Machine translation (MT) has revolutionised communication, what was seen as language barriers in the past have now been broken down by automated translation, but the ethics of machine translation require careful consideration.
One of the most pressing concerns is accuracy. Rule-based machine translation relies on linguistic rules and bilingual dictionaries, which can affect accuracy if the source text contains errors or uses words that are not present in the built-in dictionaries.
Imagine a crucial medical report with a mistranslated side effect, potentially impacting a patient’s treatment. This underscores the need for trust and transparency in machine translation use.
Neural machine translation, which uses neural networks inspired by the human brain, offers advantages in handling nuances and cultural references, improving the overall quality of translations. Users need to be aware of the limitations and mitigate these with post-editing human expertise for critical content.
At the heart of machine translation lies artificial intelligence, a field where ethics is an ever-present discussion. Microsoft’s AI principles emphasise fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability.
Machine learning algorithms are used to improve the accuracy and efficiency of machine translation by analysing translations and making intelligent predictions.
These principles guide the responsible deployment of AI, including machine translation, to avoid perpetuating biases or making unjust decisions based on language processing.
There is a flood of bad machine translations, and it has a serious impact on AI training models.
IBM Research reveals that 90% of all data has been generated in the last two years alone, with a significant portion fed into developing smarter AI. But where does this data come from, and who owns it? When confidential information is processed through machine translation, the risk of data breaches looms large.
Note: Ensure that the translation service providers that manage sensitive data has ISO:27001 certified security controls in place to protect information.
Data protection is a major ethical concern. The General Data Protection Regulation (GDPR) of the EU, which aims to give individuals control over their personal data, has set a global precedent.
Violations can lead to hefty fines, as seen in cases like Google’s €50 million penalty in France for GDPR breaches. This legislation underscores the importance of using machine translation solutions that comply with data protection laws, especially when handling personal or proprietary information.
The future of machine translation lies in responsible development and ethical use. As businesses and individuals, we must be vigilant in demanding transparency, advocating for secure and ethical practices, and ensuring that the tools we use also respect our values and protect our data.
Find out how to choose the best machine translation software in 2024.
Machine translation is not a replacement of human expertise but a collaboration. Human translators can post-edit machine translations this is recommended to ensure accuracy and cultural sensitivity. Human translators play a vital role in post-editing to guarantee high-quality, accurate, and culturally relevant translations.
As the world is discovering with new AI products like Microsoft’s Copilot, human-machine collaboration is the secret to fostering trust and understanding across the globe.
The benefits of machine translation tools in improving translation quality are undeniable, though challenges remain in specialised fields like law, engineering and medical where verified datasets may not be available to train the solution.