全世界社交媒體用戶聯(lián)合起來！
如果柏拉圖(Plato)今天還活著，他很可能會(huì)把我們做的大部分工作視為休閑，而把我們享受的多數(shù)休閑時(shí)光視為工作。那些拿著超高薪水、穿梭世界各地討論全球大事的首席執(zhí)行官們，實(shí)際上是在享受無休止的酒會(huì)。但柏拉圖很可能會(huì)用懷疑的眼神看待那些享受釣魚、園藝和烹飪的人，認(rèn)為這些活動(dòng)是辛苦的職業(yè)。
So argued the Czech philosopher Tomas Sedlacek at a recent Financial Times conference, where he claimed to be working. His argument was intended (I think) mostly as an intellectual provocation to highlight how our definitions of work and leisure depend on cultural context rather than immutable social laws.
在英國《金融時(shí)報(bào)》近期舉辦的一場(chǎng)會(huì)議上，捷克哲學(xué)家托馬斯•塞德拉切克(Tomas Sedlacek)就如此論證，并稱自己參加會(huì)議就是在工作。他的觀點(diǎn)(我認(rèn)為)主要意在通過刺激人們思考，來突顯我們對(duì)工作和休閑的定義更依賴于文化背景，而非不可更改的社會(huì)規(guī)律。
But it would certainly help us unravel some of the puzzles of our digital economy if we were to flip some of our conceptual classifications on their head.
但是，如果我們將一些概念分類拋諸腦后，肯定會(huì)幫助我們解開數(shù)字經(jīng)濟(jì)中的一些謎題。
Take social media, for example. Users of Facebook, Instagram, Twitter and YouTube may believe they are simply sharing their special moments, witty insights and hilarious escapades with friends and families. All this activity is enriching our lives, deepening our social connections, and providing fun and free leisure time.
以社交媒體為例。Facebook、Instagram、Twitter和YouTube的用戶或許認(rèn)為只是在分享自己的特別時(shí)刻、詼諧見解以及與朋友和家人的滑稽惡作劇。所有這些活動(dòng)豐富了我們的生活，加深了我們的社會(huì)聯(lián)系，帶來了樂趣和自由的閑暇時(shí)光。
Looked at another way, though, all we are doing by pecking away at our mobile phones like so many digital battery hens is generating massive data sets for machine-learning programs to work out how to sell advertising against us. The genius of Facebook is that all its users are — unwittingly — working for the company for free, creating its most valuable product.
然而，從另一角度看，我們像母雞啄米一樣盯著手機(jī)所做的一切，都在為機(jī)器學(xué)習(xí)程序研究如何投放針對(duì)我們的廣告生成大量數(shù)據(jù)集。Facebook的聰明之處在于，所有用戶都在不知不覺中為該公司免費(fèi)工作，創(chuàng)造了其最有價(jià)值的產(chǎn)品。
That enables Facebook to pay out the equivalent of just 1 per cent of the company’s market value to its own employees, compared with 40 per cent at Walmart. We have all been seduced by the “siren servers”, as Jaron Lanier, the author and Microsoft researcher, has called them.
這使得Facebook的員工開支僅相當(dāng)于公司市值的1%，而沃爾瑪(Walmart)的這一比例為40%。我們都受到了被作家、微軟(Microsoft)研究員杰倫•拉尼爾(Jaron Lanier)稱為“海妖服務(wù)器”的誘惑。
Naturally, most of the Silicon Valley crowd see little wrong with our implicit digital contract. Hal Varian, Google’s chief economist, argues that consumers receive immensely popular, convenient services for free. Advertisers benefit from cheap, effective targeting of audiences. If users do not like Google’s offer then they can easily switch to other services. Rivals can generate, and buy in, their own data unencumbered. Competition is but a click away.
當(dāng)然，硅谷多數(shù)人士并不認(rèn)為我們的隱性數(shù)字合同有什么問題。谷歌(Google)首席經(jīng)濟(jì)學(xué)家哈爾•瓦里安(Hal Varian)辯稱，消費(fèi)者免費(fèi)得到了廣為流行、便捷的服務(wù)。廣告商獲益于針對(duì)受眾的低成本、有效廣告投放。如果用戶不喜歡谷歌提供的內(nèi)容，那么他們可以輕松切換到其他服務(wù)。競爭對(duì)手可以毫無阻礙地生成、買進(jìn)他們自己的數(shù)據(jù)。競爭不過是輕輕敲擊鍵盤。
That argument may hang together if you regard user data as capital created and owned by the technology companies. But a team of technologists and academics, including Mr Lanier, has published a paper challenging that conception. They argue that data are better viewed as the product of labour, rather than the byproduct of leisure.
如果你把用戶數(shù)據(jù)視為由科技公司創(chuàng)造和擁有的資本，那么上述理由或許還算成立。但包括拉尼爾在內(nèi)的一個(gè)技術(shù)專家和學(xué)者團(tuán)隊(duì)發(fā)表了一篇論文，質(zhì)疑了上述概念。他們認(rèn)為，數(shù)據(jù)更應(yīng)該被視為勞動(dòng)的產(chǎn)物，而非休閑的副產(chǎn)品。
The data economy has developed by accident rather than design, is inefficient, unfair and unproductive, and should be radically rethought, they contend. They draw a distinction between what they call our existing Data as Capital (DaC) model, which treats data as the “exhaust” products of consumption and the feedstock for surveillance capitalism, and a theoretical Data as Labour (DaL) model, which would treat data as user-generated possessions that should primarily benefit their owners.
