Focus On: Lynne Bowker and Machine Translation Literacy

July 8, 2019

Highlighting research by members of the Canadian library and information management community.

Researcher: Lynne Bowker, PhD

Professor, School of Translation & Interpretation and School of Information Studies, University of Ottawa, and 2019 Researcher-in-Residence, Concordia University Library

What is your research topic?

I have an interdisciplinary background that spans translation, natural language processing, and library and information science. Much of my research lies at the intersection of these fields, including my current project on “machine translation literacy”.

Machine translation has gained prominence in recent years. Who hasn’t used a free online machine translation tool? At first glance, it seems pretty straightforward: open the tool, paste in your text, choose your languages, and click on “Translate”. What could be easier?

But while using a machine translation tool may be easy, using it critically requires some thought. For instance, have you ever considered what happens to the text that you paste into the tool? Maybe you think it just disappears once you close the window? (Spoiler alert: it doesn’t). Confidentiality and privacy are some issues worth thinking about before choosing to use an online machine translation system.

And how reliable are the translations that come out? Recent artificial intelligence-based approaches to machine translation use machine learning. Essentially, the computer program is fed with millions of words of text, and it uses this “training data” to learn how to translate new texts. However, depending on the texts that are used for training, the machine translation system might learn some inappropriate things. For instance, there are reports of AI-based systems that produce texts containing gender or racial bias. It’s important to be aware of such possibilities rather than simply using these systems without thinking. Finally, learning how to prepare texts in a machine-translation friendly way can improve the usability of the translated output, and there are also techniques for post-editing this output to further improve it.

All of these elements, such as thinking about whether, when, why, and how to use machine translation, are part of what I term “machine translation literacy”. It basically comes down to being an informed and critical user of this technology, rather than being someone who just pastes and clicks. The ultimate goal of this project is to propose a program for teaching machine translation literacy as part of a broader digital literacy framework.

What interested you in that topic?

In my job as a professor and researcher, I have noticed that Canada’s higher education system is increasingly attracting international students and faculty, not all of whom have English as a native language. However, English has become the dominant language of scholarly communication. The more interactions that I had with international students, visiting scholars and colleagues at international conferences, the more I began to recognize the additional hurdles faced by these scholars who must both engage with and contribute to the scholarly literature through English.

In conversations with such scholars, I learned that many of them turn to machine translation to help them with their tasks; however, it also became clear that not all users of this technology were aware of the potential risks or of techniques that they could use to optimize the tools’ performance. I therefore witnessed an emerging need for training in machine translation literacy. So my goal is to leverage my expertise in translation technology to help members of the scholarly community – from undergraduates through to full professors – to improve their machine translation literacy so that they can avoid some of the potential pitfalls of this technology while maximizing its strengths.

What impact would you like to see your research have on LIS practitioners?

I believe that academic librarians are well placed to develop and deliver machine translation literacy instruction at academic and research institutions. The need for machine translation literacy is present in every discipline of research enquiry, and the library is an ideal venue for this type of cross-cutting instruction. Moreover, librarians are already experienced in providing instruction in scholarly communication, information literacy, media literacy, and digital literacy, for example, and I see instruction in machine translation literacy as being a logical extension of this type of work. So I’d love to see more academic librarians incorporating machine translation literacy into the training options that they offer to students and faculty.

Furthermore, while my current project focuses on an academic environment, I believe that a machine translation literacy program can be adapted for other groups, such as school kids (e.g. in French immersion programs or English-as-a-second-language courses), or for newcomers to Canada who speak languages other than English or French. I plan to extend the project in this direction and so hope to involve public librarians and school librarians, who will be able to reach these communities and help them to become more informed users of machine translation too.

What emerging topics do you foresee in the future of LIS research?

I’ve read several articles recently which claim that survey-based investigations are over-represented in LIS research and which call for a broader range of methods to be applied. Therefore, I expect that we will see a diversification of research methods being used by LIS researchers. What’s more, given that LIS is a very interdisciplinary field, some of these methods may be borrowed from other disciplines. For instance, I recently wrote an article on how corpus linguistics techniques can be applied to LIS research. Another fun example that has been borrowed from design thinking is using the “Love Letter / Break-up Letter” technique instead of a simple interview or survey. Introducing a wider range of methods will strengthen LIS research by making it easier to triangulate findings, and investigating the same problem using different techniques will lead to a deeper and more holistic understanding of the issue.

What advice would you give to LIS students or practitioners hoping to engage in research?

My current appointment as Researcher-in-Residence at Concordia University Library is precisely intended to foster a culture of research in the library and to promote the use of research by practitioners. I encourage LIS students and practitioners to get in touch – either with me or future occupants of this position, or with people in similar roles elsewhere – to discuss ideas or ask questions about doing research. Consider starting a conversation by leaving a comment below, for instance!

In addition, I would encourage LIS students to look for opportunities to work as a research assistant since this is a great way to be exposed to different elements of a research project under the guidance of a more experienced researcher. For instance, as part of my Researcher-in-Residence project, I have hired two graduate students to work as research assistants on the machine translation literacy project. Many professors offer assistantships to MLIS or PhD students, so keep your eyes open for such opportunities.

Similarly, LIS practitioners who want to explore research should not hesitate to seek collaborative opportunities with colleagues who have research experience, whether these be faculty or other LIS practitioners. Don’t hesitate to request an informational interview with a researcher to find out more about what they do and to see whether you could contribute. There’s nothing a researcher likes more than talking about their research, so don’t be shy about asking them to share their experience!

Select Bibliography

Bowker, L. and Buitrago Ciro, J. (2019) Machine Translation and Global Research: Towards Improved Machine Translation Literacy in the Scholarly Community. Bingley, UK: Emerald.

Bowker, L. (2019) Investigating the participation of business librarians in academic program reviews using corpus-based methods. Journal of Business and Finance Librarianship.

Bowker, L. (2018) Corpus linguistics is not just for linguists: Considering the potential of computer-based corpus methods for library and information science research. Library Hi Tech 36(2): 358-371.

Bowker, L. and Delsey, T. (2016) Translation Studies and Information Science: Adaptation, Collaboration, Integration. In Y. Gambier and L. van Doorslaer (eds.), Border Crossings: Translation Studies and Other Disciplines, 73-96. Amsterdam: John Benjamins.

Bowker, L. and Buitrago Ciro, J. (2015) Investigating the usefulness of machine translation for newcomers at the public library. Translation and Interpreting Studies 10(2): 165-186.