Top Three Pros and Cons of Using AI in Medical Translations
In today’s rapidly evolving world of medical and clinical research, the need for precise and reliable translation services is greater than ever. Our blog, “Making Medical Translation A Differentiating Factor For Successful Clinical Trials,” explores this issue in greater detail.
With recent advances in artificial intelligence (AI), the landscape of medical translation has continued to evolve. Generative AI technologies can offer greater consistency and speed, while AI-powered translation and machine translation (MT) can help process large volumes of routine scientific content, including clinical trial documents, research papers, and regulatory submissions.
While there are clear benefits to this emerging technology, clinical researchers also need to understand its potential limitations. In this article, we’ll look at three of the most important pros and cons of using AI for medical and clinical research translation.
AI Clinical Research Materials Translation: The Pros
Increased Speed & Productivity
Since the COVID-19 pandemic, the sheer amount of clinical information generated has significantly increased in the globalized medical field. AI has proven indispensable for analyzing this data, making medical texts available in multiple languages in very short timeframes.
AI tools such as ChatGPT can extract keywords from text and complete translations for each term, automatically adding hundreds of terms that would have taken a translator months to complete if done by hand.
Cost Efficiency
Cost efficiency is an expected outcome of any automation process, and this is true for medical language translation as well. By implementing automated translation systems, companies can optimize their translation processes and save costs.
But cost alone should not be the only criterion when choosing an AI translation. It is essential to consider the limitations and challenges associated with these systems and the ultimate value they provide.
Availability
AI-powered translation and machine translation rely on automated processes rather than human availability. These tools leverage always-on algorithms to review and process language and, as such, are available 24/7.
In the case of medical-specific language translators, the tools analyze each sentence from a medical terminology perspective, returning translations that fit the common medical vernacular.
AI Clinical Research Materials Translation: The Cons
Accuracy
While AI medical translation tools excel at handling straightforward medical terminology, they can have a hard time with more complex content.
Translating localized medical expressions, emerging technologies and processes, or complex clinical protocol language can be more challenging. In these cases, AI may miss context or interpret specialized terminology incorrectly, leading to inaccuracies in the translated material.
Lack of Nuance and Context
Medical translations involve complex concepts and specialized terminology, which can vary depending on where you are in the world.
For example, take the French word “intoxication”, which is considered to mean “poisoning”. In English, the same word refers to a state of inebriation from consuming too much alcohol.
AI translators can face similar difficulties with the abbreviations, acronyms, and shorthand used throughout medical literature and progress notes, where meaning can depend heavily on context.
Quality Control
Generative AI can use prior translated content as context for new translations. In clinical research, however, patient safety makes expert human oversight essential.
Medical professionals and other subject matter experts (SMEs) bring the depth of scientific, medical, and technical knowledge needed to identify issues AI may miss and help maintain a high standard of translation quality.
When AI Makes Sense for Medical Translation
The advantages and limitations of AI become more useful when they’re considered in the context of the material being translated. Speed, volume, and cost may support greater use of automation, while complexity, patient impact, regulatory requirements, and the need for precise terminology can increase the importance of human review.
| Consideration | Where AI can add value | Where human expertise matters |
|---|---|---|
| Speed and volume | Processes large amounts of content quickly and efficiently | Reviews output when faster turnaround cannot come at the expense of meaning or accuracy |
| Terminology and context | Handles recurring or straightforward language efficiently | Interprets specialized terminology, nuance, abbreviations, and context |
| Content risk | Can support appropriate lower-risk or routine materials | Becomes increasingly important for patient-facing, clinical, or other higher-risk content |
| Quality control | Reduces repetitive translation work | Identifies errors, resolves ambiguity, and applies scientific and medical subject matter expertise |
Frequently Asked Questions
What are the main benefits of using AI for medical translation?
AI can improve speed, efficiency, and scalability, particularly when large volumes of routine or repetitive content need to be translated. It can also reduce some of the manual work involved in processing terminology and recurring language.
What are the main risks of AI medical translation?
AI can miss context, interpret specialized terminology incorrectly, or produce fluent language that changes the intended meaning. Those risks become more important as the content becomes more complex, patient-facing, regulated, or clinically significant.
Is AI better than human translation for medical content?
Not in every situation. AI can be useful for speed and volume, while human linguists and subject matter experts bring the contextual and technical judgment needed for more complex or higher-risk content.
When is AI most useful in medical translation?
AI can be especially useful for routine, repetitive, or high-volume content where automation can improve efficiency. The appropriate workflow still depends on the content, its intended use, and the level of review required.
When should medical translation rely more heavily on human expertise?
Greater human involvement may be appropriate when the material contains complex medical terminology, ambiguous language, patient-facing instructions, regulatory content, or other information where an error could have significant consequences.
Can machine translation handle medical terminology?
Machine translation (MT) can handle many common or recurring terms, but performance can vary depending on the language pair, subject matter, and context. Specialized terminology, abbreviations, and emerging medical concepts may require expert review.
Does AI medical translation still need quality control?
Yes. Quality control helps identify problems with terminology, context, factual meaning, and consistency that automated systems may not recognize reliably on their own.
Can AI help with large volumes of clinical research materials?
Yes. AI-powered translation can help process large volumes of clinical trial documents, research materials, and other recurring content more efficiently. Human review can then be applied according to the complexity and risk of the material.
Can AI reduce the cost of medical translation?
Automation can reduce some of the manual work involved in translation and improve efficiency, which may lower costs in appropriate workflows. Cost should still be considered alongside quality, risk, intended use, and review requirements.
How should organizations decide whether to use AI for medical translation?
The decision should consider the type of content, its audience and intended use, the consequences of an error, the volume and timeline, and the level of expert review required. The goal is to use AI where it adds practical value without removing the human expertise the content still needs.
Explore Language Scientific’s Approach to AI Medical Translation
AI translation capabilities in the medical field continue to grow rapidly, offering greater speed, consistency, and efficiency while reducing costs in appropriate workflows. But when patient health and clinically significant content are involved, AI and machine-learning technologies should be paired with experienced SME oversight.
Language Scientific has developed an AI-optimized approach to translation. Our translation methodology combines AI technology with human-driven quality control, cross-checks, and client interaction to support both technical precision and the nuances of medical terminology.
Learn more about Language Scientific’s AI-optimized translation services or contact us to discuss your translation needs.
