Automated translation, i.e. the translation of text via an IT system, offers the opportunity to translate back and forth between different languages in milliseconds. We at the Urban Change Lab have recently started using automated translation with DeepL to enable dialogue between our customers in Europe and our craftsmen in Africa so that everyone can write in their own language. We really believe that automated translation will change the world. Meanwhile, the quality of this translation is at a level that the risk of misunderstandings has become very small. The DeepL system seems to be clearly superior to Google Translate or the Bing translator.
We are particularly pleased about the social relevance of this development. The direct dialogue between people of different origins from all social groups without language barriers will change society. Initial approaches are already visible on social media platforms, where comments are automatically translated. As Urban Change Lab, we are certainly a small wheel as a user of these translation systems, but we regard the possibility that a craftswoman in Kenya or Ghana speaks to a customer in Germany in a direct dialogue without language barriers as another and very profound dimension of international understanding. It is not only a matter of different language but also of different backgrounds, experiences and perspectives. We will also see a much greater use of media coverage from other countries and language areas. It can be very beneficial and lead to more mutual understanding if one can consume the media of other countries without barriers.
When mothers can talk to each other
While integrating DeepL into the Urban Change Lab, I came up with the idea of using automated translation technology for a very special challenge for my family: My mother (71) from Kleinlangheim, Germany, speaks German only. My mother-in-law (59) from Nairobi, Kenya speaks English, Swahili and Luo.
Both do not share a common language and can therefore only speak to each other if someone translates. Well, it’s nice that they still send each other WhatsApp messages. But it is always a little bit broken telephone when the message has to go to my wife Valerie, her sister Maggie or me to translate. Facebook and others are working on solving this problem with messengers with integrated translation, but I didn’t want to wait for that.
And so I created as a by-product of the integration of DeepL into the Urban Change Lab a solution that everyone can build for themselves without any programming knowledge. My mother can now write an e-mail to my mother-in-law, which is automatically translated from German into English on the way with DeepL and gets to my mother-in-law in English. If she clicks on answer and writes her text in English, it will be automatically translated from English to German etc. on the way via DeepL. Now I will observe how this possibility affects the dialogue between the two and hope that there will be no unsolvable misunderstandings.
If you have a similar challenge in your family, you can solve it this way:
a) Set up an e-mail address for each of them (e.g. [email protected] and [email protected])
b) Get access at Zapier (with Zapier you can digitize workflows even if you cannot or do not want to program).
b1) Create a ProAccount with DeepL if you want to use DeepL for translation. If you are less advanced with technology, you can use the built-in translation in Zapier first at no extra cost.
c) Configure a flow in Zapier for email to MamaValerie (see picture): 1. incoming email with email from Zapier (set up an automatic forwarding to the generated Zapier Mail at the e-mail address [email protected]); 2. set up call to DeepL in Zapier to translate the subject line; 3. set up call to DeepL to automatically translate the mail text; 4. outgoing email with SMTP with the real email address of Mama Valerie configured as target.
d) Configure a flow in Zapier for mail to MamaJochen: 1. incoming email with email from Zapier (set up an automatic forwarding to the generated Zapier Mail at the e-mail address [email protected]); 2. set up a call to DeepL in Zapier to translate the subject line; 3. set up a call to DeepL to automatically translate the mail text; 4. outgoing email with SMTP with the real email address from Mama Jochen configured as target.
e) Send the e-mail address you set up for your two mothers as a target e-mail to each of them. But make sure they use the set up email-addresses only as a target adress to send e-mails to. Both mothers should still use their usual e-mail addresses (which you entered in steps c and d) as nothing should change for both of them in their usual communication.
There are certainly more elegant solutions, but it was just about solving it without programming knowledge to copy. If you know a better or easier solution, please let us know.
If you come across challenges while rebuilding, please ask us. Maybe we’ll make an explanatory video.
If you would like to see DeepL live, you can either view it on their website or simply ask us for an offer for a handcrafted product. Then you will enter directly into a “conversation” with a craftsman and in between automated translation (if you make your request in German).
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