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第54行： − == History ==+ − left|thumb|H.G.Wells World Brain (1936-1938)这个概念(虽然不是这样命名的)起源于1785年的美国马奎斯·孔多塞，其“陪审团定理”指出，如果一个投票群体的每个成员更有可能做出正确的决定，那么该群体中投票最多的成员是正确决定的概率随着该群体成员数量的增加而增加(见 Condorcet 的陪审团定理)。许多理论家对亚里士多德在《政治学》中的一句话进行了解释，即“多人参与的盛宴胜过一个钱包提供的晚餐”，这意味着正如许多人可以将不同的菜肴端上餐桌，因此在商议中许多人可能贡献不同的信息，以产生一个更好的决定。然而，最近的学术研究表明，这可能不是亚里士多德的意思，而是基于我们现在所知道的团队智力的现代解释。 第90行：
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第185行： − 个人智力被证明受到遗传和环境的影响。类似地，集体智力研究的目的是探索为什么某些群体比其他群体表现得更聪明，因为 c 只是与个体群体成员的智力适度相关。根据伍利等人的研究。研究结果表明，团队凝聚力、团队动机和团队满意度与 c 均无相关性，但有三个因素显著相关: 说话次数的差异、团队成员的平均社会敏感度和女性比例。三者对 c 的预测能力相似，但只有社会敏感性具有统计学意义(b = 0.33，p = 0.05)。+ 第217行：
第216行： − = = = 过程 = = 拇指 | 集体智慧因子 c 的预测因子，由 Woolley，Aggarwal & Malone (2015)提出+ 第224行：
第223行： − = = = = 自顶向下过程 = = = 自顶向下过程覆盖了组交互，例如结构、过程和规范。这种自顶向下流程的一个例子是会话转换。研究进一步表明，集体智慧群体的沟通更加普遍，也更加平等; 参与也是如此，表现在面对面的交流以及仅通过书面交流的在线群体上。+ 第231行：
第230行： − = = = = 自下而上的过程 = = = 自下而上的过程包括群组成分，即集合到团队一级的群组成员的特征。这种自下而上的过程的一个例子是群体成员的平均社会敏感度或平均和最高智力分数。此外，集体智力与一个群体的认知多样性有关，包括思维方式和观点。认知方式适度多样化的群体比认知方式非常相似或非常不同的群体有更高的集体智慧。因此，成员太相似的群体缺乏表现良好所需的各种观点和技能。另一方面，成员差异太大的群体似乎难以有效地沟通和协调。+ 第237行：
第236行： − + 第264行：
第263行： − + 第295行：
第294行： − = = = 预测有效性 = = = 除了预测一个小组在更复杂的标准任务上的表现之外，集体智慧因子 c 也被发现可以预测一个小组在持续几个月的 MBA 课程中在不同任务上的表现。因此，高度集体智力的小组在他们的小组作业中获得了显著的高分，尽管他们的成员在其他单独完成的作业中并没有表现得更好。此外，高度集体智慧的团队随着时间的推移提高了性能，这表明更多集体智慧的团队学得更好。这是另一个与个人智力相似的潜在因素，在个人智力中，越聪明的人获取新知识的速度越快。+ 第308行：
第307行： − = = = 个人智力的潜在联系 = = 格拉德威尔(2008)表明，个人智商和成功之间的关系只在一定程度上起作用，超过估计的智商120的额外智商点不会转化为现实生活中的优势。如果类似的边界存在的群体智商或优势是线性和无限的，仍然有待探索。同样，在许多其他可以转移的个体智慧逻辑中，也存在着对个体智慧和集体智慧之间可能存在的联系进一步研究的需求，例如，随着时间的推移而产生的发展或提高智力的问题。虽然人类的智力是否可以通过培训得到提高还存在争议，但是一个群体的集体智力可能通过交换团队成员或实施结构和技术提供更简单的改进机会。此外，社会敏感性被发现，至少是暂时的，可以通过阅读文学小说和观看戏剧电影来改善。在多大程度上这种培训最终通过社会敏感性提高集体智慧仍然是一个悬而未决的问题。+ 第321行：
第320行： − = = 争议 = = = 其他学者通过将团队成员的一般智力汇总到团队水平来解释团队绩效，而不是建立一个自己的整体集体智力测量。Devine 和 Philips (2001)在一项荟萃分析中指出，认知能力可以预测实验室环境(0.37)和现场环境(0.14)下的团队表现。注意，这只是一个很小的影响。其他学者的研究表明，对相关任务的依赖性很强，需要高度沟通和合作的任务被认为受认知能力最低的团队成员影响最大。选择最好的团队成员是最成功的策略的任务，被证明受认知能力最高的成员的影响最大。+ 第343行：
第342行： − = = = = = = = 计算集体智慧 = = = = 拇指 | 计算集体智慧 Tadeusz Szuba 2001年，波兰 AGH 大学的 Tadeusz (Tad) Szuba 提出了一个集体智慧现象的正式模型。它被认为是一个无意识的、随机的、平行的、分布式的计算过程，通过社会结构在数理逻辑中运行。计算集体智能，420页，Wiley NY，2001+ 第356行：
第355行： − = = = 集体智商 = = = 有时候，特别是更多的人工智能理论家采用的一个衡量标准是“集体智商”(或者“合作商数”)——可以从“个人”智商(IQ)中归一化——从而有可能确定每个新加入集体行动的个人所增加的边际智力，从而使用衡量标准来避免集体思维和愚蠢的危害。+ 第362行：
第361行： − + 第375行：
第374行： − = = = 引出点估计 = = = 在这里，我们的目标是得到某事物的估计(在一个单一的值中)。例如，估计一个对象的重量，或者一个产品的发布日期，或者一个项目的成功概率等等。在 Intrade、 HSX 或 InklingMarkets 等预测市场，以及诸如德尔福(Delphi)方法等数字结果的众包估计实现中都可以看到这种情况。本质上，我们试图得到人群中成员提供的估计值的平均值。+ 第382行：
第381行： − 在这种情况下，从群众中收集关于一个想法、问题或产品的意见。例如，试图获得在线销售产品的评级(在一定规模上)(如亚马逊的星级评级系统)。这里的重点是收集并简单地汇总客户/用户提供的评级。+ 第418行：
第417行： − = = = = 政治和技术预测 = = = 拇指 | 美国2016年选举方法政党动员大量人民制定政策，选择候选人，资助和开展竞选活动。通过各种投票方法聚焦的知识可以通过假设无知投票在某种程度上是随机的，并且可以从决策过程中过滤掉，只留下知情共识的残留，从而使观点趋于一致。批评人士指出，经常存在错误的想法、误解和误解，决策过程的结构必须有利于专家，因为他们可能不太容易在特定情况下进行随机或错误信息的投票。+ 第434行：
第433行： − 2012年,”千年项目”创建了全球未来集体智慧系统(GFIS) ，它集中体现了集体智慧，即数据/信息/知识、软件/硬件以及专门知识/见解之间的协同交汇，具有一个学习过程，比单个行为者更好地作出决策。+ 第481行：
第480行： − 泰普斯科特和威廉姆斯进行的研究提供了集体智慧对商业的好处的几个例子:+ 第504行：
第503行： − 文化理论家和在线社区开发者约翰 · 班克斯认为在线粉丝社区对 Trainz 产品的创造做出了贡献。他认为，其商业成功从根本上取决于“一个活跃而充满活力的在线粉丝社区的形成和发展，这个社区将积极推广该产品，并为游戏软件提供内容扩展和附加功能”。约翰 · a · l。银行。在新媒体环境下谈判参与式文化: Auran 和 Trainz 在线社区-可能的关系，昆士兰大学。英语、媒体研究与艺术史学院。墨尔本2003+ 第523行：
第522行： − 合作的好处有助于解决最重要和最有趣的多学科问题。詹姆斯•索罗维茨基(James Surowiecki)在他的书中提到，大多数科学家认为，与潜在成本相比，合作的好处更有价值。合作之所以奏效，还因为它充其量只能保证不同观点的数量。由于技术的可能性，全球合作现在比以前更加容易和富有成效。很明显，当合作从大学层面进入全球层面时，它会带来显著的好处。+ 第537行：
第536行： − * = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = =.在线广告公司正在利用集体智慧来绕过传统的市场营销和创意机构。“ web2.0服务业平台领导力的成功因素。”服务业4.2(2010) : 89-103。+ 第570行：
第569行： − 即兴表演》的演员们学到了一堂关于即兴表演和生活的重要课程，即兴表演的演员们也体验到一种他们称之为“群体智慧”的集体智慧，因为戏剧性的即兴表演依赖于相互合作和协议，从而形成“群体智慧”的统一。+ 第589行：
第588行： − = = = = = 不同类型任务的协调 = = = = 集体行动或任务需要不同数量的协调，这取决于任务的复杂程度。任务从高度独立的简单任务到复杂的相互依赖的任务，这些任务是由许多个人构建的，需要大量的协调。在 Kittur、 Lee 和 Kraut 撰写的文章中，作者介绍了合作中的一个问题:”当任务需要高度协调，因为工作是高度相互依赖的，有更多的贡献者可能会增加流程损失，降低团队的效率，低于个人成员可以最佳完成的水平”。即使额外的捐助者增加了资源，如果团队过于庞大，整体效率可能会受到影响。最后，协调的总成本可能会超过其他成本。“集体智慧中的协调: 团队结构和任务相互依赖的作用”，计算机系统中的人为因素会议论文集，页。1495–1504.+ 第602行：
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第614行： − = = 与智力分离 = = 菲利普 · 布朗和休 · 兰黛引用鲍尔斯和金蒂斯(1976)的话，为了真正定义集体智力，将智力与智力分离是至关重要的。他们继续争辩说，智力是一种成就，只有在被允许的情况下才能得到发展。例如，早些时候，来自社会底层的群体在聚集和汇集他们的智力方面受到严格限制。这是因为精英们害怕集体智慧会说服人民起来反抗。如果没有这种能力和关系，就不会有建立集体智慧的基础设施。这反映了如果任其发展，集体智慧是多么强大。+ 第622行：
第621行： − 怀疑论者，尤其是那些对人工智能持批评态度的人，更倾向于相信身体伤害和身体行为的风险是人与人之间一切团结的基础，更可能强调一个群体采取行动和承受伤害的能力，就像体液政治动员一样，对伤害置之不理，就像身体对少数细胞的损失置之不理一样。这种思路在反全球化运动和拥有属性的 John Zerzan，Carol Moore 和 Starhawk 的著作中最为明显，他们通常回避学者。这些理论家更可能提到生态和集体智慧以及协商一致进程在作出本体论区分方面的作用，而不是任何形式的”智慧”本身，因为他们常常认为这种智慧并不存在，或者仅仅是”聪明”。+ 第697行：
第696行： − = = = = 相似的概念和应用 = = = = 公民科学 + + − + + 第714行：
第715行： − + + + − * 维基 − + 第743行：
第745行： − 计算和计算机科学 = = = 蜜蜂算法 + + 第751行：
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第819行： − = = = 引用作品 = = = + − * + + 第1,117行：
第954行： − = = 进一步阅读 = = + + + − + +
Moved page from wikipedia:en:Collective intelligence (history)
The concept (although not so named) originated in 1785 with the Marquis de Condorcet, whose "jury theorem" states that if each member of a voting group is more likely than not to make a correct decision, the probability that the highest vote of the group is the correct decision increases with the number of members of the group (see Condorcet's jury theorem). Many theorists have interpreted Aristotle's statement in the Politics that "a feast to which many contribute is better than a dinner provided out of a single purse" to mean that just as many may bring different dishes to the table, so in a deliberation many may contribute different pieces of information to generate a better decision. Recent scholarship, however, suggests that this was probably not what Aristotle meant but is a modern interpretation based on what we now know about team intelligence.
