VOSS: Supporting Multilingual Virtual Organizations

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Language choice is a key issue for organizations whose workers are distributed across the world. Allowing everyone to speak their native language and using machine translation tools is an imperfect solution because even the best such tools make many mistakes. However, companies that require all communication to take place in a standard "corporate language" (often English) risk excluding people for whom the corporate language is not their main language, who may feel like second-class members because they fear making mistakes and being judged on their language use. The goal of this project is to better understand and support informal communication in global virtual organizations whose members speak different native languages. Specifically, the research addresses three interrelated questions: (a) What are the experiences of non-native speakers in English-based virtual organizations? (b) What are the benefits and costs of using English as a common language vs. machine translation? (c) How can machine translation be augmented to improve communication? We investigate these questions through a combination of interviews and surveys, controlled laboratory studies, and the development and evaluation of tools that use additional representations of meaning, such as pictures, to smooth gaps in machine translation.Understanding the issues and tradeoffs involved around language choice practices is important both practically, in terms of companies' competitiveness and people's experiences in the workplace, and theoretically, by complementing existing work in psychology and computer-mediated communication on how culture affects relationship-building and teamwork in virtual organizations. This research could help broaden participation of non-native English speakers in virtual organizations leading to increased trust and improved organizational competitiveness. Developing new tools to support existing machine translation approaches will also help individuals and organizations to communicate and collaborate, while contributing to the existing body of literature in language processing, machine translation, and multi-lingual picture retrieval. The research also involves undergraduate and graduate students and will result in their further training and education in interdisciplinary research.