Marco Simões, a 64-year-old freelance translator and university teacher in São Paulo, Brazil, has witnessed firsthand how AI is transforming the translation industry while maintaining that human expertise remains irreplaceable. Working with Lilt, a translation service that integrates AI into its platform, Simões has seen his productivity skyrocket from translating 260-300 words per hour with manual methods to an impressive 1,000-1,200 words per hour using AI-powered tools.
Simões began his translation career in 2015 after spending years in IT instruction for companies like Novell and Intel, where he translated technical materials from English to Portuguese. Initially working with WinTranslation using traditional methods and occasional Google Translate assistance, he transitioned to Lilt in 2020, which employs computer-aided translation (CAT) technology. The platform’s AI generates translated sentences first, which human translators then review and refine before submission.
The translator now supplements Lilt’s internal AI with tools like ChatGPT and Bard for research and problem-solving. He cites examples where AI dramatically reduced research time—what once took 15 minutes to understand specialized terminology like “revolver” in financial contexts now takes seconds. However, Simões emphasizes that AI has significant limitations. He discovered ChatGPT provided only the metaphorical meaning of the Brazilian expression “plantar bananeira” (to do a handstand) without explaining its literal translation (to plant a banana tree), demonstrating how AI can miss crucial contextual nuances.
Despite increased productivity, Simões notes that higher output doesn’t necessarily mean higher pay, as compensation depends on whether translators are paid hourly or per word. He describes the evolving role of translators as “facilitators of technology” rather than being replaced by it. The AI learns from human corrections over time, requiring fewer adjustments as it adapts to client styles and preferences.
Simões maintains that certain translation types—particularly poetry and highly artistic works—remain beyond AI’s capabilities due to language’s inherent complexity, including irony, humor, and cultural nuances. He expresses concern about younger generations using AI before developing critical thinking skills, emphasizing the need for responsible AI adoption. His perspective: AI is an indispensable tool for high-volume technical translation, but human intervention remains essential for quality, accuracy, and capturing the living, evolving nature of language.
Key Quotes
With the introduction of AI tools, it’s now possible to translate as many as 1,200 words an hour, and my workflow has improved massively.
Marco Simões describes the dramatic productivity increase from using AI translation tools compared to his previous manual translation rate of 260-300 words per hour, demonstrating a roughly 400% improvement in output.
We are becoming facilitators of technology. Using AI makes me more creative.
Simões explains how the translator’s role is evolving rather than disappearing, with AI serving as a tool that enhances creativity by offering new perspectives when translators feel stuck, rather than simply automating their work away.
I don’t think it’s possible that AI will replace human translators because language is alive. There are complexities, nuances, and layers of language.
The veteran translator articulates why human expertise remains essential despite AI’s capabilities, pointing to language’s dynamic nature and the cultural, contextual, and creative elements that AI cannot fully grasp.
As a teacher, I worry about young people using it before developing critical thinking skills. It’s not so much whether AI is beneficial, but whether the future generation is prepared to use it responsibly.
Simões raises concerns about AI adoption without proper foundational skills, highlighting a broader societal challenge about ensuring people develop the judgment necessary to use AI tools effectively and critically.
Our Take
Simões’ experience perfectly illustrates the “centaur model” of human-AI collaboration that’s emerging across knowledge work sectors. His 400% productivity gain demonstrates AI’s transformative potential, yet his emphasis on human oversight reveals why complete automation remains elusive. The translation industry is particularly instructive because language work requires both mechanical pattern recognition—where AI excels—and cultural intelligence, where humans remain superior.
What’s especially noteworthy is his observation about compensation not keeping pace with productivity gains. This suggests AI may create a “productivity trap” where workers must adopt AI tools to remain competitive, but increased output doesn’t translate to proportional income growth. This dynamic could reshape labor economics across industries.
His concerns about critical thinking skills highlight a crucial challenge: we’re deploying powerful AI tools faster than we’re developing the judgment to use them wisely. The translation field’s evolution suggests the future belongs not to those who resist AI or blindly embrace it, but to professionals who develop sophisticated AI literacy—knowing when to trust AI, when to question it, and how to leverage it creatively.
Why This Matters
This firsthand account from a working translator provides crucial insights into AI’s real-world impact on knowledge workers and challenges both utopian and dystopian narratives about AI replacing human jobs. Simões’ experience demonstrates a more nuanced reality: AI augments rather than replaces skilled professionals, increasing productivity by 400% while simultaneously highlighting irreplaceable human capabilities.
The translation industry serves as a bellwether for AI’s broader impact across white-collar professions. As generative AI tools like ChatGPT and specialized platforms like Lilt become ubiquitous, professionals across industries face similar questions about adaptation versus obsolescence. Simões’ embrace of AI while maintaining critical oversight offers a blueprint for successful human-AI collaboration.
His concerns about compensation structures—where increased productivity doesn’t guarantee higher pay—raise important questions about how AI’s economic benefits are distributed. This story also underscores the importance of developing AI literacy and critical thinking skills before widespread adoption, particularly among younger workers. As AI continues advancing, the translation industry’s evolution suggests that jobs requiring cultural understanding, contextual judgment, and creative problem-solving will remain fundamentally human, even as AI handles routine aspects of the work.
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Source: https://www.businessinsider.com/language-translator-uses-ai-wont-replace-adapt-2024-10