Fooling Big Brother

戲弄“老大哥（有獨(dú)|裁|者的含義，文章說出了借計(jì)算機(jī)面部識別系統(tǒng)來組建的監(jiān)視/識別網(wǎng)絡(luò)）”

As face-recognition technology spreads, so do ideas for subverting it

隨著人臉識別技術(shù)的普及，破壞它的想法也在不斷涌現(xiàn)

詞匯

Subvert/顛覆；推翻；破壞

They work because machine vision and human vision are different

“破壞”之所以有效，是因?yàn)闄C(jī)器視覺和人類視覺是不同的

Aug 17th 2019

POWERED BY advances in artificial intelligence (AI), face-recognition systems are spreading like knotweed. Facebook, a social network, uses the technology to label people in uploaded photographs. Modern smartphones can be unlocked with it. Some banks employ it to verify transactions. Supermarkets watch for under-age drinkers. Advertising billboards assess consumers’ reactions to their contents. America’s Department of Homeland Security reckons face recognition will scrutinise 97% of outbound airline passengers by 2023. Networks of face-recognition cameras are part of the (敏感刪除) China has built in Xinjiang, in the country’s far west. And a number of British police forces have tested the technology as a tool of mass surveillance in trials designed to spot criminals on the street.

在人工智能(AI)進(jìn)步的推動下，人臉識別系統(tǒng)正在像雜草一樣普及。社交網(wǎng)絡(luò)Facebook使用這項(xiàng)技術(shù)在上傳的照片中給人貼上標(biāo)簽。現(xiàn)代智能手機(jī)可以用它解鎖。一些銀行用它來驗(yàn)證交易。超市留意未成年飲酒者。廣告牌借此檢測消費(fèi)者對其內(nèi)容的反映。美國國土安全部估計(jì)，到2023年，97%的出境航班乘客將接受人臉識別檢查。人臉識別攝像頭網(wǎng)絡(luò)是中國在遙遠(yuǎn)的西部新疆建立的一部分。一些英國警察已經(jīng)測試了這種技術(shù)，將其作為大規(guī)模監(jiān)控的工具，用于在街道上發(fā)現(xiàn)罪犯。

詞匯

Knotweed/紫菀科植物；蓼科雜草

Scrutinize/作仔細(xì)檢查；細(xì)致觀察

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A backlash, though, is brewing. The authorities in several American cities, including San Francisco and Oakland, have forbidden agencies such as the police from using the technology. In Britain, members of parliament have called, so far without success, for a ban on police tests. Refuseniks can also take matters into their own hands by trying to hide their faces from the cameras or, as has happened recently(敏感刪除), by pointing hand-held lasers at CCTV cameras. to dazzle them (see picture). Meanwhile, a small but growing group of privacy campaigners and academics are looking at ways to subvert the underlying technology directly.

然而，一場抵制正在醞釀之中。包括舊金山和奧克蘭在內(nèi)的幾個(gè)美國城市的當(dāng)局已經(jīng)禁止警察等機(jī)構(gòu)使用這種技術(shù)。在英國，議會成員呼吁禁止治安測試，但至今未獲成功。反抗者也可以用自己的方式解決問題，比如試圖把自己的臉藏起來不讓攝像頭看到，或者用手持激光對準(zhǔn)閉路電視攝像機(jī)，就像最近(敏感刪除)。讓他們眼花繚亂(標(biāo)題圖已更替)。與此同時(shí)，一個(gè)規(guī)模雖小但不斷壯大的隱私維權(quán)人士和學(xué)者團(tuán)體正在尋找直接顛覆基層技術(shù)的方法。

詞匯

Backlash/反沖；強(qiáng)烈抵制

Refusenik/拒絕者，反抗者

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Put your best face forward

將你最棒的一面置于前方

Face recognition relies on machine learning, a subfield of AI in which computers teach themselves to do tasks that their programmers are unable to explain to them explicitly. First, a system is trained on thousands of examples of human faces. By rewarding it when it correctly identifies a face, and penalising it when it does not, it can be taught to distinguish images that contain faces from those that do not. Once it has an idea what a face looks like, the system can then begin to distinguish one face from another. The specifics vary, depending on the algorithm, but usually involve a mathematical representation of a number of crucial anatomical points, such as the location of the nose relative to other facial features, or the distance between the eyes.

人臉識別依賴于機(jī)器學(xué)習(xí)(machine learning)，這是人工智能的一個(gè)子領(lǐng)域，在這個(gè)領(lǐng)域中，計(jì)算機(jī)自學(xué)完成程序員無法明確解釋的任務(wù)。首先，一個(gè)系統(tǒng)是針對成千上萬的人臉樣本進(jìn)行訓(xùn)練的。在識別正確人臉時(shí)給予獎(jiǎng)勵(lì)，在錯(cuò)誤識別后進(jìn)行懲罰，可以教會它區(qū)分包含人臉的圖像和不包含人臉的圖像。一旦它知道一張臉是什么樣子的，系統(tǒng)就可以開始區(qū)分一張臉和另一張臉。具體情況因算法而異，但通常涉及到一些關(guān)鍵解剖點(diǎn)的數(shù)學(xué)表示，比如鼻子相對于其他面部特征的位置，或者眼睛之間的距離。

詞匯

Anatomical/ ?解剖的；解剖學(xué)的；結(jié)構(gòu)上的

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In laboratory tests, such systems can be extremely accurate. One survey by the NIST, an America standards-setting body, found that, between 2014 and 2018, the ability of face-recognition software to match an image of a known person with the image of that person held in a database improved from 96% to 99.8%. But because the machines have taught themselves, the visual systems they have come up with are bespoke. Computer vision, in other words, is nothing like the human sort. And that can provide plenty of *****s in an algorithm’s armour.

