本文摘要：Artificial intelligence can accurately guess whether people are gay or straight based on photos of their faces, according to new research suggesting that machines can have significantly better gaydar than humans.一项新的研究表明，人工智能可以通过人脸照片准确辨识出有

Artificial intelligence can accurately guess whether people are gay or straight based on photos of their faces, according to new research suggesting that machines can have significantly better gaydar than humans.一项新的研究表明，人工智能可以通过人脸照片准确辨识出有这个人是平男还是同性恋者，该研究指出，机器的“gay约”（同志雷达）比人类精确得多。The study from Stanford University – which found that a computer algorithm could correctly distinguish between gay and straight men 81% of the time, and 74% for women – has raised questions about the biological origins of sexual orientation, the ethics of facial-detection technology and the potential for this kind of software to violate peoples privacy or be abused for anti-LGBT purposes.这项斯坦福大学的研究找到，计算机算法能正确区分平男与同性恋者，准确率高达81%，对女性性取向判断的准确率为74%。这一研究引起了人们对性向的生物学起源、人脸识别科技的道德伦理以及此类软件对个人隐私有可能导致的侵害，或被欺诈于鼓吹同性恋者、双性恋及变性人群体等问题的争议。

The machine intelligence tested in the research, which was published in the Journal of Personality and Social Psychology and first reported in the Economist, was based on a sample of more than 35,000 facial images that men and women publicly posted on a US dating website. The researchers, Michal Kosinski and Yilun Wang, extracted features from the images using deep neural networks, meaning a sophisticated mathematical system that learns to analyze visuals based on a large dataset.这项研究首度被《经济学人》报导，并公开发表在《人格与社会心理学》杂志上。这种人工智能分析了美国某交友网站上公开发表公布的35000多张男女面部图像样本。

研究人员迈克·科辛斯基和Yilun Wang利用“深层神经网络”从图像中萃取涉及性别特征，这是一个从大量数据中学不会视觉分析的简单数学系统。The research found that gay men and women tended to have gender-atypical features, expressions and grooming styles, essentially meaning gay men appeared more feminine and vice versa. The data also identified certain trends, including that gay men had narrower jaws, longer noses and larger foreheads than straight men, and that gay women had larger jaws and smaller foreheads compared to straight women.研究找到，同性恋者男女往往具备“非典型性别”特征、表情和“装扮风格”，也就是说男同性恋一般趋向于女性化，而女同反之。研究数据还找到了一些其他趋势，如男同性恋的下巴比直男更加较宽，鼻子更长，前额更加长。

而同性恋者女性比起直女下巴更加长，前额更加较宽。Human judges performed much worse than the algorithm, accurately identifying orientation only 61% of the time for men and 54% for women. When the software reviewed five images per person, it was even more successful – 91% of the time with men and 83% with women. Broadly, that means faces contain much more information about sexual orientation than can be perceived and interpreted by the human brain, the authors wrote.人类在这方面的的辨别展现出远逊机器算法，其辨别男性性向的准确率仅有为61%，女性的为54%。

当人工智能软件需要网页5张测试对象的照片时，准确率则更高：对男性性向辨别的准确率为91%，对女性的为83%。研究人员在论文中写到，从广义上谈，这意味著“人类面孔包括的性取向信息比人类大脑可以感官和理解的更好”。The paper suggested that the findings provide strong support for the theory that sexual orientation stems from exposure to certain hormones before birth, meaning people are born gay and being queer is not a choice. The machines lower success rate for women also could support the notion that female sexual orientation is more fluid.文中认为，有理论指出胎儿出生于前认识到的某些激素要求了其性向，也就是说同性恋者是天生的，而不是后天的自由选择，该研究结果回应获取了“有力反对”。

而机器对于女性性向辨识成功率较低的现象，则印证了女性性取向更为易变的众说纷纭。While the findings have clear limits when it comes to gender and sexuality – people of color were not included in the study, and there was no consideration of transgender or bisexual people – the implications for artificial intelligence (AI) are vast and alarming. With billions of facial images of people stored on social media sites and in government databases, the researchers suggested that public data could be used to detect peoples sexual orientation without their consent.虽然研究结果对性别和性征有显著的局限，有色人种没被划入研究，而变性者和双性恋也没划入考量，但这早已表明了人工智能的极大影响，并给人类响起了警钟。社交网络和政府数据库中存储了数十亿人像图片，研究人员指出这些公共数据都有可能在予以本人表示同意的情况下，被人用来展开性取向辨识。

Its easy to imagine spouses using the technology on partners they suspect are closeted, or teenagers using the algorithm on themselves or their peers. More frighteningly, governments that continue to prosecute LGBT people could hypothetically use the technology to out and target populations. That means building this kind of software and publicizing it is itself controversial given concerns that it could encourage harmful applications.可想而知，夫妻可能会用这项技术测试被他们猜测是浅柜的另一半，青少年也可以用于这种算法来辨识自己和同龄人。更为可怕的是，一些对LGBT群体展开法律制裁的国家可能会利用该技术让人出柜。这解释研发并公开发表此类软件的不道德本身不存在争议，因为这可能会造成有危害性的应用软件经常出现。

But the authors argued that the technology already exists, and its capabilities are important to expose so that governments and companies can proactively consider privacy risks and the need for safeguards and regulations.但该论文的作者回应，这些技术早就不存在，曝光其功能很关键，因为这样政府和公司才能主动注目其隐私风险，以及展开管理防止的必要性。Its certainly unsettling. Like any new tool, if it gets into the wrong hands, it can be used for ill purposes, said Nick Rule, an associate professor of psychology at the University of Toronto, who has published research on the science of gaydar. If you can start profiling people based on their appearance, then identifying them and doing horrible things to them, thats really bad.多伦多大学心理学教授尼克·鲁尔曾公开发表过关于“同志雷达”的研究。他回应：“这当然是令人不安的，它就像任何新的工具一样，如果心术不正的人获得它，就不会用来做坏事。

如果我们开始以外表来分析一个人，由此得出结论辨别，并对他们作出可怕的事情，那就过于差劲了。

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