Freelance Translators Face Existential Crisis Amid AI Boom: should they adapt or make a career change?
A new survey has reiterated what many working in the freelance translation industry have feared
Half of all freelance linguists have considered abandoning their profession due to the rapid advancements in AI translation tools, according to a report conducted by industry news outlet Slator.
The findings paints a stark picture of the challenges faced by these professionals as they grapple with the growing capabilities of machine translation. However, researchers in Spain are seeing a silver lining in all of this upheaval.
AI’s Impact on the Language Industry: Linguists Adapt or Exit
While AI continues to disrupt numerous sectors, freelance translators appear particularly vulnerable. The survey findings suggest that many are struggling to compete with increasingly sophisticated AI models, leading to a widespread sense of uncertainty about their future prospects. However, this report also highlights a silver lining, suggesting that freelance linguists can leverage their unique skills and linguistic talents in alternative roles, such as language consultants, data annotators, and cultural mediators.
The survey by Slator paints a vivid picture of the shifting landscape for language professionals in the age of AI. With traditional translation and interpretation tasks facing decreasing demand, linguists are finding themselves at a crossroads – adapt or consider a career change.
The survey, which polled 260 linguists, revealed that more than half of freelance translators experienced a decline in requests for their services over the past year. AI was cited as the primary culprit behind this trend, with the majority believing the impact will intensify over the next five years. The data further showed one in five freelance translators and interpreters are actively seeking new jobs.
While the demand for traditional linguistic services is dwindling, new opportunities are emerging. AI-related tasks such as prompting, terminology management, and data annotation for training LLMs are increasingly sought after. To stay relevant, linguists are upskilling; a third have acquired new AI skills in the past year, and nearly half have expanded their subject matter expertise.
However, the transition isn’t seamless. Over 50% of freelance translators and interpreters have contemplated a career switch, either within or outside the language industry. Those specialising in Professional Services, Technology, and Life Sciences seem particularly inclined towards exploring alternative career paths.
Today, the post-editing of machine translations is the second-most sought-after skill among language service providers and is the task with the greatest growth potential.
European Language Industry Survey
New research says AI can empower translators
A groundbreaking report from the Universitat Oberta de Catalunya (UOC), reveals a transformative shift in the translation industry. Far from replacing human translators, AI is emerging as a powerful tool, enhancing efficiency and productivity.
The study explores the evolving relationship between human translators and AI, showcasing how machine translation, once seen as a threat, is now being embraced as an invaluable asset. AI is proving particularly helpful in streamlining repetitive tasks, allowing translators to focus on the more nuanced aspects of their work.
Today, the post-editing of machine translations is the second-most sought-after skill among language service providers and is the task with the greatest growth potential, according to the European Language Industry Survey.
We have concluded that there is no direct relationship between what automated quality assessment metrics say and the actual post-editing effort involved,” said Oliver. “We therefore felt that there was a need to add a further step to the quality assessment system.
UOC report researchers
The UOC report said, “Translators edit unprocessed machine translations, correcting texts produced by artificial intelligence. This brings with it many advantages for human translators, but also significant problems if the quality of the machine translation is poor. This is why the ability to objectively assess the quality of machine translation tools is essential for the sector.”
Two researchers from the Universitat Oberta de Catalunya (UOC), Antoni Oliver, member of the Interinstitutional Research Group in Linguistic Applications (GRIAL-UOC), coordinator of the TAN-IBE project and member of the UOC’s Faculty of Arts and Humanities, and Sergi Álvarez-Vidal, a fellow GRIAL-UOC researcher, have developed a new method for assessing work by AI to improve translators’ work, boosting their capabilities with the potential of machine translation, and enhancing the quality of the end result for all users.
“We have concluded that there is no direct relationship between what automated quality assessment metrics say and the actual post-editing effort involved,” said Oliver. “We therefore felt that there was a need to add a further step to the quality assessment system.”
New post-editing software for translators
The researchers suggest complementing automated assessment systems with another programme that helps evaluate the actual effort put into post-editing. This will allow companies to choose an AI tool that actually increases the efficiency of the translation process.
“We have added a further step: translators translate a sample of the machine translation with a special programme we have developed. This allows us to gather a range of data and decide whether the effort made by the translators is less than that with other systems,” explains Álvarez-Vidal. “If it is less, it means that this machine translation tool works for the translation company’s workflow.”
Machine translation is a common tool in the translation industry, but human review remains essential. Post-editors refine machine output by making corrections, amendments, or even rejecting it entirely.
Oliver highlights the central question, “Who’s truly in charge here: the human post-editor or the AI system?”
The researchers stress that machine translation quality directly affects post-editors. Higher-quality machine translations make post-editing faster and easier, while lower-quality machine translations increase the risk of errors slipping through and raise the time and cost of post-editing. Oliver succinctly states, “Quality in machine translation is crucial for effective post-editing.”
The report highlights several key benefits of this human-AI collaboration:
- Increased Productivity: AI can rapidly translate large volumes of text, significantly reducing turnaround times.
- Improved Accuracy: Machine translation algorithms are constantly learning and improving, leading to more accurate translations.
- Enhanced Consistency: AI can ensure consistent terminology and style throughout a document.
However, AI is not a panacea. Human translators remain essential for complex texts requiring cultural sensitivity and in-depth understanding of specialised fields.
The UOC report paints an optimistic picture of the future of translation. AI is revolutionising the industry, empowering translators to work smarter, not harder.