The concept (although not so named) originated in 1785 with the Marquis de Condorcet, whose "jury theorem" states that if each member of a voting group is more likely than not to make a correct decision, the probability that the highest vote of the group is the correct decision increases with the number of members of the group (see Condorcet's jury theorem). Many theorists have interpreted Aristotle's statement in the Politics that "a feast to which many contribute is better than a dinner provided out of a single purse" to mean that just as many may bring different dishes to the table, so in a deliberation many may contribute different pieces of information to generate a better decision. Recent scholarship, however, suggests that this was probably not what Aristotle meant but is a modern interpretation based on what we now know about team intelligence.
左手大拇指 | h.g。Wells World Brain (1936-1938)这个概念(虽然不是这样命名的)起源于1785年的美国马奎斯·孔多塞，其“陪审团定理”指出，如果一个投票群体的每个成员更有可能做出正确的决定，那么该群体中投票最多的成员是正确决定的概率随着该群体成员数量的增加而增加(见 Condorcet 的陪审团定理)。许多理论家对亚里士多德在《政治学》中的一句话进行了解释，即“多人参与的盛宴胜过一个钱包提供的晚餐”，这意味着正如许多人可以将不同的菜肴端上餐桌，因此在商议中许多人可能贡献不同的信息，以产生一个更好的决定。然而，最近的学术研究表明，这可能不是亚里士多德的意思，而是基于我们现在所知道的团队智力的现代解释。
A precursor of the concept is found in entomologist [[William Morton Wheeler]]'s observation that seemingly independent individuals can cooperate so closely as to become indistinguishable from a single organism (1910).<ref>Wheeler, W. M. (1910). Ants: their structure, development and behavior (Vol. 9). Columbia University Press.</ref> Wheeler saw this collaborative process at work in [[ants]] that acted like the cells of a single beast he called a [[superorganism]].
A precursor of the concept is found in entomologist [[William Morton Wheeler]]'s observation that seemingly independent individuals can cooperate so closely as to become indistinguishable from a single organism (1910).<ref>Wheeler, W. M. (1910). Ants: their structure, development and behavior (Vol. 9). Columbia University Press.</ref> Wheeler saw this collaborative process at work in [[ants]] that acted like the cells of a single beast he called a [[superorganism]].
Howard Bloom has discussed mass behavior – collective behavior from the level of quarks to the level of bacterial, plant, animal, and human societies. He stresses the biological adaptations that have turned most of this earth's living beings into components of what he calls "a learning machine". In 1986 Bloom combined the concepts of apoptosis, parallel distributed processing, group selection, and the superorganism to produce a theory of how collective intelligence works.Howard Bloom, The Lucifer Principle: A Scientific Expedition into the Forces of History, 1995 Later he showed how the collective intelligences of competing bacterial colonies and human societies can be explained in terms of computer-generated "complex adaptive systems" and the "genetic algorithms", concepts pioneered by John Holland.
Howard Bloom has discussed mass behavior – collective behavior from the level of quarks to the level of bacterial, plant, animal, and human societies. He stresses the biological adaptations that have turned most of this earth's living beings into components of what he calls "a learning machine". In 1986 Bloom combined the concepts of apoptosis, parallel distributed processing, group selection, and the superorganism to produce a theory of how collective intelligence works.Howard Bloom, The Lucifer Principle: A Scientific Expedition into the Forces of History, 1995 Later he showed how the collective intelligences of competing bacterial colonies and human societies can be explained in terms of computer-generated "complex adaptive systems" and the "genetic algorithms", concepts pioneered by John Holland.
复杂适应系统模型霍华德 · 布鲁姆讨论了从夸克层次到细菌、植物、动物和人类社会层次的大规模行为-集体行为。他强调了生物学上的适应性，这种适应性把地球上的大多数生物变成了他所说的“学习机器”的组成部分。1986年，Bloom 将细胞凋亡、并行分布式处理、群体选择和超个体等概念结合起来，提出了集体智慧是如何工作的理论。Howard Bloom，The Lucifer Principle: a Scientific Expedition into The Forces of History，1995后来，他展示了如何用计算机生成的“复杂适应系统”和“遗传算法”来解释相互竞争的细菌群落和人类社会的集体智能，这两个概念是由 John Holland 首创的。
复杂适应系统模型霍华德 · 布鲁姆讨论了从夸克到细菌、植物、动物和人类社会的大规模行为-集体行为。他强调了生物学上的适应性，这种适应性把地球上的大多数生物变成了他所说的“学习机器”的组成部分。1986年，Bloom 将细胞凋亡、并行分布式处理、群体选择和超个体等概念结合起来，提出了集体智慧是如何工作的理论。Howard Bloom，The Lucifer Principle: a Scientific Expedition into The Forces of History，1995后来，他展示了如何用计算机生成的“复杂适应系统”和“遗传算法”来解释相互竞争的细菌群落和人类社会的集体智能，这两个概念是由 John Holland 首创的。
Bloom traced the evolution of collective intelligence to our bacterial ancestors 1 billion years ago and demonstrated how a multi-species intelligence has worked since the beginning of life.<ref name="bloom2000">Howard Bloom, ''Global Brain: The Evolution of Mass Mind from the Big Bang to the 21st Century'', 2000</ref> Ant societies exhibit more intelligence, in terms of technology, than any other animal except for humans and co-operate in keeping livestock, for example [[aphid]]s for "milking".<ref name="bloom2000" /> Leaf cutters care for fungi and carry leaves to feed the fungi.<ref name="bloom2000" />
Bloom traced the evolution of collective intelligence to our bacterial ancestors 1 billion years ago and demonstrated how a multi-species intelligence has worked since the beginning of life.<ref name="bloom2000">Howard Bloom, ''Global Brain: The Evolution of Mass Mind from the Big Bang to the 21st Century'', 2000</ref> Ant societies exhibit more intelligence, in terms of technology, than any other animal except for humans and co-operate in keeping livestock, for example [[aphid]]s for "milking".<ref name="bloom2000" /> Leaf cutters care for fungi and carry leaves to feed the fungi.<ref name="bloom2000" />
Individual intelligence is shown to be genetically and environmentally influenced. Analogously, collective intelligence research aims to explore reasons why certain groups perform more intelligently than other groups given that c is just moderately correlated with the intelligence of individual group members. According to Woolley et al.'s results, neither team cohesion nor motivation or satisfaction is correlated with c. However, they claim that three factors were found as significant correlates: the variance in the number of speaking turns, group members' average social sensitivity and the proportion of females. All three had similar predictive power for c, but only social sensitivity was statistically significant (b=0.33, P=0.05).
Individual intelligence is shown to be genetically and environmentally influenced. Analogously, collective intelligence research aims to explore reasons why certain groups perform more intelligently than other groups given that c is just moderately correlated with the intelligence of individual group members. According to Woolley et al.'s results, neither team cohesion nor motivation or satisfaction is correlated with c. However, they claim that three factors were found as significant correlates: the variance in the number of speaking turns, group members' average social sensitivity and the proportion of females. All three had similar predictive power for c, but only social sensitivity was statistically significant (b=0.33, P=0.05).
