Social media users of the world unite!

Social media users of the world unite!
全世界社交媒体用户联合起来！
If Plato were alive today, he might well regard much of the work we do as leisure, and much of the
leisure we enjoy as work. Those extravagantly paid Davosian chief executives who jet around the
world discussing the great issues of the day are in fact indulging in an endless swirl of symposia. But
Plato would probably look askance at others who enjoy fishing, gardening and cooking, and view
those activities as laborious occupations.
如果柏拉图(Plato)今天还活着，他很可能会把我们做的大部分工作视为休闲，而把我们享受的
多数休闲时光视为工作。那些拿着超高薪水、穿梭世界各地讨论全球大事的首席执行官们，实
际上是在享受无休止的酒会。但柏拉图很可能会用怀疑的眼神看待那些享受钓鱼、园艺和烹饪
的人，认为这些活动是辛苦的职业。
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.
在英国《金融时报》近期举办的一场会议上，捷克哲学家托马斯•塞德拉切克(Tomas Sedlacek)
就如此论证，并称自己参加会议就是在工作。他的观点（我认为）主要意在通过刺激人们思考，
来突显我们对工作和休闲的定义更依赖于文化背景，而非不可更改的社会规律。
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，如果我们将一些概念分类抛诸脑后，肯定会帮助我们解开数字经济中的一些谜题。
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.
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以社交媒体为例。Facebook、Instagram、Twitter 和 YouTube 的用户或许认为只是在分享自己
的特别时刻、诙谐见解以及与朋友和家人的滑稽恶作剧。所有这些活动丰富了我们的生活，加
深了我们的社会联系，带来了乐趣和自由的闲暇时光。
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，从另一角度看，我们像母鸡啄米一样盯着手机所做的一切，都在为机器学习程序研究如
何投放针对我们的广告生成大量数据集。Facebook 的聪明之处在于，所有用户都在不知不觉
中为该公司免费工作，创造了其最有价值的产品。
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.
这使得 Facebook 的员工开支仅相当于公司市值的 1%，而沃尔玛(Walmart)的这一比例为 40%。
我们都受到了被作家、微软(Microsoft)研究员杰伦•拉尼尔(Jaron Lanier)称为“海妖服务器”的
诱惑。
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.
当然，硅谷多数人士并不认为我们的隐性数字合同有什么问题。谷歌(Google)首席经济学家哈
尔•瓦里安(Hal Varian)辩称，消费者免费得到了广为流行、便捷的服务。广告商获益于针对受
众的低成本、有效广告投放。如果用户不喜欢谷歌提供的内容，那么他们可以轻松切换到其他
服务。竞争对手可以毫无阻碍地生成、买进他们自己的数据。竞争不过是轻轻敲击键盘。
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.
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如果你把用户数据视为由科技公司创造和拥有的资本，那么上述理由或许还算成立。但包括拉
尼尔在内的一个技术专家和学者团队发表了一篇论文，质疑了上述概念。他们认为，数据更应
该被视为劳动的产物，而非休闲的副产品。
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.
他们认为，数据经济是偶然形成的，并非通过设计实现，是低效、不公平和没有收益的，应该
从根本上进行反思。要区别对待我们现有的“数据作为资本”(DaC)模型——即将数据视为消
费的“废气”产品和“监控资本主义”的原料——与“数据作为劳动”(DaL)模型——即将数
据视为由用户生成的财产，应首先让其所有者受益。
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.
他们呼吁劳动力市场经济学家和企业家帮助打造一个真正的用户数据市场。此类市场将为人们
的数据付费，创造新的就业机会，培育“数字尊严”文化，提高经济的生产率。
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.”
上述观点是埃里克•波斯纳(Eric Posner)和格伦•韦尔(Glen Weyl)在即将出版的《Radical
Markets》一书中提出的。该书既是对“技术-封建主义”的猛烈批判，也是对更公平地分享我
们的集体智慧成果的一种理想主义呼吁。韦尔表示：“目前的数据所有权模式，在经济上是低
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.
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拉尼尔和论文的其他合著者承认，将 DaC 模型和 DaL 模型视为非此即彼是将问题简单化了。
他们也承认，在现实世界为数据向个人付费存在问题。微软等公司为获得数据而奖励用户的一
些试验立刻就被机器人戏耍了。
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，或许很难让持怀疑态度的公众相信，他们的模型数据经济中，一些最具劳动竞赛精神的
“工人”可能是那些被边缘化的青少年游戏成瘾者，即使文章论据凿凿。
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.
为了引导数据经济转向正确方向，论文作者们建议我们需要加强三大抗衡力量。首先，更激烈
的竞争和创新对于刺激真正的数据市场至关重要。不应允许大型科技公司扼杀较小的初创企
业。实际上，考虑到令人生畏的规模经济，甚至可能需要一家大型科技公司来冲破束缚，支持
新的数据经济。
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，政府需要升级、贯彻竞争政策，鼓励数据可移植性和 DaL 经济增长。更严格的监管制
度，如将于今年 5 月生效的欧盟《一般数据保护条例》(General Data Protection Regulation)，应
该有所帮助。
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!”
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最后，我们消费者应该认识到自己作为数字工作者的角色，并形成“阶级意识”（用马克思主
义术语）。需要建立数据工会，为我们的集体权利而斗争。历史上劳工对抗强大资本的做法一
直是罢工。当我们开始在“没有报酬不发帖”的口号下，用数字方式对抗社交媒体集团时，我
们就会知道 DaL 运动是严肃的。