好英语网谷歌街景地图如何揭示收入水平
Cars have long been status symbols – if you have a fancy car, people might think you’re rich.
汽车一直是地位的象征：人们会认为坐拥豪车的人都是富人。
While flaunting ritzy items is usually a practice of one-upsmanship to impress neighbours, a new study finds that the types of cars found in a community might also suggest very real facts about an area’s income level, demographics and an existence of inequality.
尽管在他人面前炫耀奢华物品通常会显得高人一等，但一项最新研究发现，某个社区拥有的汽车类型可能会非常真实地反映当地的收入水平、人口结构和不平等现象。
For example, the more foreign cars in a neighbourhood, the higher the average income in that neighbourhood. That might not sound too surprising – but the surprising part is that all this information was gathered not by hand but by algorithms combing Google Street View. This new approach has big implications for how large-scale income data can be collected in the future.
例如，社区中外国汽车越多，人们的平均收入也就越高。这听起来可能并不太令人意外，但令人惊讶的是，所有这些信息并非由人工采集，而是谷歌街景地图外加各种算法得来的。这种新方法对未来收入大规模数据采集将产生重大影响。
2017年7月维也纳谷歌街景地图中的汽车
The study comes from Stanford University in California and was published last month. For the study, the team built an algorithm that combed through 50 million Google Street View images from 200 US cities. These algorithms recognised the year, model and make of every car in every image, even if they were obstructed by other objects or photographed from an odd angle. Next, those findings were compared with data from the American Community Survey, a $250m door-to-door study that rounds up data ranging from gender to education to unemployment, as well as voting preferences.
这项研究结果是加州斯坦福大学在上个月发布的。其中，研究人员建立了一种算法，纳入200个美国城市5000万幅谷歌街景地图。这些运算用于识别每幅图片中每辆汽车的年份、型号和厂商，即使汽车被其他物体挡住，或者拍摄角度怪异也不例外。下一步，研究人员将这些结果与《美国社区调查报告》（American Community Survey）中的数据进行对比。该调查是一项耗资2.5 亿美元的挨家挨户调查，调查内容涉及性别、教育程度、失业率以及投票偏好等。
With this comparison, the researchers could accurately predict a host of demographic identifiers such as income, race and even political views – all from the types of cars found in each community.
通过这种比较，研究人员可以准确地预测出一系列人口统计数据，如收入、种族乃至政治观点——所有这些信息都来自各个社区不同的汽车类型分布。
The study found that German and Japanese cars (Lexus in particular) were found in areas with high median household income. Meanwhile, American cars made domestically, specifically Buicks, Oldsmobiles and Dodges, were associated more with lower median household incomes.
研究发现，在家庭收入中值较高的地区，德国车和日本车（尤其是雷克萨斯，Lexus）居多。与此同时，美国国产车，尤其是别克（Buicks）、奥尔兹（Oldsmobiles）和道奇（Dodges），则与较低的家庭收入有关。
Using powerful AI to analyse images of cars on Street View could provide a faster, cheaper way to pinpoint where inequality might hit the hardest. For example, Chicago is starkly segregated by income level, with cheap cars and costlier ones separated in big swaths across the city, while Jacksonville, Florida saw the least economic segregation, judging by the distribution of cars.
研究人员借助强大的人工智能技术分析街景中的汽车图像，可以更低代价更快捷地查明不平等现象可能最为严重的地方。例如，在芝加哥，廉价汽车和豪车分别位于不同居民收入水平截然不同的区域；而在佛罗里达州的杰克逊维尔（Jacksonville），从汽车的分布来看，居民经济水平隔离情况最不明显。
This is a big deal, too, because surveys and censuses that usually find out that kind of data (like race and political leanings) are labourious, time-consuming and expensive.
这项研究发现意义重大，因为虽然通过调查和人口普查通常也会得到这些数据（如种族和政治倾向），但却费力耗时，代价高昂。
Timnit Gebru, lead researcher for the study, says that since the study has been published, the team has been contacted by political scientists who wanted to use the data.
这项研究的首席研究员蒂姆尼特·格布鲁（Timnit Gebru）表示，自研究结果发表以来，已有不少政治学家联系团队，希望使用这些数据。
“[They] could potentially augment the information we have with things other than cars, and get more accurate and timely results to perform demography,” she wrote in an email.
她在一封电子邮件中表示，"利用这些信息，（他们）能加深对汽车以外的其他信息的了解，从而能获得更及时、更准确的结果，用于人口统计学研究。"
While the findings give credence to the fact that the type of car you drive may suggest certain things about yourself, such as wealth or class, Gebru offers caveats, too.
虽然这些发现证明，你的座驾类型可能会暗示关于你本人的某些信息，如财富或阶级，但格布鲁也给出一些警告。
“I don't think that all countries have the associations between cars and people that exist in the US,” she says. “In other countries, there might be a strong relationship between certain garments and other expressions of culture.”
她表示，"我认为，美国的这种汽车与人之间的相关性不是所有国家都有。在其他国家，着装和其他文化表现形式之间可能存在密切的关系。"
“What I would like people to take away from this study is not necessarily that there is a strong relationship between cars and people – it is that computational social scientists could potentially use images to study culture,” she says. The machine learning like the kind she and her team used could act as a complement to demographics surveys that already exist.
她表示，"我希望，从这项研究中获得的并不一定是汽车和人之间的密切关联，而是计算社会科学家能会利用街景地图进行文化研究"。她和她的团队所使用的这种机器学习方法，可作为现有人口统计调查研究的补充。
Outside of matters of money and inequality, other countries have been looking to use AI and public images, like the ones from Google Street View, to learn more about the people who live there in ways that traditional surveys or censuses could measure. For example, Canadian health researchers are also analysing Google Street View images to study the relationship between certain diseases and the greenery or pollution levels of certain neighbourhoods.
除了经济和不平等问题，其他国家已经在使用像谷歌街景地图这样的公共图像和人工智能技术来了解当地居民的更多情况，而这些情况原本要传统调查或普查才能得到。例如，加拿大医疗卫生研究人员正在通过分析谷歌街景地图，研究一些地区某些疾病与当地植被或污染水平之间的关系。
And as long as there are tech companies out there snapping photos of our lives, houses and even cars, our salaries and secrets may be more accessible than we think.
只要有科技公司拍摄记录我们的生活、房子甚至汽车，我们的收入和秘密就更容易被人所知。