个人的智力被证明受到遗传和环境的影响。类似地，集体智力研究的目的是探索为什么某些群体比其他群体表现得更聪明，因为 c 只是与个体群体成员的智力适度相关。根据伍利等人的研究。研究结果表明，团队凝聚力、团队动机和团队满意度与 c 均无相关性，但有三个因素显著相关: 说话次数的差异、团队成员的平均社会敏感度和女性比例。三者对 c 的预测能力相似，但只有社会敏感性具有统计学意义(b = 0.33，p = 0.05)。
The number speaking turns indicates that "groups where a few people dominated the conversation were less collectively intelligent than those with a more equal distribution of conversational turn-taking".<ref name=":4" /> Hence, providing multiple team members the chance to speak up made a group more intelligent.<ref name=":0" />
The number speaking turns indicates that "groups where a few people dominated the conversation were less collectively intelligent than those with a more equal distribution of conversational turn-taking".<ref name=":4" /> Hence, providing multiple team members the chance to speak up made a group more intelligent.<ref name=":0" />
thumb|Predictors for the collective intelligence factor c. Suggested by Woolley, Aggarwal & Malone (2015)
thumb|Predictors for the collective intelligence factor c. Suggested by Woolley, Aggarwal & Malone (2015)
拇指 | 集体智慧因子 c 的预测因子，由 Woolley，Aggarwal & Malone (2015)提出
==== Top-down processes ====
==== Top-down processes ====
Top-down processes cover group interaction, such as structures, processes, and norms. An example of such top-down processes is conversational turn-taking. Research further suggest that collectively intelligent groups communicate more in general as well as more equally; same applies for participation and is shown for face-to-face as well as online groups communicating only via writing.
Top-down processes cover group interaction, such as structures, processes, and norms. An example of such top-down processes is conversational turn-taking. Research further suggest that collectively intelligent groups communicate more in general as well as more equally; same applies for participation and is shown for face-to-face as well as online groups communicating only via writing.
自顶向下的过程包括组交互，如结构、过程和规范。这种自顶向下流程的一个例子是会话转换。研究进一步表明，集体智慧群体的沟通更加普遍，也更加平等; 参与也是如此，表现在面对面的交流以及仅通过书面交流的在线群体上。
==== Bottom-up processes ====
==== Bottom-up processes ====
Bottom-up processes include group composition, namely the characteristics of group members which are aggregated to the team level. An example of such bottom-up processes is the average social sensitivity or the average and maximum intelligence scores of group members. Furthermore, collective intelligence was found to be related to a group's cognitive diversity including thinking styles and perspectives. Groups that are moderately diverse in cognitive style have higher collective intelligence than those who are very similar in cognitive style or very different. Consequently, groups where members are too similar to each other lack the variety of perspectives and skills needed to perform well. On the other hand, groups whose members are too different seem to have difficulties to communicate and coordinate effectively.
Bottom-up processes include group composition, namely the characteristics of group members which are aggregated to the team level. An example of such bottom-up processes is the average social sensitivity or the average and maximum intelligence scores of group members. Furthermore, collective intelligence was found to be related to a group's cognitive diversity including thinking styles and perspectives. Groups that are moderately diverse in cognitive style have higher collective intelligence than those who are very similar in cognitive style or very different. Consequently, groups where members are too similar to each other lack the variety of perspectives and skills needed to perform well. On the other hand, groups whose members are too different seem to have difficulties to communicate and coordinate effectively.
自下而上的过程包括群体的组成，即群体成员的特征，这些特征集中体现在团队层面。这种自下而上的过程的一个例子是群体成员的平均社会敏感度或平均和最高智力分数。此外，集体智力与一个群体的认知多样性有关，包括思维方式和观点。认知方式适度多样化的群体比认知方式非常相似或非常不同的群体有更高的集体智慧。因此，成员太相似的群体缺乏表现良好所需的各种观点和技能。另一方面，成员差异太大的群体似乎难以有效地沟通和协调。
==== Serial vs Parallel processes ====
==== Serial vs Parallel processes ====
==== Serial vs Parallel processes ====
==== Serial vs Parallel processes ====
= = = = 串行与并行处理 = = = =
= = = = 串行与并行处理 = = = =
For most of human history, collective intelligence was confined to small tribal groups in which opinions were aggregated through real-time parallel interactions among members.<ref>{{Cite book|title=Moral tribes : emotion, reason, and the gap between us and them |last=Greene |first=Joshua David |isbn=978-0143126058 |oclc=871336785 |date=2014-12-30 |url-access=registration |url=https://archive.org/details/moraltribesemoti0000gree}}</ref> In modern times, mass communication, mass media, and networking technologies have enabled collective intelligence to span massive groups, distributed across continents and time-zones. To accommodate this shift in scale, collective intelligence in large-scale groups been dominated by serialized polling processes such as aggregating up-votes, likes, and ratings over time. In engineering, aggregating many engineering decisions allows for identifying typical good designs.<ref>{{Cite journal|last1=Bruch|first1=Marcel|last2=Bodden|first2=Eric|last3=Monperrus|first3=Martin|last4=Mezini|first4=Mira|date=2010|title=IDE 2.0: collective intelligence in software development|url=https://hal.archives-ouvertes.fr/hal-01575346/file/bbmm10ide.pdf|journal=Proceedings of the FSE/SDP Workshop on Future of Software Engineering Research - FoSER '10|doi=10.1145/1882362.1882374|s2cid=7637561}}</ref> While modern systems benefit from larger group size, the serialized process has been found to introduce substantial noise that distorts the collective output of the group. In one significant study of serialized collective intelligence, it was found that the first vote contributed to a serialized voting system can distort the final result by 34%.<ref>{{Cite journal|last1=Muchnik|first1=Lev|last2=Aral|first2=Sinan|last3=Taylor|first3=Sean J.|date=2013-08-09|title=Social Influence Bias: A Randomized Experiment|journal=Science|volume=341|issue=6146|pages=647–651|doi=10.1126/science.1240466|issn=0036-8075|pmid=23929980|bibcode=2013Sci...341..647M|s2cid=15775672}}</ref>
For most of human history, collective intelligence was confined to small tribal groups in which opinions were aggregated through real-time parallel interactions among members.<ref>{{Cite book|title=Moral tribes : emotion, reason, and the gap between us and them |last=Greene |first=Joshua David |isbn=978-0143126058 |oclc=871336785 |date=2014-12-30 |url-access=registration |url=https://archive.org/details/moraltribesemoti0000gree}}</ref> In modern times, mass communication, mass media, and networking technologies have enabled collective intelligence to span massive groups, distributed across continents and time-zones. To accommodate this shift in scale, collective intelligence in large-scale groups been dominated by serialized polling processes such as aggregating up-votes, likes, and ratings over time. In engineering, aggregating many engineering decisions allows for identifying typical good designs.<ref>{{Cite journal|last1=Bruch|first1=Marcel|last2=Bodden|first2=Eric|last3=Monperrus|first3=Martin|last4=Mezini|first4=Mira|date=2010|title=IDE 2.0: collective intelligence in software development|url=https://hal.archives-ouvertes.fr/hal-01575346/file/bbmm10ide.pdf|journal=Proceedings of the FSE/SDP Workshop on Future of Software Engineering Research - FoSER '10|doi=10.1145/1882362.1882374|s2cid=7637561}}</ref> While modern systems benefit from larger group size, the serialized process has been found to introduce substantial noise that distorts the collective output of the group. In one significant study of serialized collective intelligence, it was found that the first vote contributed to a serialized voting system can distort the final result by 34%.<ref>{{Cite journal|last1=Muchnik|first1=Lev|last2=Aral|first2=Sinan|last3=Taylor|first3=Sean J.|date=2013-08-09|title=Social Influence Bias: A Randomized Experiment|journal=Science|volume=341|issue=6146|pages=647–651|doi=10.1126/science.1240466|issn=0036-8075|pmid=23929980|bibcode=2013Sci...341..647M|s2cid=15775672}}</ref>
Woolley, Chabris, Pentland, Hashmi, & Malone (2010), the originators of this scientific understanding of collective intelligence, found a single statistical factor for collective intelligence in their research across 192 groups with people randomly recruited from the public. In Woolley et al.'s two initial studies, groups worked together on different tasks from the McGrath Task Circumplex, a well-established taxonomy of group tasks. Tasks were chosen from all four quadrants of the circumplex and included visual puzzles, brainstorming, making collective moral judgments, and negotiating over limited resources. The results in these tasks were taken to conduct a factor analysis. Both studies showed support for a general collective intelligence factor c underlying differences in group performance with an initial eigenvalue accounting for 43% (44% in study 2) of the variance, whereas the next factor accounted for only 18% (20%). That fits the range normally found in research regarding a general individual intelligence factor g typically accounting for 40% to 50% percent of between-individual performance differences on cognitive tests.
Woolley, Chabris, Pentland, Hashmi, & Malone (2010), the originators of this scientific understanding of collective intelligence, found a single statistical factor for collective intelligence in their research across 192 groups with people randomly recruited from the public. In Woolley et al.'s two initial studies, groups worked together on different tasks from the McGrath Task Circumplex, a well-established taxonomy of group tasks. Tasks were chosen from all four quadrants of the circumplex and included visual puzzles, brainstorming, making collective moral judgments, and negotiating over limited resources. The results in these tasks were taken to conduct a factor analysis. Both studies showed support for a general collective intelligence factor c underlying differences in group performance with an initial eigenvalue accounting for 43% (44% in study 2) of the variance, whereas the next factor accounted for only 18% (20%). That fits the range normally found in research regarding a general individual intelligence factor g typically accounting for 40% to 50% percent of between-individual performance differences on cognitive tests.
