Machine translation in society: insights from UK users

Abstract

Machine translation (MT) tools like Google Translate can overcome language barriers and increase access to information. These tools also carry risks, and their societal role remains understudied. This article investigates typical uses and perceptions of MT based on a survey of 1200 United Kingdom residents who were representative of the national population in terms of age, sex, and ethnicity. We highlight three main findings from our analysis. First, participants often used MT for non-essential purposes that rarely justified professional human translations. Second, while they were highly satisfied with MT they also expressed desires for higher MT quality. These desires were usually motivated by expectations of perfection rather than fitness for purpose. Third, participants’ future vision for MT involved increasingly blurred boundaries between text and speech. The article calls for more MT research on the interface between written and spoken communication and on the ethical implications of rare but significant high-risk uses of the technology.

Privacy and everyday users of machine translation

“…These factors alone may present more opportunities for privacy concerns to arise in relation to MT tools, though we note that smartphones are not necessarily the most popular MT use device. Our survey in fact suggests that MT is still mostly accessed on laptops and desktops (Vieira et al 2022; see also Table 1).…”

“…We outline the methods pertaining to these two data sources below in Sections 3.1 and 3.2, respectively. Further analysis of the UK survey is provided by Vieira et al (2022), and a link to the survey dataset is available at the end of this article (see Data Availability Statement).…”

Machine translation in everyone’s hands - Adoption and changes among general users of MT

“…This is not an uncommon assumption. In their study, Vieira et al (2022) found that UK-based general users of MT seemed to trust the systems and were satisfied overall with the quality, even though they would ask for better quality when given the chance.…”

Good, but not always Fair: An Evaluation of Gender Bias for three Commercial Machine Translation Systems

“…In 2016, Google Translate was estimated to generate more than 100 billion words per day (Pichai, 2016), and its use has further increased ever since (Pitman, 2021). MT is integrated into e-commerce platforms such as eBay, search engines, and Bahdanau online chats, whereas online MT tools are deployed for a range of use cases by millions of people daily, e.g., for leisure, traveling, or work-related activities (Vieira et al, 2022).…”