Is AI Transforming Language Professions? Exploring the Impact on Translators and Interpreters
As a language student back in 2012, I was reassured that technology was not going to replace translators, interpreters, and other language professionals. There was no way machines could connect ideas like the human brain does. Little did we know that just a year later, neural machine translation (NMT) would begin revolutionizing the language industry. In 2018, Microsoft researchers boldly claimed that human-machine parity in translation had been achieved. Of course, they were referring to a specific language pair and set of texts. Nonetheless, they brought massive attention to the capabilities of these engines and the possibility of integrating them into a translator’s workflow. For many, this was a welcome change, while for others it was seen as an atrocious crime against our profession.
More recently, 2022 marked a definitive revolution in the language industry, with artificial intelligence (AI) incorporating millions of data points into large language models, making them “almost as smart as humans.”
People have learned to work with these systems for countless applications, including translation and interpreting. Most individuals now travel the world with ChatGPT or the Google Translate app on their phones, allowing them to communicate with almost anyone in hundreds of different languages. However, there are still roles that only humans can fulfill. Let’s dive into the capabilities and limitations of AI in serving language-related tasks.
Capabilities of AI in Language Tasks:
Speed and Efficiency: LLMs can process vast amounts of text and speech in a fraction of the time it would take a human. Whether it’s translating documents, interpreting real-time conversations, or generating content, AI-driven systems make rapid language processing possible with just a few clicks.
Handling Multiple Languages: AI language tools support hundreds of languages, making them indispensable for global communication. A single app can handle dozens of language pairs, providing a level of accessibility that was unthinkable just a decade ago, whether for written or spoken interactions.
Constant Learning and Improvement: Thanks to machine learning, AI-based language systems continuously learn from new data. This means that over time, they adapt and improve, refining their ability to little by little understand nuances, idiomatic expressions, and even specialized jargon across various language-related tasks.
Cost-Effectiveness: AI-powered language services drastically reduce the cost of translation and interpreting, especially for businesses that need to process large volumes of content or require real-time communication. Hiring a team of human translators and interpreters for such tasks would be far more expensive.
Automated Multimodal Capabilities: AI doesn’t just handle written text— tools like Speech-to-Text and Text-to-Speech (such as Microsoft’s Translator, Google’s Speech Recognition, or Interprefy Connect Pro) enable real-time spoken language translation, breaking down barriers in conversations between people who don’t share a common language.
Limitations of AI in Language Tasks:
Lack of Cultural and Contextual Understanding: While AI systems are fast, they often lack the deep cultural understanding that human translators and interpreters bring. AI can process the words, but it struggles with the broader context, tone, and regional variations in meaning, leading to awkward or incorrect results in both written translations and live AI speech translation.
Inconsistent Accuracy with Complex Texts or Speech: For straightforward, literal tasks, AI works well. However, when dealing with too complex, nuanced, or highly specialized content—such as legal documents, medical interpreting, or literary works—accuracy drops significantly. AI still has a long way to go in capturing subtle meanings, implied tones, and the spontaneity needed for real-time interpreting.
Over-Reliance on Training Data: AI systems are only as good as the data they are trained on. If the training data of a specific system lacks diversity or contains biases, the output will reflect that. This can result in misinterpretations or biased results, whether in written translations or spoken interactions, especially in certain language pairs or cultural contexts.
Inability to Convey Emotion and Intent: AI cannot fully grasp or convey human emotions or intent behind words. Sarcasm, humor, and idiomatic expressions often get lost in translation or interpretation. While AI can process the literal meaning, it misses the subtleties that a human translator or interpreter would instantly understand and convey.
Human Expertise Still Needed for High-Stakes Language Tasks: For legal, medical, or diplomatic communication, where precision and nuance are crucial, human oversight remains irreplaceable. AI can assist in speeding up the process, but final decisions, interpretations, and revisions must be handled by skilled professionals to ensure accuracy in high-stakes scenarios.
In short, while neural networks and AI have brought tremendous improvements to the field of language studies, there are still limitations that only human expertise can overcome. It’s about finding the right balance between using technology for efficiency and knowing when human intervention is needed.
Regarding language professionals, there is still hope. We are still very much needed, and new career opportunities are opening up for us. However, AI is definitely changing the game. On one hand, many language study programs are now combining language and technology to explore how to better use these systems and even train them for improved accuracy and performance. On the other hand, language specialists are diversifying their expertise, branching into fields like programming, marketing, or sales— demonstrating that our linguistic skills, coupled with deep multilingual and multicultural knowledge, make us invaluable in industries beyond translation and interpreting. This is the path I’m personally taking. By leveraging my language background, I am venturing into marketing, which allows me to apply my skills in new and rewarding ways.