions.

Highlights the shift in user engagement with LLM-powered MT.

Provides interdisciplinary insights for improving user-centered MT.

Abstract

Converging societal and technical factors have transformed language technologies into user-facing applications used by the general public across languages. Machine Translation (MT) has become a global tool, with cross-lingual services now also supported by dialogue systems powered by multilingual Large Language Models (LLMs). Widespread accessibility has extended MT's reach to a vast base of lay users, many with little to no expertise in the languages or the technology itself. And yet, the understanding of MT consumed by such a diverse group of users -- their needs, experiences, and interactions with multilingual systems -- remains limited. In our position paper, we first trace the evolution of MT user profiles, focusing on non-experts and how their engagement with technology may shift with the rise of LLMs. Building on an interdisciplinary body of work, we identify three factors -- usability, trust, and literacy -- that are central to shaping user interactions and must be addressed to align MT with user needs. By examining these dimensions, we provide insights to guide the progress of more user-centered MT.