Human vs. machine | cHAPTER 5

Merging Machine
Efficiency with
Human Insight

The stakes are always high for localization in the life sciences industry. However, balancing speed, accuracy, and cost is a constant challenge.

While other industries must also balance speed, accuracy, and cost in localizing content, life sciences organizations face unique challenges.

Advancements in AI and neural machine translation (NMT) technologies have significantly improved the quality of machine-generated translations.

Despite AI advancements, human translators remain irreplaceable. Localization requires a nuanced understanding of languages and cultural sensitivity, which AI is not (yet) capable of.

The decision between machine and human translation hinges on balancing speed, accuracy, and cost.

The landscape of translation technologies is constantly evolving. Advancements in AI, machine learning, and NMT will continue to refine the quality and capabilities of machine translation.

The decision between machine and human translation hinges on balancing speed, accuracy, and cost. As the life sciences industry introduces communication solutions, such as multilingual chatbots for patient engagement, or faces the demands for swift pharmacovigilance translations to meet regulatory requirements, integrating technology and human expertise becomes critical.

The most effective approach is a strategic blend of human and machine expertise. This hybrid model leverages the strengths of both AI for initial drafts and human review for final revisions.

MT can handle the initial translation of large data sets, providing a solid foundation for further refinement. Human translators then meticulously review and refine the machine-generated translations, ensuring accuracy, fluency, and appropriateness.

The impact of AI is not only in automated translations but also in streamlining processes. For instance, AI is already being used in translation quality assessment and work routing, determining which translated output requires further human review and which does not.

Organizations can optimize their translation efforts by implementing configurable workflows integrating machine translation with human review processes. This ensures that critical information is accurately and swiftly conveyed, supporting timely decision-making and effective communication across the global life sciences landscape.

GenAI is even more powerful because it enables translation directly within authoring environments. Content platforms like Microsoft Office, Adobe, and WordPress embed LLM-enabled co-pilots that can automatically create and translate content simultaneously.

Instead of a linear workflow wherein translation follows content creation, this can now be done in parallel. This cuts down processing times and allows human translators to focus on reviewing and editing AI-translated content.

The decision to leverage machine or human translation is not mutually exclusive but a strategic choice based on project requirements. A hybrid approach is better because it allows life sciences organizations to balance high-quality translations, swift turnaround times, and cost-effectiveness.

Leveraging AI for initial drafts reduces reliance on human translation, saving costs. Human expertise refines AI-translated output, ensuring accuracy. Human translators understand cultural nuances better, guaranteeing content resonates with global audiences. At the same time, human oversight in the translation process also ensures adherence to stringent regulatory requirements in the life sciences industry.

“Welocalize has built a state-of-the-art AI platform, enabling rapid deployment of tailored solutions like custom MT, AIQE, LLM-based revisions, and error detection for each client. Achieving top-notch localization means matching the right AI models and human expertise to the specific content and program needs. Our approach ensures client-specific solutions while maintaining high-volume capacity, enterprise-grade engineering standards, and efficient turnaround times”
Mikaela Grace, Head of AI/ML Engineering, Welocalize

By combining AI’s speed with human expertise in linguistic nuances and cultural context, companies can deliver patient-facing materials that resonate with global audiences, fostering better healthcare outcomes.