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.

这项研究率先被《经济学人》报道，并发表在《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”从图像中提取相关性别特征，这是一个从大量数据中学会视觉分析的复杂数学系统。

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.

研究发现，同性恋男女往往具有“非典型性别”特征、表情和“打扮风格”，也就是说男同性恋一般趋向于女性化，而女同反之。研究数据还发现了一些其他趋势，如男同性恋的下巴比直男更窄，鼻子更长，前额更宽。而同性恋女性相比直女下巴更宽，前额更窄。

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