Contextualizing Linguistic and Cultural Diversity in Digital Spaces: Digital Translation Tools and Culturally-Localized Information Design

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Abstract

Translation in digital spaces has been a relevant area of study for over fifty years (Chen and Bao, 2007). The development of Cross-Language Information Retrieval Software (CLIR) allows individuals to search information in one language and get results in a different language. Though CLIR research has been consistently improving, most research is guided by the development of algorithms to measure accuracy in machine translation (Liu, 2007; McCown, et al., 2005). While these algorithms are useful, current digital translation software treats translation as an algorithmic problem, rather than as a culturally- and socially-situated negotiation of meaning. In this paper, I explain how current translation tools, such as Google translate, operate on problematic algorithms that do not account for cultural and linguistic dimensions of translation work. In addition, I provide strategies for re-designing translation software that contextualizes linguistic and cultural diversity in digital spaces.

Author

• Laura Gonzales, Michigan State U