Groups who use Google Translate have said that using the app can come with some quirks and funny misunderstandings – but they’ve found that after some practice and certain techniques they are able to use the app effectively. However, many Groups have found that after the first few weeks, using Google Translate is sufficient for some day-to-day interaction and communicating via text message.Īlthough it should never replace an interpreter for communicating about important matters, GP appointments or benefits discussions, Groups have told us that Google Translate, either online or in app form, has simplified interactions with the family. Community Sponsorship Groups use professional in-person interpreter, telephone interpreters, volunteers or even bilingual Group members to meet this requirement. Part of your Sponsor Requirements in supporting a resettled family is to provide interpretation support for the language spoken by the family for their first year in the UK. “Stereotyping often results in the type of bias that negatively impacts all minority communities.Learn how Community Sponsorship Groups are making the most out of this free app
“We welcome the swift resolution of this issue and hope measures will be implemented to ensure that translation services do not produce such stereotypical results for any language,” said Nihad Awad, the national executive director of CAIR. Google removed the offensive phrase from the word’s entry shortly after receiving criticism from groups like CAIR. “Unfortunately, some of those patterns can lead to unintentional autocomplete suggestions.” “Google Translate is an automatic translator, using patterns from millions of existing translations as well as user queries to help decide on the best translation and autocomplete suggestions for our users,” Google said in a statement apologizing for the most recent error. Experts on the technology have stated that developers must consider the consequences of replicating human bias and work toward reducing it as much as possible. A similar problem is present in large language models, which have been the subject of debate for their potential to augment hate speech. Such bias, while concerning, is not entirely the developers’ fault - because machine translation systems are trained on huge datasets of human language, they may replicate human biases.
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