Blockchain would be a useful way to streamline translation
Write it. Edit it. Translate it. Edit it. Review it. Check for nuances. Add subtlety. Change phrases. Check. Publish.
Translation — done well that is — is a long process. If you like translation or learning languages, it isn’t as tedious as it sounds. Time-consuming, yes, but not a chore. Google Translate arguably makes translation a smoother process (especially following its neural network updates) because you can drop a text into the machine and then edit the result. It is faster to work off a text instead of producing one from scratch.
But that only works if you have certain skills.
If you are fluent or communicable in the target language, this can speed up your process. But if you don’t have enough experience, you might not understand when Google Translate or any other machine translation produces a simple (pretty elementary) mistake: Well, in layman’s terms, a stupid mistake.
You might see an exact translation and think it looks fine, not realizing the machine selected the wrong definition of a word with several meanings. This happens less and less when it’s English to a common European language like Spanish, French or German. But there are still plenty of errors in other widely spoken languages and especially non-European languages.
Thankfully, Google has an improving suggestion/correction mechanism. I find myself using this a lot with Hebrew, a language I would expect to have better results considering how important Israel is in the tech world (I even work across the street from Google’s Tel Aviv office).
Checking those translations might be smoother with a blockchain process. It would also make the incentives clearer for users in the Google Translate community. It’s also an appealing solution to for-profit translation companies.
Crowd wisdom makes translations more precise
This goes for styles of speech as well as dialects. In addition, the compilation of data about the person checking the translation could be valuable for understanding differences between speakers based on region, age or even ethnic background. This can help businesses marketing to specific demographics and, as always, help students sound more natural with more common vocabulary and style usage in a target language.
Impact on professional translations
There are a handful of companies serving the blockchain and cryptocurrency industry, names like Crypteido and Kotaba. But few companies have yet to explore implementing blockchain as part of their translation process.
Google Translate, Microsoft/Bing Translator and Yandex.Translate (Russia) are good for single sentences or small paragraphs, but they of course aren’t designed for full-scale projects. It’s one thing to crowdsurf to improve a machine translation’s databank, entirely another to seek out professional services. But there is no reason why both cannot exist in the same ecosystem.
In areas with fewer conventional payment options, translators of isolated dialects or offering lower prices can offer their services in this decentralized marketplace.
With translation, it’s a balance between human input and algorithms
Machine translation is a steady process. Algorithms aren’t yet available that can keep up with the pace of change in human language, much less pick up on nuances of tone and word choice (especially broken down by demographic and context).
In this crowdsourced translation protocol, because we are not dealing with simple financial approvals (essentially yes/no questions of whether not to validate transactions), instantaneous results are not expected. There is incentive to move quickly, but that speed will be limited by availability of people willing to vouch for specific translations and make edits.
In fact, the authority of a given translation (be it one sentence or one page) increases every time an editor improves or approves it. In other words, the more people who approve the translation, the more acceptable it becomes.
Translations are rarely, if ever, perfect.
Translation, thanks to the ebb and flow of language, can only be so precise. Its accuracy, theoretically, can change every few years (perhaps on shorter timelines if you are talking about using trending slang). That also holds in the present, where most people can agree on a translation but there might be subtle disagreements based on preference for a certain word (one translator thinks the term “fast” sounds better than “quick”; or a certain expression translated to English should be equated with “take a chance” instead of “make an effort”).
To incentivize the translators and the editors reviewing their work, levels of token rewards might have to incrementally decrease. For example, the main translator of a three-sentence paragraph gets 1 token. The first editor to review the work is entitled to .5 tokens. The second editor gets .25 tokens. If a third person volunteers and approves it, that person gets .125 tokens, etc. The amount can be adjusted if the system is sufficiently managed (.8 tokens, then .6, then .4, etc.). For more extensive or professional translations, someone may set a certain price, then parameters of the system can define how much each editor is entitled as a reward.
There is more than one model for ‘translation on blockchain’
It will be fascinating to see how advanced communication on such a blockchain-based app might become given the need to explain how the technology operates to different linguistic communities around the world. It is very possible the app for this kind of community would incentivize language-learning itself, or even occasional translation requests from people who want to read something unavailable in their native language!
In other words, we democratize translation demand, making it easier for individuals to seek out other individuals for translation projects unrelated to business or academic work, simply seeking someone to help them translate something for their leisure. The possibilities here are truly fascinating to think about.
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