Languages are vessels of culture. An ethical translator considers cultural nuances, idiomatic expressions, and context. What works in one culture may not resonate in another. Respect for cultural diversity ensures effective communication. Translators must remain neutral. Biases and personal opinions should not color a translation.
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machine translation
Gender Bias in Machine Translation and the Importance of Diversity
In short, artificial Intelligence is a powerful and promising technology that can bring benefits and opportunities to translation, but it also presents risks and challenges that require human attention, care, and action. AI is neither neutral, infallible, nor impartial. It’s a reflection and product of human society, which is complex, dynamic, and diverse, but also has many issues, like discrimination, prejudice, racism, sexism, etc.
Human and machine translators
Human translators can also apply this contextual insight that AI lacks to deal with complex texts, such as legal documents or technical manuals. Humans can interpret ambiguous or idiomatic text by considering the wider context, resulting in a more accurate and faithful translation.
Machine Translation Post-Editing – Part 2
Without a keen eye, we can easily be led to believe at first glance that a sentence makes perfect sense, when in fact its structure is awkward, or it has a glaring translation error that wasn’t easy to detect in a light reading.
Machine Translation Post-Editing – Part 1
The professional’s approach to a full post-editing will obviously be much slower and therefore also more expensive than a light post-editing. The specific project strategy must be adapted to the client’s expectations regarding time, cost, and quality.
Is post-editing a relevant skill?
In the past, it was often easier to work directly from the source text and translate from scratch than to post-edit the usually poorly generated content. But advances in machine translation, mostly driven by the post-edited text being fed back into the engines for learning, now allow for a higher-quality output, and this has been increasing the demand for this service.
The Ethical Compass in Translation
Languages are vessels of culture. An ethical translator considers cultural nuances, idiomatic expressions, and context. What works in one culture may not resonate in another. Respect for cultural diversity ensures effective communication. Translators must remain neutral. Biases and personal opinions should not color a translation.
Gender Bias in Machine Translation and the Importance of Diversity
In short, artificial Intelligence is a powerful and promising technology that can bring benefits and opportunities to translation, but it also presents risks and challenges that require human attention, care, and action. AI is neither neutral, infallible, nor impartial. It’s a reflection and product of human society, which is complex, dynamic, and diverse, but also has many issues, like discrimination, prejudice, racism, sexism, etc.
Human and machine translators
Human translators can also apply this contextual insight that AI lacks to deal with complex texts, such as legal documents or technical manuals. Humans can interpret ambiguous or idiomatic text by considering the wider context, resulting in a more accurate and faithful translation.
Machine Translation Post-Editing – Part 2
Without a keen eye, we can easily be led to believe at first glance that a sentence makes perfect sense, when in fact its structure is awkward, or it has a glaring translation error that wasn’t easy to detect in a light reading.
Machine Translation Post-Editing – Part 1
The professional’s approach to a full post-editing will obviously be much slower and therefore also more expensive than a light post-editing. The specific project strategy must be adapted to the client’s expectations regarding time, cost, and quality.
Is post-editing a relevant skill?
In the past, it was often easier to work directly from the source text and translate from scratch than to post-edit the usually poorly generated content. But advances in machine translation, mostly driven by the post-edited text being fed back into the engines for learning, now allow for a higher-quality output, and this has been increasing the demand for this service.