= = = 证据 = = alt = 标准化回归系数的集体智力因素 c 和群体成员的智力退回到两个标准的任务在伍利等人。在伍利等人的研究中发现的集体智慧因子 c 的标准化回归系数。2010年的两项原始研究。C 和平均(最大)成员智力得分回归于标准任务。Woolley，Chabris，彭特兰，Hashmi，and Malone (2010) ，集体智慧科学理解的发起者，在他们对192个随机从公众中招募的人的研究中发现了一个单一的集体智慧统计因素。在伍利等人的文章中。在麦格拉斯的两个初步研究中，研究小组共同完成了麦格拉斯环绕任务(McGrath Task Circumplex)中的不同任务。任务从复杂的四个象限中选择，包括视觉谜题、头脑风暴、做出集体道德判断以及在有限的资源上进行谈判。对这些任务的结果进行因子分析。两项研究都表明支持一般集体智力因素 c，在群体绩效的潜在差异中，最初的特征值占方差的43% (研究2中为44%) ，而下一个因素只占18% (20%)。这符合研究中通常发现的范围，一般个人智力因素 g 通常占个人认知测试成绩差异的40% 至50% 。
Alt = 集体智力因子 c 和群体成员智力的标准化回归系数在伍利等人的两个标准任务上回归。在伍利等人的研究中发现的集体智慧因子 c 的标准化回归系数。2010年的两项原始研究。C 和平均(最大)成员智力得分回归于标准任务。Woolley，Chabris，彭特兰，Hashmi，and Malone (2010) ，集体智慧科学理解的发起者，在他们对192个随机从公众中招募的人的研究中发现了一个单一的集体智慧统计因素。在伍利等人的文章中。在麦格拉斯的两个初步研究中，研究小组共同完成了麦格拉斯环绕任务(McGrath Task Circumplex)中的不同任务。任务从复杂的四个象限中选择，包括视觉谜题、头脑风暴、做出集体道德判断以及在有限的资源上进行谈判。对这些任务的结果进行因子分析。两项研究都表明支持一般集体智力因素 c，在群体绩效的潜在差异中，最初的特征值占方差的43% (研究2中为44%) ，而下一个因素只占18% (20%)。这符合研究中通常发现的范围，一般个人智力因素 g 通常占个人认知测试成绩差异的40% 至50% 。
Afterwards, a more complex task was solved by each group to determine whether ''c'' factor scores predict performance on tasks beyond the original test. Criterion tasks were playing [[Draughts|checkers (draughts)]] against a standardized computer in the first and a complex architectural design task in the second study. In a [[regression analysis]] using both individual intelligence of group members and ''c'' to predict performance on the criterion tasks, ''c'' had a significant effect, but average and maximum individual intelligence had not. While average (r=0.15, P=0.04) and maximum intelligence (r=0.19, P=0.008) of individual group members were moderately correlated with ''c'', ''c'' was still a much better predictor of the criterion tasks. According to Woolley et al., this supports the existence of a collective intelligence factor ''c,'' because it demonstrates an effect over and beyond group members' individual intelligence and thus that ''c'' is more than just the aggregation of the individual IQs or the influence of the group member with the highest IQ.<ref name=":0" />
Afterwards, a more complex task was solved by each group to determine whether ''c'' factor scores predict performance on tasks beyond the original test. Criterion tasks were playing [[Draughts|checkers (draughts)]] against a standardized computer in the first and a complex architectural design task in the second study. In a [[regression analysis]] using both individual intelligence of group members and ''c'' to predict performance on the criterion tasks, ''c'' had a significant effect, but average and maximum individual intelligence had not. While average (r=0.15, P=0.04) and maximum intelligence (r=0.19, P=0.008) of individual group members were moderately correlated with ''c'', ''c'' was still a much better predictor of the criterion tasks. According to Woolley et al., this supports the existence of a collective intelligence factor ''c,'' because it demonstrates an effect over and beyond group members' individual intelligence and thus that ''c'' is more than just the aggregation of the individual IQs or the influence of the group member with the highest IQ.<ref name=":0" />
Next to predicting a group's performance on more complex criterion tasks as shown in the original experiments, the collective intelligence factor c was also found to predict group performance in diverse tasks in MBA classes lasting over several months. Thereby, highly collectively intelligent groups earned significantly higher scores on their group assignments although their members did not do any better on other individually performed assignments. Moreover, highly collective intelligent teams improved performance over time suggesting that more collectively intelligent teams learn better. This is another potential parallel to individual intelligence where more intelligent people are found to acquire new material quicker.
Next to predicting a group's performance on more complex criterion tasks as shown in the original experiments, the collective intelligence factor c was also found to predict group performance in diverse tasks in MBA classes lasting over several months. Thereby, highly collectively intelligent groups earned significantly higher scores on their group assignments although their members did not do any better on other individually performed assignments. Moreover, highly collective intelligent teams improved performance over time suggesting that more collectively intelligent teams learn better. This is another potential parallel to individual intelligence where more intelligent people are found to acquire new material quicker.
除了预测一个团队在更复杂的标准任务中的表现之外，集体智慧因子 c 也被发现可以预测一个团队在持续数月的 MBA 课程中在不同任务中的表现。因此，高度集体智力的小组在他们的小组作业中获得了显著的高分，尽管他们的成员在其他单独完成的作业中并没有表现得更好。此外，高度集体智慧的团队随着时间的推移提高了性能，这表明更多集体智慧的团队学得更好。这是另一个与个人智力相似的潜在因素，在个人智力中，越聪明的人获取新知识的速度越快。
Individual intelligence can be used to predict plenty of life outcomes from school attainment<ref>{{Cite journal|last=Nathan, B.|date=1997|title=Intelligence, Schooling, and Society|journal=American Psychologist |volume=52 |issue=10 |pages=1046–1050|doi=10.1037/0003-066x.52.10.1046}}</ref> and career success<ref>{{Cite journal|last=Strenze|first=Tarmo|date=2007-09-01|title=Intelligence and socioeconomic success: A meta-analytic review of longitudinal research|journal=Intelligence|volume=35|issue=5|pages=401–426|doi=10.1016/j.intell.2006.09.004}}</ref> to health outcomes<ref name=":14">{{Cite journal |author1=Deary, I.J. |author2=Weiss, A. |author3=Batty, D.G. |name-list-style=amp |date=2010 |title=Intelligence and Personality as Predictors of Illness and Death. How Researchers in Differential Psychology and Chronic Disease Epidemiology Are Collaborating to Understand and Address Health Inequalities |journal=Psychological Science in the Public Interest |volume=11 |issue=2 |pages=53–79 |doi=10.1177/1529100610387081 |pmid=26168413 |hdl=20.500.11820/134d66d9-98db-447a-a8b2-5b019b96a7bb |s2cid=13106622 |url=https://www.pure.ed.ac.uk/ws/files/8895401/intelligence_and_personality_as_predictors.pdf |access-date=9 December 2019 |archive-url=https://web.archive.org/web/20180719215714/https://www.pure.ed.ac.uk/ws/files/8895401/intelligence_and_personality_as_predictors.pdf |archive-date=19 July 2018 |url-status=live }}</ref> and even mortality.<ref name=":14" /> Whether collective intelligence is able to predict other outcomes besides group performance on mental tasks has still to be investigated.
Individual intelligence can be used to predict plenty of life outcomes from school attainment<ref>{{Cite journal|last=Nathan, B.|date=1997|title=Intelligence, Schooling, and Society|journal=American Psychologist |volume=52 |issue=10 |pages=1046–1050|doi=10.1037/0003-066x.52.10.1046}}</ref> and career success<ref>{{Cite journal|last=Strenze|first=Tarmo|date=2007-09-01|title=Intelligence and socioeconomic success: A meta-analytic review of longitudinal research|journal=Intelligence|volume=35|issue=5|pages=401–426|doi=10.1016/j.intell.2006.09.004}}</ref> to health outcomes<ref name=":14">{{Cite journal |author1=Deary, I.J. |author2=Weiss, A. |author3=Batty, D.G. |name-list-style=amp |date=2010 |title=Intelligence and Personality as Predictors of Illness and Death. How Researchers in Differential Psychology and Chronic Disease Epidemiology Are Collaborating to Understand and Address Health Inequalities |journal=Psychological Science in the Public Interest |volume=11 |issue=2 |pages=53–79 |doi=10.1177/1529100610387081 |pmid=26168413 |hdl=20.500.11820/134d66d9-98db-447a-a8b2-5b019b96a7bb |s2cid=13106622 |url=https://www.pure.ed.ac.uk/ws/files/8895401/intelligence_and_personality_as_predictors.pdf |access-date=9 December 2019 |archive-url=https://web.archive.org/web/20180719215714/https://www.pure.ed.ac.uk/ws/files/8895401/intelligence_and_personality_as_predictors.pdf |archive-date=19 July 2018 |url-status=live }}</ref> and even mortality.<ref name=":14" /> Whether collective intelligence is able to predict other outcomes besides group performance on mental tasks has still to be investigated.
Gladwell (2008) showed that the relationship between individual IQ and success works only to a certain point and that additional IQ points over an estimate of IQ 120 do not translate into real life advantages. If a similar border exists for Group-IQ or if advantages are linear and infinite, has still to be explored. Similarly, demand for further research on possible connections of individual and collective intelligence exists within plenty of other potentially transferable logics of individual intelligence, such as, for instance, the development over time or the question of improving intelligence. Whereas it is controversial whether human intelligence can be enhanced via training, a group's collective intelligence potentially offers simpler opportunities for improvement by exchanging team members or implementing structures and technologies. Moreover, social sensitivity was found to be, at least temporarily, improvable by reading literary fiction as well as watching drama movies. In how far such training ultimately improves collective intelligence through social sensitivity remains an open question.
