Translation tools from Alphabet Inc<\/a>'s Google<\/a> and other companies<\/a> could be contributing to significant misunderstanding of legal terms with conflicting meanings such as \"enjoin,\" according to research due to be presented at an academic workshop on Monday. 翻译工具的字母公司的谷歌和其他公司可能导致重大误解与冲突的法律术语的含义如“禁止,”根据研究定于周一在一个学术研讨会。
Google<\/a>'s translation software turns an English sentence about a court enjoining violence, or banning it, into one in the Indian language of Kannada that implies the court-ordered violence, according to the new study<\/a>.
\"Enjoin\" can refer to either promoting or restraining an action. Mistranslations also arise with other contronyms<\/a>, or words with contradictory meanings depending on context, including \"all over,\" \"eventual\" and \"garnish,\" the paper said.
Google said machine translation is \"is still just a complement to specialized professional translation\" and that it is \"continually researching improvements, from better handling ambiguous language, to mitigating bias, to making large quality gains for under-resourced languages.\"
The study's findings add to scrutiny of automated translations<\/a> generated by artificial intelligence software. Researchers previously have found programs that learn translations by studying non-diverse text perpetuate historical gender biases, such as associating \"doctor\" with \"he.\"
The new paper raises concerns about a popular method companies use to broaden the vocabulary of their translation software. They translate foreign text into English and then back into the foreign language, aiming to teach the software to associate similar ways of saying the same phrase.
Known as back translation, this process struggles with contronyms, said Vinay Prabhu, chief scientist at authentication startup UnifyID and one of the paper's authors.
When they translated a sentence about a court enjoining violence into 109 languages supported by Google's software, most results erred. When spun back to English, 88 back translations said the court called for violence and only 10 properly said the court prohibited it. The remainder generated other issues.
Another researcher, Abubakar Abid, tweeted in December that he found possible bias in back translation through Turkish. Using Google, short phrases with \"enjoin\" translated to \"people\" and \"Muslims\" ordering violence but the \"government\" and \"CIA<\/a>\" outlawing it.
The new paper said translation issues could lead to severe consequences as more businesses use AI to generate or translate legal text. One example in the paper is a news headline about nonlethal domestic violence turning \"hit\" into \"killed\" during translation, a potentially true but problematic association.
Authors also expressed concern about the lack of warnings and confidence scores in tools from Google and others. Google in support materials warns it may not have the best solution \"for specialized translation in your own fields.\"
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谷歌的翻译软件把英文句子对法院责令暴力,或禁止它,到一个在印度的埃纳德语语言意味着法院下令暴力,根据新的研究。
“嘱咐”可以指促进或抑制一个动作。误译等也会出现与其他contronyms,或者与矛盾的含义取决于上下文,包括“,”“最终”和“装饰,”该报称。
自动化的研究结果增加审查翻译由人工智能软件生成的。以前研究人员发现学习翻译的程序通过研究non-diverse文本延续历史的性别偏见,比如将“医生”与“他”。
这篇新论文提出担忧公司使用流行的方法扩大词汇的翻译软件。他们把外国文本翻译成英语,然后回外语,旨在教软件副类似说同样话的方式。
被称为翻译,这个过程与contronyms斗争,首席科学家验证Vinay您正在说启动UnifyID和文章的作者之一。
当他们一句关于法院责令暴力翻译成109种语言支持谷歌的软件,大部分结果错误。当旋转回英语,88年回翻译说,法院呼吁暴力和只有10适当法院禁止它说。其余产生其他问题。
另一位研究员,Abubakar阿比德,去年12月在推特上,他发现可能的偏见通过土耳其重新翻译。使用谷歌,短语“嘱咐”翻译成“人”和“穆斯林”订购暴力,但“政府”和“美国中央情报局“取缔它。
新论文说翻译问题可能导致严重后果随着越来越多的企业使用人工智能生成或翻译法律文本。一个例子在报纸上的新闻标题是关于家庭暴力不致命的“得分”变成乐动扑克了“死亡”在翻译过程中,一个潜在的真实但问题协会。
作者还警告和信心的缺乏表示担忧分数从谷歌和其他工具。谷歌支持材料警告说它可能没有最好的解决方案”,在自己的领域的专业翻译。”
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Translation tools from Alphabet Inc<\/a>'s Google<\/a> and other companies<\/a> could be contributing to significant misunderstanding of legal terms with conflicting meanings such as \"enjoin,\" according to research due to be presented at an academic workshop on Monday.
Google<\/a>'s translation software turns an English sentence about a court enjoining violence, or banning it, into one in the Indian language of Kannada that implies the court-ordered violence, according to the new study<\/a>.
\"Enjoin\" can refer to either promoting or restraining an action. Mistranslations also arise with other contronyms<\/a>, or words with contradictory meanings depending on context, including \"all over,\" \"eventual\" and \"garnish,\" the paper said.
Google said machine translation is \"is still just a complement to specialized professional translation\" and that it is \"continually researching improvements, from better handling ambiguous language, to mitigating bias, to making large quality gains for under-resourced languages.\"
The study's findings add to scrutiny of automated translations<\/a> generated by artificial intelligence software. Researchers previously have found programs that learn translations by studying non-diverse text perpetuate historical gender biases, such as associating \"doctor\" with \"he.\"
The new paper raises concerns about a popular method companies use to broaden the vocabulary of their translation software. They translate foreign text into English and then back into the foreign language, aiming to teach the software to associate similar ways of saying the same phrase.
Known as back translation, this process struggles with contronyms, said Vinay Prabhu, chief scientist at authentication startup UnifyID and one of the paper's authors.
When they translated a sentence about a court enjoining violence into 109 languages supported by Google's software, most results erred. When spun back to English, 88 back translations said the court called for violence and only 10 properly said the court prohibited it. The remainder generated other issues.
Another researcher, Abubakar Abid, tweeted in December that he found possible bias in back translation through Turkish. Using Google, short phrases with \"enjoin\" translated to \"people\" and \"Muslims\" ordering violence but the \"government\" and \"CIA<\/a>\" outlawing it.
The new paper said translation issues could lead to severe consequences as more businesses use AI to generate or translate legal text. One example in the paper is a news headline about nonlethal domestic violence turning \"hit\" into \"killed\" during translation, a potentially true but problematic association.
Authors also expressed concern about the lack of warnings and confidence scores in tools from Google and others. Google in support materials warns it may not have the best solution \"for specialized translation in your own fields.\"
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