If you're wondering why your peers seem to be prospering way more than you are, it might not be because they're better at their jobs: it's probably just down to random chance, according to a new computer model of wealth simulation.
如果你奇怪你的同龄人为什么比你混得更好,这也许并不是因为他们更能干,而很可能只是因为他们运气好。这是电脑上的财富模拟模型计算出的最新结果。
Charting a working lifespan of 40 years, the detailed computer simulation accurately reproduced the wealth distribution model of the real world, but found that those at the top of the money pile were the luckiest, not the most talented.
借助于这一详细的模拟算法,电脑准确再现了40年间现实世界的财富分布模式,但却发现,拥有最多财富的是最幸运的那些人,而不是最有才华的那些人。

The aim of the study from researchers at the University of Catania in Italy is not to make you despair at the futility of life, but to understand the role that chance plays in the way we invest our time and resources in multiple fields.
意大利卡塔尼亚大学的研究人员开展的这项研究,目的不是要让你哀叹人生的徒劳,而在于让你理解我们在各个领域投入时间和资源时运气所发挥的作用。
The conundrum they set out to solve is this: if talent, intelligence, willingness to work and other factors that would typically help you get on in life are quite evenly distributed among the population, why isn't wealth?
研究人员想要解决的难题是:如果才华、智力、工作积极性和其他能帮你在人生中获得成功的因素在人群中是均匀分布的,那么为什么财富不是均匀分布的呢?
Broadly speaking, 10 percent of humanity enjoys 85 percent of the wealth, but talent and smartness aren't hoarded by a select few to anywhere near the same extent – so what's the hidden ingredient?
广义地说,10%的人享有85%的财富,但才华和智慧并不是专属于少数一部分人,有才和聪明的人远远不止10%,那么隐含的致富秘方是什么呢?
"Our simulation clearly shows that such a factor is just pure luck," write the researchers.
研究人员写道:“我们的模型清楚地显示,这种因素就是纯粹的运气。”
The team started off with 1,000 computer-generated individuals, or agents, though the model can be adapted to any size. Talent is distributed normally around an average level, with some standard deviation – so in the model, everyone has some talent, but no one has a huge amount more or less than anyone else.
该研究团队用电脑生成了1000个个体(模型可生成无限多个个体),才华均匀地分布在每个个体上,部分个体有一些标准偏差,也就是说,在模型中,每个人都有一些才华,但没有哪个人的才华和其他人差距很大。
Meanwhile, everyone starts off with the same level of wealth.
与此同时,每个人的财富值在起点都是同样多的。
Random events are then introduced into the simulation, which the agents can use to increase their wealth if they're lucky, or which hit their wealth levels if they're unlucky.
之后模型引入了一些随机的事件,如果幸运的话,一些个体可以借助这些事件来增加他们的财富,如果运气差的话,这些事件会让部分个体的财富减少。
When the final results were analysed, the wealth distribution looked much like it does in the real world, with around 20 percent of people owning 80 percent of the wealth. The simulation was repeated several times to check its integrity.
在分析最终结果时,财富的分布和现实世界非常相似,20%的人拥有80%的财富。模型重复运行了好几次,来确认其一致性。
But the wealthiest 20 percent were not the most talented 20 percent, or indeed the least talented 20 percent: "the maximum success never coincides with the maximum talent, and vice-versa" according to the researchers.
但是最富有的20%并不是最有才华的20%,也不是最没有才华的20%,研究人员表示:“最大的成功从来也不会和最多的才华重合,反之亦然。”
In fact, the top earners ended up being those with talent somewhere near the general average. What's more, the people at the top of the wealth pyramid had experienced the luckiest events during their simulated lives, while those at the bottom had been hit by the unluckiest ones.
事实上,最后挣得最多的人往往是那些才华接近平均线的人。而且,位于财富金字塔顶层的人在模拟人生中经历过最幸运的事情,而那些位于金字塔底层的人曾遭遇过最不幸的事情。
The team behind the study now want to explore how the model can be used to maximise investments in everything from science funding to business practices. For example, it may be wise to invest resources equally among companies, rather than focusing on the people who've been most successful in the past, if luck plays such a big role.
该研究团队现在想探究如何运用模型实现科学基金和商务活动等各种投资的收益最大化。打个比方,如果运气是如此重要,也许明智的做法是将资源均等地投入到多个公司,而不是将资源投入到以往最成功的那些人身上。
"If it is true that some degree of talent is necessary to be successful in life, almost never the most talented people reach the highest peaks of success, being overtaken by mediocre but sensibly luckier individuals," conclude the researchers.
研究人员总结道:“即便一定程度的才华确实是成功人生的必要条件,但是最有才华的人往往不能获得最大的成功,打败他们的是那些资质平凡但相当幸运的人。”
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