Gladwell (2008) showed that the relationship between individual IQ and success works only to a certain point and that additional IQ points over an estimate of IQ 120 do not translate into real life advantages. If a similar border exists for Group-IQ or if advantages are linear and infinite, has still to be explored. Similarly, demand for further research on possible connections of individual and collective intelligence exists within plenty of other potentially transferable logics of individual intelligence, such as, for instance, the development over time or the question of improving intelligence. Whereas it is controversial whether human intelligence can be enhanced via training, a group's collective intelligence potentially offers simpler opportunities for improvement by exchanging team members or implementing structures and technologies. Moreover, social sensitivity was found to be, at least temporarily, improvable by reading literary fiction as well as watching drama movies. In how far such training ultimately improves collective intelligence through social sensitivity remains an open question.
格拉德威尔(2008年)指出，个人智商和成功之间的关系只在一定程度上起作用，超过估计智商120的额外智商点不会转化为现实生活中的优势。如果类似的边界存在的群体智商或优势是线性和无限的，仍然有待探索。同样，在许多其他可以转移的个体智慧逻辑中，也存在着对个体智慧和集体智慧之间可能存在的联系进一步研究的需求，例如，随着时间的推移而产生的发展或提高智力的问题。虽然人类的智力是否可以通过培训得到提高还存在争议，但是一个群体的集体智力可能通过交换团队成员或实施结构和技术提供更简单的改进机会。此外，社会敏感性被发现，至少是暂时的，可以通过阅读文学小说和观看戏剧电影来改善。在多大程度上这种培训最终通过社会敏感性提高集体智慧仍然是一个悬而未决的问题。
There are further more advanced concepts and factor models attempting to explain individual cognitive ability including the categorization of intelligence in [[fluid and crystallized intelligence]]<ref>{{Cite book|title=Models of intelligence. In R.L. Linn (Ed.), Intelligence: Measurement, theory, and public policy (pp. 29–73).|last=Horn, J.|publisher=University of Illinois Press.|year=1989|location=Urbana, IL}}</ref><ref>{{Cite book|title=Abilities: Their structure, growth, and action.|last=Cattell, R. B.|publisher=New York, NY|year=1971|location=Houghton Mifflin}}</ref> or the [[Three-stratum theory|hierarchical model of intelligence differences]].<ref>{{Cite book|title=Human cognitive abilities: A survey of factor analytic studies.|last=Carroll, J.B.|publisher=Cambridge University Press.|year=1993|isbn=9780521387125|location=Cambridge, England|url=https://books.google.com/books?id=jp9dt4_0_cIC}}</ref><ref>{{Cite journal|last1=Johnson|first1=Wendy|last2=Bouchard Jr.|first2=Thomas J.|date=2005-07-01|title=The structure of human intelligence: It is verbal, perceptual, and image rotation (VPR), not fluid and crystallized|journal=Intelligence|volume=33|issue=4|pages=393–416|doi=10.1016/j.intell.2004.12.002}}</ref> Further supplementing explanations and conceptualizations for the factor structure of the '''Genomes''' of collective intelligence besides a general {{'}}''c'' factor', though, are missing yet.<ref>{{Cite web|url=http://cci.mit.edu/research_developing.html|title=MIT Center for Collective Intelligence|website=cci.mit.edu|access-date=2016-04-27|archive-url=https://web.archive.org/web/20160330091237/http://cci.mit.edu/research_developing.html|archive-date=30 March 2016|url-status=dead}}</ref>
There are further more advanced concepts and factor models attempting to explain individual cognitive ability including the categorization of intelligence in [[fluid and crystallized intelligence]]<ref>{{Cite book|title=Models of intelligence. In R.L. Linn (Ed.), Intelligence: Measurement, theory, and public policy (pp. 29–73).|last=Horn, J.|publisher=University of Illinois Press.|year=1989|location=Urbana, IL}}</ref><ref>{{Cite book|title=Abilities: Their structure, growth, and action.|last=Cattell, R. B.|publisher=New York, NY|year=1971|location=Houghton Mifflin}}</ref> or the [[Three-stratum theory|hierarchical model of intelligence differences]].<ref>{{Cite book|title=Human cognitive abilities: A survey of factor analytic studies.|last=Carroll, J.B.|publisher=Cambridge University Press.|year=1993|isbn=9780521387125|location=Cambridge, England|url=https://books.google.com/books?id=jp9dt4_0_cIC}}</ref><ref>{{Cite journal|last1=Johnson|first1=Wendy|last2=Bouchard Jr.|first2=Thomas J.|date=2005-07-01|title=The structure of human intelligence: It is verbal, perceptual, and image rotation (VPR), not fluid and crystallized|journal=Intelligence|volume=33|issue=4|pages=393–416|doi=10.1016/j.intell.2004.12.002}}</ref> Further supplementing explanations and conceptualizations for the factor structure of the '''Genomes''' of collective intelligence besides a general {{'}}''c'' factor', though, are missing yet.<ref>{{Cite web|url=http://cci.mit.edu/research_developing.html|title=MIT Center for Collective Intelligence|website=cci.mit.edu|access-date=2016-04-27|archive-url=https://web.archive.org/web/20160330091237/http://cci.mit.edu/research_developing.html|archive-date=30 March 2016|url-status=dead}}</ref>
Other scholars explain team performance by aggregating team members' general intelligence to the team level instead of building an own overall collective intelligence measure. Devine and Philips (2001) showed in a meta-analysis that mean cognitive ability predicts team performance in laboratory settings (.37) as well as field settings (.14) – note that this is only a small effect. Suggesting a strong dependence on the relevant tasks, other scholars showed that tasks requiring a high degree of communication and cooperation are found to be most influenced by the team member with the lowest cognitive ability. Tasks in which selecting the best team member is the most successful strategy, are shown to be most influenced by the member with the highest cognitive ability.
Other scholars explain team performance by aggregating team members' general intelligence to the team level instead of building an own overall collective intelligence measure. Devine and Philips (2001) showed in a meta-analysis that mean cognitive ability predicts team performance in laboratory settings (.37) as well as field settings (.14) – note that this is only a small effect. Suggesting a strong dependence on the relevant tasks, other scholars showed that tasks requiring a high degree of communication and cooperation are found to be most influenced by the team member with the lowest cognitive ability. Tasks in which selecting the best team member is the most successful strategy, are shown to be most influenced by the member with the highest cognitive ability.
其他学者通过将团队成员的一般智力汇总到团队水平来解释团队表现，而不是建立一个自己的整体集体智力测量。Devine 和 Philips (2001)在一项荟萃分析中指出，认知能力可以预测实验室环境(0.37)和现场环境(0.14)下的团队表现。注意，这只是一个很小的影响。其他学者的研究表明，对相关任务的依赖性很强，需要高度沟通和合作的任务被认为受认知能力最低的团队成员影响最大。选择最好的团队成员是最成功的策略的任务，被证明受认知能力最高的成员的影响最大。
Since Woolley et al.'s<ref name=":0" /> results do not show any influence of group satisfaction, [[group cohesiveness]], or motivation, they, at least implicitly, challenge these concepts regarding the importance for group performance in general and thus contrast meta-analytically proven evidence concerning the positive effects of [[Group cohesiveness|group cohesion]],<ref>{{Cite journal|last1=Evans|first1=Charles R.|last2=Dion|first2=Kenneth L.|date=1991-05-01|title=Group Cohesion and Performance A Meta-Analysis|journal=Small Group Research|volume=22|issue=2|pages=175–186|doi=10.1177/1046496491222002|s2cid=145344583}}</ref><ref>{{Cite journal|last1=Gully|first1=Stanley M.|last2=Devine|first2=Dennis J.|last3=Whitney|first3=David J.|date=2012-12-01|title=A Meta-Analysis of Cohesion and Performance Effects of Level of Analysis and Task Interdependence|journal=Small Group Research|volume=43|issue=6|pages=702–725|doi=10.1177/1046496412468069|s2cid=220319732}}</ref><ref>{{Cite journal|last1=Beal|first1=Daniel J.|last2=Cohen|first2=Robin R.|last3=Burke|first3=Michael J.|last4=McLendon|first4=Christy L.|title=Cohesion and Performance in Groups: A Meta-Analytic Clarification of Construct Relations.|journal=Journal of Applied Psychology|volume=88|issue=6|pages=989–1004|doi=10.1037/0021-9010.88.6.989|pmid=14640811|date=December 2003}}</ref> motivation<ref>{{Cite journal|last1=O'leary-kelly|first1=Anne M.|last2=Martocchio|first2=Joseph J.|last3=Frink|first3=Dwight D.|date=1994-10-01|title=A Review of the Influence of Group Goals on Group Performance|url=http://amj.aom.org/content/37/5/1285|journal=Academy of Management Journal|volume=37|issue=5|pages=1285–1301|doi=10.2307/256673|jstor=256673}}</ref><ref>{{Cite journal|last1=Kleingeld|first1=Ad|last2=Mierlo|first2=Heleen van|last3=Arends|first3=Lidia|title=The effect of goal setting on group performance: A meta-analysis|journal=Journal of Applied Psychology|volume=96|issue=6|pages=1289–1304|doi=10.1037/a0024315|pmid=21744940|year=2011}}</ref> and satisfaction<ref>{{Cite journal|author1=Duffy, M. K. |author2=Shaw, J. D. |author3= Stark, E. M. |name-list-style=amp |date=2000|title=Performance and satisfaction in conflicted interdependent groups: When and how does selfesteem make a difference?|journal=Academy of Management Journal |volume=43 |issue=4 |pages=772–782|doi=10.2307/1556367|jstor=1556367 }}</ref> on group performance.
