The Role and Importance of AI and Machine Learning in Translation
Look at the news and it’s hard to deny that AI is making an impact. AI contributed £3.7 billion to the UK economy in 2022, and the number of AI companies has increased by 688% in the last decade. The technology looks set to transform myriad industries, and, if the transition is not managed well, dire warnings follow about the impact on human workers: the UK Government estimates that 7% of existing UK jobs could be displaced by AI in the coming years.
With translation being one of many industries where AI and machine learning stand poised to make a significant impact, we thought it prudent to explore the role and importance of AI and machine learning in translation. Our focus is explaining how the two fit together, the potential benefits on offer, and what you need to know when making decisions about translation services.
Here’s what we’ll cover in this blog post:
- How AI and machine learning can be used in translation
- The potential benefits each can bring
- Their potential drawbacks
- How to use AI and machine learning responsibly and effectively
- Factors to consider when incorporating AI and machine learning into your translation workflow
How AI and machine learning can be used in translation
To set the scene, let’s first look at some ways that AI and machine learning can be used in a translation context. This is helpful in understanding the real-world applications for these technologies.
- Real-time translation: AI tools can ‘listen’ to audio and translate it near-instantly, which can be a boon in video conferences and other similar contexts.
- Website localisation: by integrating with a website CMS, an AI can translate product descriptions into multiple languages at great speed.
- Customer support chat bots: AI-powered chat bots are already in use, and are a great way to triage user queries. These can also function in multiple languages, making translation in a customer support context more effective.
- Subtitling: AI algorithms can create subtitles in multiple languages, expanding the reach of TV and other visual media.
- Education tools: AI can potentially revolutionise education by personalising learning paths based on an individual’s progress, learning style, and other factors.
In each of these contexts, it’s easy to see the value that human collaboration or oversight would bring. This is a key theme that we will explore in later sections, but first let’s take a look at some of the broader benefits of AI and machine learning in translation.
The potential benefits of AI and machine learning in translation
The future of translation almost definitely includes AI and machine learning in some capacity, for several reasons:
- These technologies can process large amounts of text at speeds way beyond what a human translator can achieve, leading to greater procedural efficiency.
- AI could lead to good cost savings, despite high initial setup costs. This is especially true in the context of repetitive tasks.
- The technologies lend themselves to workflows and processes where humans remain involved for oversight and quality control purposes, while also reducing their overall workload.
- AI and machine learning algorithms are incredibly adaptable and can be trained on language relevant to specific industries, or even specific companies. This makes output increasingly sophisticated and relevant over time.
- These technologies promote greater accessibility by making it easier to provide text- and potentially audio-based communications with which users with accessibility needs can engage.
The potential drawbacks of AI and machine learning in translation
There are also drawbacks to be aware of, and building a balanced understanding of the technology is helpful in understanding its application. Here are some things to be aware of:
- AI and machine learning does not have the human touch. While this is hard to precisely articulate, you can sometimes ‘feel’ when text is AI generated (although this may become more difficult over time as the technologies improve).
- The technology is prone to produce errors, whether syntactical or in terms of linguistic nuance. AI hallucinations (i.e. AI making up an answer) are a well documented issue.
- AI and machine learning tools may present security challenges to organisations who must demonstrate compliance with data protection legislation like GDPR and similar. Just like with well-known public machine translation services, data is not guaranteed to be kept confidential.
How to use AI and machine learning responsibly and effectively
Balancing the benefits and the drawbacks allows a measured approach to AI and machine learning and translation. If you are considering incorporating these tools into your translation workflows, we recommend considering the following factors:
- Maintain human oversight: this allows you to leverage that human touch, to monitor output for errors, and to tweak output to be more aligned with brand tone of voice where necessary.
- Prioritise specialised engines: specialised translation engines bring the benefit of having been trained on language that is closer in relevance to your industry than a general engine will have been. In theory this means a more accurate, higher quality translation.
- Consider data security: make sure that any AI or machine learning tools are compliant with all relevant processes and legislation – data security and otherwise – before you begin using them.
Factors to consider when incorporating AI and machine learning into your translation workflow
With the above in mind, let’s now take a look at the options for incorporating AI and machine learning into translation workflows. We will also explore working solely with human translators as a comparative baseline.
Working solely with specialist human translators
Until recent years, this was the only option available. Specialist human translators build a bank of knowledge and expertise in one or more industries, and combine this with high levels of proficiency in multiple languages to create high quality, accurate translations in their area(s) of expertise.
The key benefits of this approach:
- Human translators understand cultural sensitivity, context, and nuance very effectively, and can incorporate these into their output
- Human translators can guarantee confidentiality and security for sensitive materials
- Human translators are responsive and can maintain ongoing communication throughout the translation project, allowing for course correction
- The human output is higher quality as it is fact-checked and adapted to the target audience
The main drawbacks of this approach:
- Human translators take longer than machines to translate, especially when high volumes of material are being translated
- Human translators cost more because of this increased time commitment
Working with specialist human translators who use AI and machine learning tools
This hybrid approach is becoming more common as technologies continue to increase in sophistication, but with organisations keen, at the same time, to temper these novel technological solutions with the tried-and-tested human approach.
The key benefits of this approach:
- AI translation with human input and oversight allows for time and efficiency savings while ensuring that cultural sensitivity, context, and nuance are effectively integrated into output
- AI translation with human input allows for ongoing training and improvement of the tools involved, and human agents can check that the direction of movement is correct
- AI translation with human input is flexible, as the contributions of each party can vary depending on the nature and scale of the project
The main drawbacks of this approach:
- While flexibility is a plus, effectively coordinating human and machine tools may present unforeseen complexity, especially in the early stages
- Human agents may not have the required experience or expertise to effectively use the tools, and this may lead to inefficiencies in cost and time
Working solely with AI and machine learning tools
The option exists to rely only on AI and machine learning tools, with minimal input or oversight from human agents. While this may seem appealing on initial inspection, we advise caution in moving ahead with this approach.
The key benefits of this approach:
- AI and machine learning tools are unmatchable by human translators in terms of processing speed
- AI and machine learning tools are likely to be significantly cheaper than human translators once the initial setup costs are taken into account
The main drawbacks of this approach:
- AI and machine learning tools are less capable of incorporating nuance and cultural aspects into their translations
- AI and machine learning tools without human oversight run the risk of not only producing errors, but on becoming trained on the incorrect information that led to these errors, increasing the likelihood of future errors occurring
- With AI, it is easy for users to select the wrong technology if unfamiliar with the different tools
- Despire AI and machine learning tools offering time savings generally, the setup time and costs are often underestimated
The hybrid approach to AI and translation
As you can see from the above, a hybrid approach that combines the strengths of both AI tools and human translators is perhaps the most preferable. This balanced approach allows for greater speed and efficiency, reduced costs, and translations that retain the accuracy and cultural resonances that only a human translator can impart.
To find out more about our translation services and how we employ AI and machine learning in our processes, please get in touch. We would be happy to discuss this with you and address any queries or concerns you have about the role of AI and machine learning in translation.
We also invite you to browse our case studies to get a feel for the type and scale of projects we carry out for clients around the world.
