GALA Champion Annelise Finegan

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Annelise Finegan is Academic Director of Translation & Interpreting and Clinical Associate Professor of Translation at the NYU School of Professional Studies Center for Applied Liberal Arts. An award-winning translator, she has published translations from Chinese, including novels, short stories, and nonfiction by prominent contemporary and historical authors.

Annelise has worked for academic and textbook publishers as an acquisitions editor, publishing coordinator, bilingual editor, and project manager. She holds a Ph.D. in Comparative Literature from Washington University in St. Louis, where she also earned a Graduate Certificate in Translation Studies.

In this interview we talked about volunteering for the GALA Member Program Committee, and how academia and the localization industry should collaborate to train the next generation of professionals.

Here are a few snippets.

03:14 Volunteering at GALA

For the past 2 years I have been on the Member Program Committee as academic representative, and I couldn't speak more highly of this experience. I recommend it to everyone. It's been a fantastic way to connect with global colleagues. 

GALA has created this thoughtful and intentional model of gathering input and insights about what programs its members seek, how to seek out new members, but also there is expert guidance from its full-time staff.

04:10 Collaboration between the localization industry and the academic world

The most frequent answer to this question is more internships, more practicums. And that is all well and good, but I think we need more. I would like to see many more companies and their hiring practices recognizing that a degree in translation and localization is equivalent to a five year prior employment experience. After all, this is written in the ISO 17:100. There is a real need to recognize the value of the credentials.

05:30 Closing the talent gap 

I do agree there is a talent gap and it is something that I think about every day. I think the talent gap is a micro instance of a macro issue for the language industry.

We need narratives of success that are also realistic to encourage talent to enter the field. It doesn't help that we need to counteract impressions around AI and other technologies that translation and localization will be the first jobs to go with arguments instead of reminders that translation is actually 6 or 7 years ahead of the curve when it comes to incorporating machine learning and AI.