Since Woolley et al.'s<ref name=":0" /> results do not show any influence of group satisfaction, [[group cohesiveness]], or motivation, they, at least implicitly, challenge these concepts regarding the importance for group performance in general and thus contrast meta-analytically proven evidence concerning the positive effects of [[Group cohesiveness|group cohesion]],<ref>{{Cite journal|last1=Evans|first1=Charles R.|last2=Dion|first2=Kenneth L.|date=1991-05-01|title=Group Cohesion and Performance A Meta-Analysis|journal=Small Group Research|volume=22|issue=2|pages=175–186|doi=10.1177/1046496491222002|s2cid=145344583}}</ref><ref>{{Cite journal|last1=Gully|first1=Stanley M.|last2=Devine|first2=Dennis J.|last3=Whitney|first3=David J.|date=2012-12-01|title=A Meta-Analysis of Cohesion and Performance Effects of Level of Analysis and Task Interdependence|journal=Small Group Research|volume=43|issue=6|pages=702–725|doi=10.1177/1046496412468069|s2cid=220319732}}</ref><ref>{{Cite journal|last1=Beal|first1=Daniel J.|last2=Cohen|first2=Robin R.|last3=Burke|first3=Michael J.|last4=McLendon|first4=Christy L.|title=Cohesion and Performance in Groups: A Meta-Analytic Clarification of Construct Relations.|journal=Journal of Applied Psychology|volume=88|issue=6|pages=989–1004|doi=10.1037/0021-9010.88.6.989|pmid=14640811|date=December 2003}}</ref> motivation<ref>{{Cite journal|last1=O'leary-kelly|first1=Anne M.|last2=Martocchio|first2=Joseph J.|last3=Frink|first3=Dwight D.|date=1994-10-01|title=A Review of the Influence of Group Goals on Group Performance|url=http://amj.aom.org/content/37/5/1285|journal=Academy of Management Journal|volume=37|issue=5|pages=1285–1301|doi=10.2307/256673|jstor=256673}}</ref><ref>{{Cite journal|last1=Kleingeld|first1=Ad|last2=Mierlo|first2=Heleen van|last3=Arends|first3=Lidia|title=The effect of goal setting on group performance: A meta-analysis|journal=Journal of Applied Psychology|volume=96|issue=6|pages=1289–1304|doi=10.1037/a0024315|pmid=21744940|year=2011}}</ref> and satisfaction<ref>{{Cite journal|author1=Duffy, M. K. |author2=Shaw, J. D. |author3= Stark, E. M. |name-list-style=amp |date=2000|title=Performance and satisfaction in conflicted interdependent groups: When and how does selfesteem make a difference?|journal=Academy of Management Journal |volume=43 |issue=4 |pages=772–782|doi=10.2307/1556367|jstor=1556367 }}</ref> on group performance.
In 2001, Tadeusz (Tad) Szuba from the AGH University in Poland proposed a formal model for the phenomenon of collective intelligence. It is assumed to be an unconscious, random, parallel, and distributed computational process, run in mathematical logic by the social structure.Szuba T., Computational Collective Intelligence, 420 pages, Wiley NY, 2001
In 2001, Tadeusz (Tad) Szuba from the AGH University in Poland proposed a formal model for the phenomenon of collective intelligence. It is assumed to be an unconscious, random, parallel, and distributed computational process, run in mathematical logic by the social structure.Szuba T., Computational Collective Intelligence, 420 pages, Wiley NY, 2001
Ttadeusz Szuba 2001年，来自波兰 AGH 大学的 Tadeusz (Tad) Szuba 提出了一个集体智慧现象的正式模型。它被认为是一个无意识的、随机的、平行的、分布式的计算过程，通过社会结构在数理逻辑中运行。计算集体智能，420页，Wiley NY，2001
In this model, beings and information are modeled as abstract information molecules carrying expressions of mathematical logic.<ref name="szuba" /> They are quasi-randomly displacing due to their interaction with their environments with their intended displacements.<ref name="szuba" /> Their interaction in abstract computational space creates multi-thread inference process which we perceive as collective intelligence.<ref name="szuba" /> Thus, a non-[[Alan Turing|Turing]] model of computation is used. This theory allows simple formal definition of collective intelligence as the property of [[social structure]] and seems to be working well for a wide spectrum of beings, from bacterial colonies up to human social structures. Collective intelligence considered as a specific computational process is providing a straightforward explanation of several social phenomena. For this model of collective intelligence, the formal definition of IQS (IQ Social) was proposed and was defined as "the probability function over the time and domain of N-element inferences which are reflecting inference activity of the social structure".<ref name="szuba" /> While IQS seems to be computationally hard, modeling of social structure in terms of a computational process as described above gives a chance for approximation.<ref name="szuba" /> Prospective applications are optimization of companies through the maximization of their IQS, and the analysis of drug resistance against collective intelligence of bacterial colonies.<ref name="szuba"/>
In this model, beings and information are modeled as abstract information molecules carrying expressions of mathematical logic.<ref name="szuba" /> They are quasi-randomly displacing due to their interaction with their environments with their intended displacements.<ref name="szuba" /> Their interaction in abstract computational space creates multi-thread inference process which we perceive as collective intelligence.<ref name="szuba" /> Thus, a non-[[Alan Turing|Turing]] model of computation is used. This theory allows simple formal definition of collective intelligence as the property of [[social structure]] and seems to be working well for a wide spectrum of beings, from bacterial colonies up to human social structures. Collective intelligence considered as a specific computational process is providing a straightforward explanation of several social phenomena. For this model of collective intelligence, the formal definition of IQS (IQ Social) was proposed and was defined as "the probability function over the time and domain of N-element inferences which are reflecting inference activity of the social structure".<ref name="szuba" /> While IQS seems to be computationally hard, modeling of social structure in terms of a computational process as described above gives a chance for approximation.<ref name="szuba" /> Prospective applications are optimization of companies through the maximization of their IQS, and the analysis of drug resistance against collective intelligence of bacterial colonies.<ref name="szuba"/>
One measure sometimes applied, especially by more artificial intelligence focused theorists, is a "collective intelligence quotient" (or "cooperation quotient") – which can be normalized from the "individual" intelligence quotient (IQ) – thus making it possible to determine the marginal intelligence added by each new individual participating in the collective action, thus using metrics to avoid the hazards of group think and stupidity.
One measure sometimes applied, especially by more artificial intelligence focused theorists, is a "collective intelligence quotient" (or "cooperation quotient") – which can be normalized from the "individual" intelligence quotient (IQ) – thus making it possible to determine the marginal intelligence added by each new individual participating in the collective action, thus using metrics to avoid the hazards of group think and stupidity.
有时候，特别是那些更注重人工智能的理论家们，会采用一种“集体智商”(或者“合作商数”)——可以从“个人”智商(IQ)中规范化——这样就可以确定每个新加入集体行动的个体所增加的边际智力，从而使用度量标准来避免集体思维和愚蠢的危害。
== Applications ==
== Applications ==
== Applications ==
== Applications ==
= = 应用程序 = =
= = 应用程序 = =
There have been many recent applications of collective intelligence, including in fields such as crowd-sourcing, citizen science and prediction markets. The Nesta Centre for Collective Intelligence Design <ref>https://www.nesta.org.uk/project/centre-collective-intelligence-design/</ref> was launched in 2018 and has produced many surveys of applications as well as funding experiments. In 2020 the UNDP Accelerator Labs <ref>https://acceleratorlabs.undp.org/</ref> began using collective intelligence methods in their work to accelerate innovation for the [[Sustainable Development Goals]].
There have been many recent applications of collective intelligence, including in fields such as crowd-sourcing, citizen science and prediction markets. The Nesta Centre for Collective Intelligence Design <ref>https://www.nesta.org.uk/project/centre-collective-intelligence-design/</ref> was launched in 2018 and has produced many surveys of applications as well as funding experiments. In 2020 the UNDP Accelerator Labs <ref>https://acceleratorlabs.undp.org/</ref> began using collective intelligence methods in their work to accelerate innovation for the [[Sustainable Development Goals]].
Here, the goal is to get an estimate (in a single value) of something. For example, estimating the weight of an object, or the release date of a product or probability of success of a project etc. as seen in prediction markets like Intrade, HSX or InklingMarkets and also in several implementations of crowdsourced estimation of a numeric outcome such as the Delphi method. Essentially, we try to get the average value of the estimates provided by the members in the crowd.
Here, the goal is to get an estimate (in a single value) of something. For example, estimating the weight of an object, or the release date of a product or probability of success of a project etc. as seen in prediction markets like Intrade, HSX or InklingMarkets and also in several implementations of crowdsourced estimation of a numeric outcome such as the Delphi method. Essentially, we try to get the average value of the estimates provided by the members in the crowd.
在这里，目标是得到一个估计(在一个单一的价值)的东西。例如，估计一个对象的重量，或者一个产品的发布日期，或者一个项目的成功概率等等。在 Intrade、 HSX 或 InklingMarkets 等预测市场，以及诸如德尔福(Delphi)方法等数字结果的众包估计实现中都可以看到这种情况。本质上，我们试图得到人群中成员提供的估计值的平均值。
=== Opinion aggregation ===
=== Opinion aggregation ===
In this situation, opinions are gathered from the crowd regarding an idea, issue or product. For example, trying to get a rating (on some scale) of a product sold online (such as Amazon's star rating system). Here, the emphasis is to collect and simply aggregate the ratings provided by customers/users.
