AI Writing
How AI is Transforming Multilingual Content Marketing, Creation, and Translation
Learn how AI is impacting multilingual content marketing, content creation, and translation and how to use it effectively
The rise of AI brought with it extensive possibilities for transforming multilingual content marketing. It offered the potential to write content in a concise, coherent way, and do so in multiple languages.
AI has performed well at understanding languages from a vocabulary and grammatical standpoint. However, like with English text generation, multilingual AI text also faces challenges.
Some of the issues with multilingual AI content include:
When you carry this process, flaws and all, over to multilingual content marketing and multilingual marketing in general, you end up with both benefits and challenges.
So, before you wholeheartedly jump into multilingual content marketing or multilingual content creation using AI, here’s what you need to know.
AI translation tools work similarly to their text-generating counterparts by using machine learning and algorithms to process and convert text from one language to another.
Many well-known translation tools, including Google Translate and DeepL, use neural machine translation (NMT) and neural networks to improve the accuracy of their translations.
According to a study published in Science Direct, with NMT, “translation can be modeled at different levels, such as document-, paragraph-, or sentence-level.” However, the study notes that further research and work needs to be done to improve NMT architecture and incorporate human knowledge into the frameworks.
There are several potential issues that AI multilingual content translation can pose in general and in content marketing.
If you’re translating multilingual content, you may notice your content being flagged as AI. When you use an AI translator, even when the original source material was written by humans, the translation is generated by AI. In this case, an AI detector could detect the content as AI because the translated text was generated by an AI-powered tool.
Interested in learning more about AI detection? Read our guide on AI detection accuracy, a meta-analysis of third-party AI detection studies, and our article on false positives.
AI often repeats itself and uses the same specific words and phrases where a human would have chosen something more nuanced.
Note: Studies have found that ChatGPT is harder to detect than you might think. Many of the words and phrases that ChatGPT uses are surprisingly common, such as ‘but a’ or ‘on the other hand.’
As an example, in Catalan, ‘Va començar a ploure a bots i barrals,’ may be translated by AI to read ‘it started to rain buckets and barrels’ instead of the more idiomatic ‘it started to rain cats and dogs.’
For all its sophistication and polish, AI still makes mistakes, particularly when translating advanced or awkward sentence structures.
Imagine asking it to translate something like, “All of the willpower that I had had had no effect on the outcome.” That’s a perfectly logical (albeit odd) sentence in English, but it might trip up an AI translator.
Human translations have a specific tone and style that they can maintain throughout the text, whereas AI tends to wander, shifting in tone and style and missing the point entirely, or going from overly formal to overly simplified language.
AI can struggle to translate certain terminology in specialized industries. For example, it might translate a “software bug” to “insecto” in Spanish, even though it’s not an actual insect but rather a programming error.
The intricacies of languages and grammar, when translated, could pose further problems in generating the correct sentence with proper word use. Polysemy and homonymy provide an excellent example.
Polysemy refers to words that have multiple meanings.
Example: Good could describe the level of skill or a personality. They were a good person could mean someone was kind. Alternatively saying they were good at carpentry could mean someone had an excellent proficiency in the trade.
Homonymy occurs when you have two or more words that sound or are spelled the same but have different meanings.
Example: Bark could refer to the rough outer covering of a tree or the sound a dog makes.
AI’s role in multilingual content creation depends heavily on the quantity and variety of training data. This directly affects the quality and accuracy of its translations, which is a major problem for less-commonly spoken or endangered languages.
Human translators aren’t perfect, and some errors in the original training data can lead to learned errors that continue to spread in AI multilingual content output.
If you’re involved in multilingual marketing or multilingual content marketing, there are potential impacts to consider. While AI can streamline the translation process, it can also pose challenges for content marketing.
If your audience notices that your multilingual marketing materials are robotic or bland-sounding, it can create a disconnect with your audience. In contrast, a human translator can incorporate cultural context, idioms, and expressions. Human-translated content evokes emotion and has a personal touch that readers understand and appreciate.
When you’re translating content with an AI-powered translator, the tool generates AI copy (even when the input content was original and human-written). As a result, it can increase the AI score of content.
Google prioritizes people-first content, and mass-produced content that doesn’t comply with its spam policies could result in content being flagged as AI spam. Google has demonstrated that it penalizes AI content, so it’s important to balance AI tools with unique, human-written content. It’s worth investing in high-quality, human translations to help capture not just the essence but the quality of your content.
So, how do you strike a proper balance between human creativity and AI translation?
Consider using AI as a starting point for drafts. The AI translator can take a first pass at the translation to help create a consistent foundation. It’s then up to human translators to refine and edit the copy, add creativity and emotion, and infuse the text with cultural nuances and expressions.
AI is also great for:
However, the last stages of refinement and polishing should be left to the human professionals. It’s also a good idea to get feedback from the target audience to make sure that the translated content not only makes sense, but that it resonates well with them.
Originality.ai’s powerful AI checker is not only highly accurate (Standard 2.0.1 has 99%+ accuracy when detecting AI content), but it also detects AI content created in 15 languages, including:
This means whether you’re getting started with multilingual marketing or you want to make sure that your translated content isn’t AI-generated, Originality.ai’s cutting-edge AI checker can give you the peace of mind you need to publish with integrity.
As the future of AI continues to unfold, it’s likely that AI translation will continue to improve and advance.
In the meantime, it’s important to be aware of the challenges that multilingual AI content translation poses, from increasing AI content on a website (which could impact rankings) to struggling to capture intricate grammar or linguistic style.
It’s best practice to keep a human in the loop to make sure that your multilingual content marketing reaches the quality threshold you’re aiming for.
Pexels As a web publisher, site owner, or content agency, the quality of your content has a direct impact on your business. You want to be sure that the text you publish is top-notch – but if you’re ordering copy from an outside source, quality control ain’t easy. Especially when trying to identify AI-generated
