考研閱讀精選：慷慨行為的進化歷程

『人類對陌生人友好的沖動并非是生理異常。』

　　The evolution of generosity：Welcome, stranger

　　慷慨行為的進化歷程：歡迎你，陌生人

　　Jul 30th 2011 | from the Economist

　　THE extraordinary success of Homo sapiens  is a result of four things: intelligence, language, an ability to manipulate objects dexterously  in order to make tools, and co-operation. Over the decades the anthropological  spotlight has shifted from one to another of these as the prime mover  of the package, and thus the fundament of the human condition. At the moment co-operation is the most fashionable subject of investigation. In particular, why are humans so willing to collaborate with unrelated strangers, even to the point of risking being cheated by people whose characters they cannot possibly know?

　　Evidence from economic games played in the laboratory for real money suggests humans are both trusting of those they have no reason to expect they will ever see again, and surprisingly unwilling to cheat them—and that these phenomena are deeply ingrained in the species’s psychology.  Existing theories of the evolution of trust depend either on the participants being relatives (and thus sharing genes) or on their relationship being long-term, with each keeping count  to make sure the overall benefits of collaboration exceed the costs. Neither applies in the case of passing strangers, and that has led to speculation that something extraordinary, such as a need for extreme collaboration prompted by the emergence of warfare that uses weapons, has happened in recent human evolution to promote the emergence of an instinct for unconditional generosity .

　　Leda Cosmides and John Tooby, two doyens  of the field, do not agree. They see no need for extraordinary mechanisms  and the latest study to come from their group suggests they are right.

　　Studying human evolution directly is obviously impossible. The generation times are far too long. But it is possible to isolate features of interest and examine how they evolve in computer simulations . To this end Dr Delton and Dr Krasnow designed software agents that were able to meet up and interact in a computer’s processor.

　　The agents’ interactions mimicked  those of economic games in the real world, though the currency was arbitrary  “fitness units” rather than dollars. This meant that agents which successfully collaborated built up  fitness over the period of their collaboration. Those that cheated on the first encounter  got a one-off  allocation  of fitness, but would never be trusted in the future. Each agent had an inbuilt and heritable level of trustworthiness (ie, the likelihood that it would cheat at the first opportunity) and, in each encounter it had, it was assigned a level of likelihood (detectable by the other agent) that it would be back for further interactions.

　　After a certain amount of time the agents reproduced in proportion to their accumulated fitness; the old generation died, and the young took over. The process was then repeated for 10,000 generations to see what level of collaboration would emerge.

　　The upshot  was that, as the researchers predicted, generosity pays —or, rather, the cost of early selfishness is greater than the cost of trust. For most plausible  sets of costs, benefits and chances of future encounters the simulation found that it pays to be trusting, even though you will sometimes be cheated. Previous attempts to study the evolution of trust using games have been arranged to make it clear to the participants whether their encounter was a one-off, and drawn their conclusions accordingly. That, though, is hardly realistic. In the real world, although you might guess, based on the circumstances, whether or not you will meet someone again, you cannot know for sure. Moreover, in the ancient world of hunter-gatherers, limited movement meant a second encounter would be much more likely than it is in the populous , modern urban world.

　　No need, then, for special mechanisms to explain generosity. An open hand to the stranger makes evolutionary as well as moral sense. (743 words)

  Homo sapiens /9hEUmEU 5sApIenz/ n. 智人（全比現代人的屬和種）
  dexterously /5dekstrEslI/ adj. 善于用手的；手巧的
  anthropological /9AnWrEpE5lCdVIkl/ adj. 人類學的
  prime mover n. 發起者；推動者；原動力
  人們在實驗室里進行了一項可以贏現金的經濟游戲，其中所得證據表明，人們不僅會相信那些沒理由期待還會再次碰面的人，而且會莫名其妙地不愿意欺騙他們。這些現象已經在人類的心理意識中根深蒂固了。ingrained(in sth)：根深蒂固的；日久難改的
  keep count：（在一段時間內）記錄變化的數字，如：I never manage to keep count of what I spend on my credit card. （我從來都記不清信用卡的支出。)
generosity /9dVenE5rCsEtI/ n. 慷慨或寬容的行為
  doyen /5dRIEn/ n. （團體、職業等的）資深者，老前輩
  mechanism /5mekEnIzEm/ n. （生物用來自我保護的、躲避危險的）機制，行為方式
  simulation /9sImjU5leIFn/ n. 模擬操作
  mimic /5mImIk/ v. 模仿（人的行為舉止）
  arbitrary /5B:bItrErI/ adj. 任意的；主觀的
  build up：（使）積累；增強，如：You have to build up trust.（你必須建立起信任。）
  encounter /In5kaUntE(r)/ n. 相遇；邂逅
  one-off adj. 只發生一次的；一次完成的
  allocation /9AlE5keIFn/ n. （錢、 地方等的）配給量
  每一個軟件代理人內在都有可繼承的信賴度（即他可能一有機會就會欺騙別人），在每次與他人相遇的時候，計算機都會安排他可能在以后的交往中還會出現，（這種可能性也是其他代理人可以察覺到的）。at the first opportunity：一有機會（就）
  upshot /5QpFCt/ n. 比較后的結果；結局
  pay /peI/ v. 受益；劃算，如：Crime doesn't pay. （犯罪是得不償失的。）
  plausible /5plR:zEbl/ adj.（指陳述、 借口等）似乎正確的，似有道理的