在實(shí)驗(yàn)室測試中，這樣的系統(tǒng)可以非常精確。美國標(biāo)準(zhǔn)制定機(jī)構(gòu)NIST的一項(xiàng)調(diào)查發(fā)現(xiàn)，從2014年到2018年，人臉識別軟件將已知人物的圖像與數(shù)據(jù)庫中此人的圖像匹配的能力從96%提高到了99.8%。但是因?yàn)闄C(jī)器是自學(xué)的，所以他們設(shè)計(jì)的視覺系統(tǒng)是定制的。換句話說，計(jì)算機(jī)視覺與人類的視覺完全不同。這可以為算法的裝甲提供很多漏洞。

詞匯

Bespoke/定做的，定制的

*****/裂縫；漏洞

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In 2010, for instance, as part of a thesis for a master’s degree at New York University, an American researcher and artist named Adam Harvey created “CV [computer vision] Dazzle”, a style of make-up designed to fool face recognisers. It uses bright colours, high contrast, graded shading and asymmetric stylings to confound an algorithm’s assumptions about what a face looks like. To a human being, the result is still clearly a face. But a computer—or, at least, the specific algorithm Mr Harvey was aiming at—is baffled.

例如，2010年，在紐約大學(xué)碩士學(xué)位論文的一部分中，一位名叫亞當(dāng)?哈維(Adam Harvey)的美國研究人員兼藝術(shù)家創(chuàng)造了“讓計(jì)算機(jī)視覺眼花（CV [computer vision] Dazzle）”，這是一種旨在欺騙面部識別裝置的化妝風(fēng)格。它使用明亮的顏色、高對比度、漸變陰影和不對稱的樣式來打亂算法對人臉外觀的假設(shè)。對一個(gè)人來說，結(jié)果還是一張清晰的臉。但是一臺計(jì)算機(jī)——或者至少是哈維先生所瞄準(zhǔn)的特定算法——卻束手無策。

詞匯

Asymmetric/不對稱的；非對稱的

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Dramatic make-up is likely to attract more attention from other people than it deflects from machines. HyperFace is a newer project of Mr Harvey’s. Where CV Dazzle aims to alter faces, HyperFace aims to hide them among dozens of fakes. It uses blocky, semi-abstract and comparatively innocent-looking patterns that are designed to appeal as strongly as possible to face classifiers. The idea is to disguise the real thing among a sea of false positives. Clothes with the pattern, which features lines and sets of dark spots vaguely reminiscent of mouths and pairs of eyes (see photograph), are already available.

戲劇性的化妝更容易吸引別人的注意卻也會降低計(jì)算機(jī)的關(guān)注度?？簥^的臉（HyperFace）是哈維先生的一個(gè)新項(xiàng)目?！白層?jì)算機(jī)視覺眼花”的目的是改變?nèi)四?，而亢奮的臉的目的是將人臉隱藏在幾十個(gè)假臉中。它使用塊狀的、半抽象的和相對無害的模式，這些模式的設(shè)計(jì)是為了盡可能強(qiáng)烈地吸引臉部分類器。這樣做的目的是在一大堆錯(cuò)誤信息中掩蓋真實(shí)情況。該圖案的衣服已經(jīng)上市，衣服上的線條和黑色斑點(diǎn)讓人隱約想起嘴巴和眼睛(見圖)。

詞匯

false positives/誤報(bào)；假陽性；主動錯(cuò)誤信息

Vaguely/含糊地；曖昧地；茫然地

Reminiscent/懷舊的，回憶往事的

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An even subtler idea was proposed by researchers at the Chinese University of Hong Kong, Indiana University Bloomington, and Alibaba, a big Chinese information-technology firm, in a paper published in 2018. It is a baseball cap fitted with tiny light-emitting diodes that project infra-red dots onto the wearer’s face. Many of the cameras used in face-recognition systems are sensitive to parts of the infra-red spectrum. Since human eyes are not, infra-red light is ideal for covert trickery.