In this situation, opinions are gathered from the crowd regarding an idea, issue or product. For example, trying to get a rating (on some scale) of a product sold online (such as Amazon's star rating system). Here, the emphasis is to collect and simply aggregate the ratings provided by customers/users.
在这种情况下，从人群中收集关于一个想法、问题或产品的意见。例如，试图获得在线销售产品的评级(在一定规模上)(如亚马逊的星级评级系统)。这里的重点是收集并简单地汇总客户/用户提供的评级。
=== Idea Collection ===
=== Idea Collection ===
Political parties mobilize large numbers of people to form policy, select candidates and finance and run election campaigns. Knowledge focusing through various voting methods allows perspectives to converge through the assumption that uninformed voting is to some degree random and can be filtered from the decision process leaving only a residue of informed consensus. Critics point out that often bad ideas, misunderstandings, and misconceptions are widely held, and that structuring of the decision process must favor experts who are presumably less prone to random or misinformed voting in a given context.
Political parties mobilize large numbers of people to form policy, select candidates and finance and run election campaigns. Knowledge focusing through various voting methods allows perspectives to converge through the assumption that uninformed voting is to some degree random and can be filtered from the decision process leaving only a residue of informed consensus. Critics point out that often bad ideas, misunderstandings, and misconceptions are widely held, and that structuring of the decision process must favor experts who are presumably less prone to random or misinformed voting in a given context.
美国2016年选举中使用的投票方法政党动员大量民众制定政策、选择候选人、资助和开展竞选活动。通过各种投票方法聚焦的知识可以通过假设无知投票在某种程度上是随机的，并且可以从决策过程中过滤掉，只留下知情共识的残留，从而使观点趋于一致。批评人士指出，经常存在错误的想法、误解和误解，决策过程的结构必须有利于专家，因为他们可能不太容易在特定情况下进行随机或错误信息的投票。
Companies such as Affinnova (acquired by Nielsen), [[Google]], [[InnoCentive]], [[Marketocracy]], and [[Threadless]]<ref name=":17">{{Cite journal|last=Bonabeau|first=E|year=2009|title=The power of collective intelligence|journal=MIT Sloan Management Review|volume=50|pages=45–52|id={{ProQuest|224962498}}}}</ref> have successfully employed the concept of collective intelligence in bringing about the next generation of technological changes through their research and development (R&D), customer service, and knowledge management.<ref name=":17" /><ref>{{Cite report|last1=Malone|first1=Thomas W.|last2=Laubacher|first2=Robert|last3=Dellarocas|first3=Chrysanthos|date=2009-02-03|title=Harnessing Crowds: Mapping the Genome of Collective Intelligence|ssrn=1381502|location=Rochester, NY|publisher=Social Science Research Network|id=MIT Sloan Research Paper No. 4732-09}}</ref> An example of such application is Google's Project Aristotle in 2012, where the effect of collective intelligence on team makeup was examined in hundreds of the company's R&D teams.<ref>{{Cite news|url=https://www.nytimes.com/2016/02/28/magazine/what-google-learned-from-its-quest-to-build-the-perfect-team.html|title=What Google Learned From Its Quest to Build the Perfect Team|last=Duhigg|first=Charles|date=2016-02-25|newspaper=The New York Times|access-date=2016-12-11|archive-url=https://web.archive.org/web/20170223084955/https://www.nytimes.com/2016/02/28/magazine/what-google-learned-from-its-quest-to-build-the-perfect-team.html|archive-date=23 February 2017|url-status=live}}</ref>
Companies such as Affinnova (acquired by Nielsen), [[Google]], [[InnoCentive]], [[Marketocracy]], and [[Threadless]]<ref name=":17">{{Cite journal|last=Bonabeau|first=E|year=2009|title=The power of collective intelligence|journal=MIT Sloan Management Review|volume=50|pages=45–52|id={{ProQuest|224962498}}}}</ref> have successfully employed the concept of collective intelligence in bringing about the next generation of technological changes through their research and development (R&D), customer service, and knowledge management.<ref name=":17" /><ref>{{Cite report|last1=Malone|first1=Thomas W.|last2=Laubacher|first2=Robert|last3=Dellarocas|first3=Chrysanthos|date=2009-02-03|title=Harnessing Crowds: Mapping the Genome of Collective Intelligence|ssrn=1381502|location=Rochester, NY|publisher=Social Science Research Network|id=MIT Sloan Research Paper No. 4732-09}}</ref> An example of such application is Google's Project Aristotle in 2012, where the effect of collective intelligence on team makeup was examined in hundreds of the company's R&D teams.<ref>{{Cite news|url=https://www.nytimes.com/2016/02/28/magazine/what-google-learned-from-its-quest-to-build-the-perfect-team.html|title=What Google Learned From Its Quest to Build the Perfect Team|last=Duhigg|first=Charles|date=2016-02-25|newspaper=The New York Times|access-date=2016-12-11|archive-url=https://web.archive.org/web/20170223084955/https://www.nytimes.com/2016/02/28/magazine/what-google-learned-from-its-quest-to-build-the-perfect-team.html|archive-date=23 February 2017|url-status=live}}</ref>
In 2012, the Global Futures Collective Intelligence System (GFIS) was created by The Millennium Project, which epitomizes collective intelligence as the synergistic intersection among data/information/knowledge, software/hardware, and expertise/insights that has a recursive learning process for better decision-making than the individual players alone.
In 2012, the Global Futures Collective Intelligence System (GFIS) was created by The Millennium Project, which epitomizes collective intelligence as the synergistic intersection among data/information/knowledge, software/hardware, and expertise/insights that has a recursive learning process for better decision-making than the individual players alone.
在千年项目中应用集体智慧2012年，全球未来集体智慧系统(GFIS)由千年项目创建，它集中体现了集体智慧，即数据/信息/知识、软件/硬件和专长/见解之间的协同交汇，具有一个递归的学习过程，比单个行为者更好地做出决策。
[[New media]] are often associated with the promotion and enhancement of collective intelligence. The ability of new media to easily store and retrieve information, predominantly through databases and the Internet, allows for it to be shared without difficulty. Thus, through interaction with new media, knowledge easily passes between sources {{Harv|Flew|2008}} resulting in a form of collective intelligence. The use of interactive new media, particularly the internet, promotes online interaction and this distribution of knowledge between users.
[[New media]] are often associated with the promotion and enhancement of collective intelligence. The ability of new media to easily store and retrieve information, predominantly through databases and the Internet, allows for it to be shared without difficulty. Thus, through interaction with new media, knowledge easily passes between sources {{Harv|Flew|2008}} resulting in a form of collective intelligence. The use of interactive new media, particularly the internet, promotes online interaction and this distribution of knowledge between users.
Research performed by Tapscott and Williams has provided a few examples of the benefits of collective intelligence to business:
Research performed by Tapscott and Williams has provided a few examples of the benefits of collective intelligence to business:
泰普斯科特和威廉姆斯的研究提供了一些集体智慧对商业的好处的例子:
;Talent utilization
;Talent utilization
Cultural theorist and online community developer, John Banks considered the contribution of online fan communities in the creation of the Trainz product. He argued that its commercial success was fundamentally dependent upon "the formation and growth of an active and vibrant online fan community that would both actively promote the product and create content- extensions and additions to the game software".John A.L. Banks. Negotiating Participatory Culture in the New Media Environment: Auran and the Trainz Online Community – An (Im)possible Relation, The University of Queensland. School of English, Media Studies and Art History. MelbourneDAC2003
Cultural theorist and online community developer, John Banks considered the contribution of online fan communities in the creation of the Trainz product. He argued that its commercial success was fundamentally dependent upon "the formation and growth of an active and vibrant online fan community that would both actively promote the product and create content- extensions and additions to the game software".John A.L. Banks. Negotiating Participatory Culture in the New Media Environment: Auran and the Trainz Online Community – An (Im)possible Relation, The University of Queensland. School of English, Media Studies and Art History. MelbourneDAC2003
作为文化理论家和在线社区开发者，约翰 · 班克斯考虑了在线粉丝社区对 Trainz 产品创造的贡献。他认为，其商业成功从根本上取决于“一个活跃而充满活力的在线粉丝社区的形成和发展，这个社区将积极推广该产品，并为游戏软件提供内容扩展和附加功能”。约翰 · a · l。银行。在新媒体环境下谈判参与式文化: Auran 和 Trainz 在线社区-可能的关系，昆士兰大学。英语、媒体研究与艺术史学院。墨尔本2003
The increase in user created content and interactivity gives rise to issues of control over the game itself and ownership of the player-created content. This gives rise to fundamental legal issues, highlighted by Lessig<ref>L, Lessig,(2006)Code Version 2.0 (2nd ed.). New York: Basic Books.</ref> and Bray and Konsynski,<ref>Bray, DA & Konsynski, BR, 2007, ''Virtual Worlds, Virtual Economies, Virtual Institutions'', viewed 10 October 2008, p. 1-27 <http://ssrn.com/abstract=962501></ref> such as [[intellectual property]] and property ownership rights.
The increase in user created content and interactivity gives rise to issues of control over the game itself and ownership of the player-created content. This gives rise to fundamental legal issues, highlighted by Lessig<ref>L, Lessig,(2006)Code Version 2.0 (2nd ed.). New York: Basic Books.</ref> and Bray and Konsynski,<ref>Bray, DA & Konsynski, BR, 2007, ''Virtual Worlds, Virtual Economies, Virtual Institutions'', viewed 10 October 2008, p. 1-27 <http://ssrn.com/abstract=962501></ref> such as [[intellectual property]] and property ownership rights.