他們認(rèn)為，數(shù)據(jù)經(jīng)濟(jì)是偶然形成的，并非通過設(shè)計(jì)實(shí)現(xiàn)，是低效、不公平和沒有收益的，應(yīng)該從根本上進(jìn)行反思。要區(qū)別對(duì)待我們現(xiàn)有的“數(shù)據(jù)作為資本”(DaC)模型——即將數(shù)據(jù)視為消費(fèi)的“廢氣”產(chǎn)品和“監(jiān)控資本主義”的原料——與“數(shù)據(jù)作為勞動(dòng)”(DaL)模型——即將數(shù)據(jù)視為由用戶生成的財(cái)產(chǎn)，應(yīng)首先讓其所有者受益。
They appeal to labour market economists and entrepreneurs to help shape a real market for users’ data. Such a market would pay people for their data, creating new jobs, nurturing a culture of “digital dignity”, and boosting the productivity of the economy.
他們呼吁勞動(dòng)力市場(chǎng)經(jīng)濟(jì)學(xué)家和企業(yè)家?guī)椭蛟煲粋€(gè)真正的用戶數(shù)據(jù)市場(chǎng)。此類市場(chǎng)將為人們的數(shù)據(jù)付費(fèi)，創(chuàng)造新的就業(yè)機(jī)會(huì)，培育“數(shù)字尊嚴(yán)”文化，提高經(jīng)濟(jì)的生產(chǎn)率。
That argument is developed in Radical Markets, a forthcoming book by Eric Posner and Glen Weyl, which is both a savage critique of “techno-feudalism” and an idealistic appeal to share the fruits of our collective intelligence more fairly. “The current model of data ownership,” says Mr Weyl, “is economically inefficient.”
上述觀點(diǎn)是埃里克•波斯納(Eric Posner)和格倫•韋爾(Glen Weyl)在即將出版的《Radical Markets》一書中提出的。該書既是對(duì)“技術(shù)-封建主義”的猛烈批判，也是對(duì)更公平地分享我們的集體智慧成果的一種理想主義呼吁。韋爾表示：“目前的數(shù)據(jù)所有權(quán)模式，在經(jīng)濟(jì)上是低效的。”
Mr Lanier and his co-authors acknowledge it is simplistic to view the DaC and DaL models as binary. They also accept that paying people for data is problematic in the real world. Some experiments by Microsoft and others to reward users for data have been immediately gamed by bots.
拉尼爾和論文的其他合著者承認(rèn)，將DaC模型和DaL模型視為非此即彼是將問題簡單化了。他們也承認(rèn)，在現(xiàn)實(shí)世界為數(shù)據(jù)向個(gè)人付費(fèi)存在問題。微軟等公司為獲得數(shù)據(jù)而獎(jiǎng)勵(lì)用戶的一些試驗(yàn)立刻就被機(jī)器人戲耍了。
It may also be a hard sell to convince a sceptical public that some of the most Stakhanovite “workers” in their model data economy might be marginalised teenage gaming addicts, even if the authors argue their case well.
此外，或許很難讓持懷疑態(tài)度的公眾相信，他們的模型數(shù)據(jù)經(jīng)濟(jì)中，一些最具勞動(dòng)競賽精神的“工人”可能是那些被邊緣化的青少年游戲成癮者，即使文章論據(jù)鑿鑿。
To shunt the data economy in the right direction, they suggest we need to strengthen three countervailing powers. First, greater competition and innovation are essential for stimulating real data markets. Big Tech should not be allowed to stifle smaller upstarts. Indeed, it may even take one of the big technology companies to break ranks and champion a new data economy given the daunting economies of scale.
為了引導(dǎo)數(shù)據(jù)經(jīng)濟(jì)轉(zhuǎn)向正確方向，論文作者們建議我們需要加強(qiáng)三大抗衡力量。首先，更激烈的競爭和創(chuàng)新對(duì)于刺激真正的數(shù)據(jù)市場(chǎng)至關(guān)重要。不應(yīng)允許大型科技公司扼殺較小的初創(chuàng)企業(yè)。實(shí)際上，考慮到令人生畏的規(guī)模經(jīng)濟(jì)，甚至可能需要一家大型科技公司來沖破束縛，支持新的數(shù)據(jù)經(jīng)濟(jì)。
Second, governments need to update and enforce competition policy, encouraging data portability and the growth of the DaL economy. Stricter regulatory regimes, such as the EU’s General Data Protection Regulation, which comes into effect in May, should help.
其次，政府需要升級(jí)、貫徹競爭政策，鼓勵(lì)數(shù)據(jù)可移植性和DaL經(jīng)濟(jì)增長。更嚴(yán)格的監(jiān)管制度，如將于今年5月生效的歐盟《一般數(shù)據(jù)保護(hù)條例》(General Data Protection Regulation)，應(yīng)該有所幫助。
Finally, we consumers should wise up to our role as digital workers and — in Marxist terminology — develop “class consciousness”. Data labour unions need to emerge to fight for our collective rights. The historic approach of labour to overmighty capital has been to strike. We may know the DaL movement is serious when we start digitally picketing social media groups under the slogan: “No posts without pay!”
最后，我們消費(fèi)者應(yīng)該認(rèn)識(shí)到自己作為數(shù)字工作者的角色，并形成“階級(jí)意識(shí)”(用馬克思主義術(shù)語)。需要建立數(shù)據(jù)工會(huì)，為我們的集體權(quán)利而斗爭。歷史上勞工對(duì)抗強(qiáng)大資本的做法一直是罷工。當(dāng)我們開始在“沒有報(bào)酬不發(fā)帖”的口號(hào)下，用數(shù)字方式對(duì)抗社交媒體集團(tuán)時(shí)，我們就會(huì)知道DaL運(yùn)動(dòng)是嚴(yán)肅的。
[email protected] 譯者/何黎