香港中文大學(xué)、印第安納大學(xué)布盧明頓分校和中國大型信息技術(shù)公司阿里巴巴的研究人員在2018年發(fā)表的一篇論文中提出了一個(gè)更微妙的想法。這是一頂棒球帽，上面裝有微型發(fā)光二極管，可以將紅外光點(diǎn)投射到佩戴者的臉上。人臉識別系統(tǒng)中使用的許多相機(jī)對紅外光譜的某些部分很敏感。由于人類的眼睛不是這樣，紅外線是隱蔽欺騙的理想光源。

詞匯

Subtle/微妙的；精細(xì)的

Covert/隱蔽的，秘密的

In tests against FaceNet, a face-recognition system developed by Google, the researchers found that the right amount of infra-red illumination could reliably prevent a computer from recognising that it was looking at a face at all. More sophisticated attacks were possible, too. By searching for faces which were mathematically similar to that of one of their colleagues, and applying fine control to the diodes, the researchers persuaded FaceNet, on 70% of attempts, that the colleague in question was actually someone else entirely.

在針對由谷歌開發(fā)的人臉識別系統(tǒng)FaceNet的測試中，研究人員發(fā)現(xiàn)，適量的紅外線照射能夠可靠地阻止計(jì)算機(jī)識別出自己正在看的是一張臉。更復(fù)雜的攻擊也是可能的。通過尋找在數(shù)學(xué)上與他們的一位同事相似的面孔，并對二極管進(jìn)行精細(xì)的控制，研究人員在70%的實(shí)驗(yàn)中讓FaceNet信服了，這個(gè)測試中的同事實(shí)際上完全是另一個(gè)人。

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Training one algorithm to fool another is known as adversarial machine learning. It is a productive approach, creating images that are misleading to a computer’s vision while looking meaningless to a human being’s. One paper, published in 2016 by researchers from Carnegie Mellon University, in Pittsburgh, and the University of North Carolina, showed how innocuous-looking abstract patterns, printed on paper and stuck onto the frame of a pair of glasses, could often convince a computer-vision system that a male AI researcher was in fact Milla Jovovich, an American actress.

訓(xùn)練一種算法去欺騙另一種算法被稱為對抗性機(jī)器學(xué)習(xí)。這是一種富有成效的方法，創(chuàng)建的圖像會誤導(dǎo)計(jì)算機(jī)的視覺，而對人類的視覺卻毫無影響。出版于2016年的一篇論文來自在匹茲堡的卡內(nèi)基梅隆大學(xué)和北卡羅萊納大學(xué)的研究人員們表明如何讓看起來無害的抽象圖案打印在紙上然后粘在眼鏡的框架上能夠使計(jì)算機(jī)視覺系統(tǒng)相信一個(gè)男性人工智能研究院“實(shí)際上”是米拉·喬沃維奇這位美國女演員。

詞匯

Adversarial/對抗的

Innocuous/無害的；無傷大雅的

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In a similar paper, presented at a computer-vision conference in July, a group of researchers at the Catholic University of Leuven, in Belgium, fooled person-recognition systems rather than face-recognition ones. They described an algorithmically generated pattern that was 40cm square. In tests, merely holding up a piece of cardboard with this pattern on it was enough to make an individual—who would be eminently visible to a human security guard—vanish from the sight of a computerised watchman.

在7月計(jì)算機(jī)視覺會議上發(fā)表的一篇類似論文中，比利時(shí)魯汶天主教大學(xué)的一組研究人員愚弄了人員識別系統(tǒng)，而不是人臉識別系統(tǒng)。他們描述了一個(gè)由算法生成的40厘米平方的圖案。在測試中，僅僅舉起一塊印有這種圖案的紙板就足以讓一個(gè)人從電腦看守人的視線中消失，而這個(gè)人對人類安全警衛(wèi)來說是顯而易見的。

詞匯

Eminently/突出地；顯著地

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As the researchers themselves admit, all these systems have constraints. In particular, most work only against specific recognition algorithms, limiting their deployability. Happily, says Mr Harvey, although face recognition is spreading, it is not yet ubiquitous—or perfect. A study by researchers at the University of Essex, published in July, found that although one police trial in London flagged up 42 potential matches, only eight proved accurate. Even in China, says Mr Harvey, only a fraction of CCTV cameras collect pictures sharp enough for face recognition to work. Low-tech approaches can help, too. “Even small things like wearing turtlenecks, wearing sunglasses, looking at your phone [and therefore not at the cameras]—together these have some protective effect”.

正如研究人員自己所承認(rèn)的，所有這些系統(tǒng)都有限制。特別是，大多數(shù)只針對特定的識別算法工作，限制了它們的可部署性。令人高興的是，哈維先生說，盡管人臉識別正在傳播，但它還沒有普及，或者說還不完美。埃塞克斯大學(xué)的研究人員在7月發(fā)表的一項(xiàng)研究發(fā)現(xiàn)，盡管倫敦警方的一項(xiàng)試驗(yàn)發(fā)現(xiàn)了42名潛在的（罪犯）配對者，但只有8名被證明是正確的。哈維表示，即使在中國，也只有一小部分閉路電視攝像頭能收集到足夠清晰的圖像，使人臉識別能夠工作。低技術(shù)含量的方法也有幫助?！凹词故窍翊└哳I(lǐng)毛衣、戴太陽鏡、看手機(jī)(而不是看相機(jī))這樣的小事，加在一起也有一定的保護(hù)作用。”

詞匯

Deployability/可部署性

flag up/指出

Turtlenecks/圓翻領(lǐng)；高翻領(lǐng)毛衣

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