有难度阅读理解及其文章精准翻译本篇文章属于较难阅读理解,篇幅长,人名多,话题抽象,难点体现在:①分清楚专有名词以及之间的关系有难度:Microsoft,Immigration andCustomsEnforcement ( ICE ), IBM,Amazon , TheOrlandopolicedepartment(奥兰多警局),Azure Government(微软产品)②人物观点辨别:Alondra Nelson(哥伦比亚大学教授);David Robinson(智库懂事),Microsoft chief executive Satya Nadella(微软首席执行官),本文是一辩论,存在各方的观点;③话题抽象:本篇文章为 IT 话题,教抽象;除此之外,还涉及美国移民问题,面部识别功能,技术偏见等问题。译文及理解思路:Microsoft announced this week that its facial-recognition system isnow more accurate in identifying people of color, touting (吹嘘) itsprogress at tackling one of the technology’s biggest biases (偏见).微软本周宣布,其面部识别系统现在可以更准确地识别有色人种,吹捧其在解决该技术最大偏见之一方面的进步。But critics, citing Microsoft’s work with Immigration and CustomsEnforcement, quickly seized on how that improved technology might beused. The agency contracts with Microsoft for cloud-computing toolsthat the tech giant says is largely limited to office work but can alsoinclude face recognition.但是批评者以微软与移民海关执法局的合作为由,很快关注那类科技如何使用的问题(评论者就此问题不放的意思)。 该机构(指的是移民海关执法局)与微软签订了云计算工具合同,这家科技巨头(指的是微软)表示,云计算工具主要限于办公室工作,但也可以包括面部识别。Columbia University professor Alondra Nelson tweeted, “We muststop confusing ‘inclusion’ in more ‘diverse’ surveillance (监管)systems with justice and equality.”哥伦比亚大学教授阿隆德拉·纳尔逊( Alondra Nelson)在一家社交网站(tweet)上说:“我们必须公平公正地,把“包容”和“多样化”监管系统分清楚。Facial-recognition systems more often misidentify people of colorbecause of a long-running data problem: The massive sets of facialimages they train on skew...