{"id":18667,"date":"2024-09-02T13:23:47","date_gmt":"2024-09-02T13:23:47","guid":{"rendered":"https:\/\/goglobalstd.wpengine.com\/why-is-humanizing-ai-key\/"},"modified":"2024-11-21T15:55:58","modified_gmt":"2024-11-21T15:55:58","slug":"why-is-humanizing-ai-key","status":"publish","type":"post","link":"https:\/\/www.goglobal-consulting.com\/pt-br\/why-is-humanizing-ai-key\/","title":{"rendered":"Why is humanizing AI key?"},"content":{"rendered":"\t\t
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Why is humanizing AI key?<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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In recent years we\u2019ve seen significant improvements in the quality of automated translations done by LLMs such as chatGPT4. But are AI translations already so sophisticated that they no longer need human supervision?<\/p>\n

We can still see that direct AI translations have their limitations when it comes to grammatical or localization mistakes, but the biggest debate surrounding the use of this type of technology has to do with what is known as the AI Bias- that diversity and inclusiveness are still areas that these new technologies need to improve.<\/strong><\/i><\/p>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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AI diversity bias.<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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AI systems rely on broad data sets, usually found on the internet, which can unintentionally perpetuate already present biases. This, in turn, can result in AI tools also making biased decisions, especially when dealing with sensitive issues such as ethnicity, gender, or socioeconomic status. <\/p>\n

A Cornell University study <\/a>found that, for example, an AI-trained robot was more likely to associate African-American men with \u201ccriminals,\u201d or women with \u201chousewives.\u201d The team of researchers concluded that ongoing use of such technology runs the risk of \u201camplifying malignant stereotypes,\u201d which continue to fuel racism and misogyny.<\/p>\n

AI diversity bias is a key issue for leaders in the field of AI technology, as highlighted in a recent statement shared with CNN<\/a> by a spokesperson for OpenAI, the company behind ChatGPT and other artificial general intelligence (AGI) models. \u201cWe are continually iterating our models to reduce bias and mitigate harmful outcomes,\u201d the company said in a statement, adding that for each new model released, OpenAI publishes research on how they are working to achieve those goals.  <\/p>\n

How can we ensure that AI translation tools achieve a wider range of diversity?<\/p>\n

\u2013 Mitigate bias in the data used for training and testing. Techniques such as data augmentation, data balancing, data anonymization, or data transformation can be used to improve both data quality and diversity while reducing the impact of bias. For example, you can incorporate more data from marginalized communities, make sure there is an equal balance of labels or entities, omit sensitive or irrelevant information, or transform data to a more neutral format.<\/p>\n

-Form diverse work teams for both those who develop the technology and those who work with the tools. This is essential in highlighting different points of view, experiences, and cultural backgrounds.<\/p>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Language localization continues to be a challenge with AI<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Culture and language are closely intertwined. A word or phrase that means one thing in one language may have a completely different meaning in another, especially in languages such as Spanish, which has many different variants and dialects.<\/p>\n

Another challenge is the excessive use of adjectives, infrequent words, or even the wrong verb tenses that continue to appear in many AI translations without human supervision.  A clear example of this is a mistake that Google Translator made, where it once noteworthily translated \u201cRussia\u201d as \u201cMordor,\u201d the fictional land from Lord of the Rings, and Russians became \u201coccupiers\u201d in Ukrainian.<\/p>\n

Getting the correct localization of messages is crucial when it comes to reaching new markets in the face of global expansion. A company\u2019s reputation or its relationship with its clients can suffer as a result of translations that are unclear, culturally insensitive, or disrespectful.<\/p>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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For a more inclusive, unbiased AI<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Humanizing artificial intelligence is crucial if we want to ensure that this technology benefits the entire society fairly and equally. By addressing the challenges of diversity and bias, and encouraging more inclusion in the development of AI, we can create systems that are more representative, culturally sensitive, and responsible, helping improve people\u2019s lives. <\/p>\n

Paula Ferrari, CEO of Go Global, states, \u201cWe believe that a team of linguistic experts can bring out the best in new translation technologies. That\u2019s why we embrace technology in our process and work together with our clients to create customized AI translation solutions that have the human touch and supervision.\u201d<\/p>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

Why is humanizing AI key? In recent years we\u2019ve seen significant improvements in the quality of automated translations done by LLMs such as chatGPT4. But are AI translations already so sophisticated that they no longer need human supervision? 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