Localization
After a worldwide journey looking for questions and answers about the localization future, Translated concluded its series of meetings at its headquarters, bringing together localization professionals, translators, and academics to discuss the future of localization and AI. Despite ongoing fears and paradoxes in the industry, the event facilitated deep discussions on several key topics.
Participants proposed and selected 4 main topics:
- The Emergence of the Global South
- Storytelling in the Localization Industry
- Localization Tools
- Translators in an AI Context
Key Highlights
1. The Emergence of the Global South
“It’s not just languages. Africa has 2000 languages. India has 200. You can’t do all of them. So, there’s a process of which ones do we do? And why do we do them? That’s what preparation means. To understand what can be done, what needs to be done, and how.”
- As the world shifts from G7 to G20 and BRIC dominance, the Global South’s rapid economic growth demands attention.
- Localization strategies must adapt to new data and cultural dynamics, moving beyond a focus on China, Japan, and Korea.
- Collaboration and understanding local needs are crucial for effective engagement and infrastructure development.
2. Storytelling in the Localization Industry
“Storytelling is not the term narrative. To me, narrative is like allowing you to control something. Storytelling, I’m inviting you to be engaged and inviting you to listen to my story.”
- The narrative around AI is often fear-driven, but the true focus should remain on enhancing human communication.
- The industry’s relevance lies in its ability to facilitate understanding and connection across cultures.
- Bridging the gap between decision-makers and linguists can highlight the continuous need for skilled professionals.
3. Localization tools
“It’s important to organize and manage linguistic assets. Yeah. The current technology is based on an old segmentation driven text matching algorithm, which is now 30, 40, 50 years old. I think that that is something we should question. Yeah. So are there better ways to organize linguistic data? Linguistic data today can mean translation memory, can mean lists of glossaries, can mean dictionaries, can mean massive amounts of monolingual data. It can mean social media data.”
- While Translation Management Systems (TMS) are essential, they must evolve to handle increasing data complexity and integrate seamlessly with various platforms.
- A headless TMS could offer more flexibility, combining the best features of different tools in one system.
- Encouraging companies to adopt these changes involves demonstrating the business opportunities and improved efficiency.
4. Translators in an AI Context
“If you are open to change and adapt, then you’ll always be needed. If you don’t want to change and adapt, that’s fine. And then you do something else. So I think we all educate humanity and inspire them to this higher vision of why we exist. So I think we should care at the end of the day.”
- Translators must evolve with technological advancements to remain relevant.
- The human touch in translation, including cultural comprehension and quality checks, remains invaluable.
- Modernizing translation studies curricula to include digital skills and AI understanding is vital for future success.
- Embracing new technology can significantly boost productivity and income, presenting new opportunities for the next generation of translators.