Co-operation helps to solve most important and most interesting multi-science problems. In his book, James Surowiecki mentioned that most scientists think that benefits of co-operation have much more value when compared to potential costs. Co-operation works also because at best it guarantees number of different viewpoints. Because of the possibilities of technology global co-operation is nowadays much easier and productive than before. It is clear that, when co-operation goes from university level to global it has significant benefits.
Co-operation helps to solve most important and most interesting multi-science problems. In his book, James Surowiecki mentioned that most scientists think that benefits of co-operation have much more value when compared to potential costs. Co-operation works also because at best it guarantees number of different viewpoints. Because of the possibilities of technology global co-operation is nowadays much easier and productive than before. It is clear that, when co-operation goes from university level to global it has significant benefits.
合作有助于解决最重要和最有趣的多学科问题。詹姆斯•索罗维茨基(James Surowiecki)在他的书中提到，大多数科学家认为，与潜在成本相比，合作的好处更有价值。合作之所以奏效，还因为它充其量只能保证不同观点的数量。由于技术的可能性，全球合作现在比以前更加容易和富有成效。很明显，当合作从大学层面进入全球层面时，它会带来显著的好处。
For example, why do scientists co-operate? Science has become more and more isolated and each science field has spread even more and it is impossible for one person to be aware of all developments. This is true especially in experimental research where highly advanced equipment requires special skills. With co-operation scientists can use information from different fields and use it effectively instead of gathering all the information just by reading by themselves."<ref name="Surowiecki">Surowiecki, J., 2007 'The Wisdom of crowds. Why the Many Are Smarter Than the Few'</ref>{{full citation needed|date=November 2017}}
For example, why do scientists co-operate? Science has become more and more isolated and each science field has spread even more and it is impossible for one person to be aware of all developments. This is true especially in experimental research where highly advanced equipment requires special skills. With co-operation scientists can use information from different fields and use it effectively instead of gathering all the information just by reading by themselves."<ref name="Surowiecki">Surowiecki, J., 2007 'The Wisdom of crowds. Why the Many Are Smarter Than the Few'</ref>{{full citation needed|date=November 2017}}
Military, trade unions, and corporations satisfy some definitions of CI – the most rigorous definition would require a capacity to respond to very arbitrary conditions without orders or guidance from "law" or "customers" to constrain actions. Online advertising companies are using collective intelligence to bypass traditional marketing and creative agencies.Lee, Sang M., et al. "Success factors of platform leadership in web 2.0 service business." Service Business 4.2 (2010): 89–103.
Military, trade unions, and corporations satisfy some definitions of CI – the most rigorous definition would require a capacity to respond to very arbitrary conditions without orders or guidance from "law" or "customers" to constrain actions. Online advertising companies are using collective intelligence to bypass traditional marketing and creative agencies.Lee, Sang M., et al. "Success factors of platform leadership in web 2.0 service business." Service Business 4.2 (2010): 89–103.
军事、工会和公司满足 CI 的某些定义——最严格的定义要求有能力对非常武断的条件作出反应，而不需要”法律”或”客户”的命令或指导来约束行动。在线广告公司正在利用集体智慧来绕过传统的市场营销和创意机构。“ web2.0服务业平台领导力的成功因素。”服务业4.2(2010) : 89-103。
The [https://web.archive.org/web/20151103044224/http://unu.ai/ UNU] open platform for "human swarming" (or "social swarming") establishes real-time closed-loop systems around groups of networked users molded after biological swarms, enabling human participants to behave as a unified collective intelligence.<ref name="Human Swarms">{{cite web|url=http://news.discovery.com/human/life/swarms-of-humans-power-a-i-platform-150603.htm|title=Swarms of Humans Power A.I. Platform|last=DNews|date=3 June 2015|access-date=21 June 2015|archive-url=https://web.archive.org/web/20150621165834/http://news.discovery.com/human/life/swarms-of-humans-power-a-i-platform-150603.htm|archive-date=21 June 2015|url-status=live}}</ref><ref>{{cite book|url=https://mitpress.mit.edu/sites/default/files/titles/content/ecal2015/ch117.html|first1=Louis B.|title=07/20/2015-07/24/2015|last1=Rosenberg|first2=Unanimous|last2=A.I.|first3=San|last3=Francisco|last4=California|last5=USA|date=1 January 2016|volume=13|pages=658–659|doi=10.7551/978-0-262-33027-5-ch117|isbn=9780262330275|access-date=12 October 2015|archive-url=https://web.archive.org/web/20151027132802/https://mitpress.mit.edu/sites/default/files/titles/content/ecal2015/ch117.html|archive-date=27 October 2015|url-status=dead}}</ref> When connected to UNU, groups of distributed users collectively answer questions and make predictions in real-time.<ref>Rosenberg, L.B., "Human swarming, a real-time method for parallel distributed intelligence," in Swarm/Human Blended Intelligence Workshop (SHBI), 2015, vol., no., pp.1–7, 28–29 Sept. 2015 doi: [https://dx.doi.org/10.1109/SHBI.2015.7321685 10.1109/SHBI.2015.7321685]</ref> Early testing shows that human swarms can out-predict individuals.<ref name="Human Swarms"/> In 2016, an UNU swarm was challenged by a reporter to predict the winners of the Kentucky Derby, and successfully picked the first four horses, in order, beating 540 to 1 odds.<ref>{{cite web|url=http://www.newsweek.com/artificial-intelligence-turns-20-11000-kentucky-derby-bet-457783|title=Artificial intelligence turns $20 into $11,000 in Kentucky Derby bet|date=10 May 2016|access-date=4 June 2016|archive-url=https://web.archive.org/web/20160604063846/http://www.newsweek.com/artificial-intelligence-turns-20-11000-kentucky-derby-bet-457783|archive-date=4 June 2016|url-status=live}}</ref><ref>{{cite web|url=https://www.washingtonpost.com/news/the-intersect/wp/2016/06/02/what-happened-when-an-ai-hive-mind-answered-reddits-burning-politics-questions/|title=What happened when an A.I. hive mind answered Reddit's burning politics questions|first=Abby|last=Ohlheiser|date=2 June 2016|via=washingtonpost.com|access-date=4 June 2016|archive-url=https://web.archive.org/web/20160604022928/https://www.washingtonpost.com/news/the-intersect/wp/2016/06/02/what-happened-when-an-ai-hive-mind-answered-reddits-burning-politics-questions/|archive-date=4 June 2016|url-status=live}}</ref>
The [https://web.archive.org/web/20151103044224/http://unu.ai/ UNU] open platform for "human swarming" (or "social swarming") establishes real-time closed-loop systems around groups of networked users molded after biological swarms, enabling human participants to behave as a unified collective intelligence.<ref name="Human Swarms">{{cite web|url=http://news.discovery.com/human/life/swarms-of-humans-power-a-i-platform-150603.htm|title=Swarms of Humans Power A.I. Platform|last=DNews|date=3 June 2015|access-date=21 June 2015|archive-url=https://web.archive.org/web/20150621165834/http://news.discovery.com/human/life/swarms-of-humans-power-a-i-platform-150603.htm|archive-date=21 June 2015|url-status=live}}</ref><ref>{{cite book|url=https://mitpress.mit.edu/sites/default/files/titles/content/ecal2015/ch117.html|first1=Louis B.|title=07/20/2015-07/24/2015|last1=Rosenberg|first2=Unanimous|last2=A.I.|first3=San|last3=Francisco|last4=California|last5=USA|date=1 January 2016|volume=13|pages=658–659|doi=10.7551/978-0-262-33027-5-ch117|isbn=9780262330275|access-date=12 October 2015|archive-url=https://web.archive.org/web/20151027132802/https://mitpress.mit.edu/sites/default/files/titles/content/ecal2015/ch117.html|archive-date=27 October 2015|url-status=dead}}</ref> When connected to UNU, groups of distributed users collectively answer questions and make predictions in real-time.<ref>Rosenberg, L.B., "Human swarming, a real-time method for parallel distributed intelligence," in Swarm/Human Blended Intelligence Workshop (SHBI), 2015, vol., no., pp.1–7, 28–29 Sept. 2015 doi: [https://dx.doi.org/10.1109/SHBI.2015.7321685 10.1109/SHBI.2015.7321685]</ref> Early testing shows that human swarms can out-predict individuals.<ref name="Human Swarms"/> In 2016, an UNU swarm was challenged by a reporter to predict the winners of the Kentucky Derby, and successfully picked the first four horses, in order, beating 540 to 1 odds.<ref>{{cite web|url=http://www.newsweek.com/artificial-intelligence-turns-20-11000-kentucky-derby-bet-457783|title=Artificial intelligence turns $20 into $11,000 in Kentucky Derby bet|date=10 May 2016|access-date=4 June 2016|archive-url=https://web.archive.org/web/20160604063846/http://www.newsweek.com/artificial-intelligence-turns-20-11000-kentucky-derby-bet-457783|archive-date=4 June 2016|url-status=live}}</ref><ref>{{cite web|url=https://www.washingtonpost.com/news/the-intersect/wp/2016/06/02/what-happened-when-an-ai-hive-mind-answered-reddits-burning-politics-questions/|title=What happened when an A.I. hive mind answered Reddit's burning politics questions|first=Abby|last=Ohlheiser|date=2 June 2016|via=washingtonpost.com|access-date=4 June 2016|archive-url=https://web.archive.org/web/20160604022928/https://www.washingtonpost.com/news/the-intersect/wp/2016/06/02/what-happened-when-an-ai-hive-mind-answered-reddits-burning-politics-questions/|archive-date=4 June 2016|url-status=live}}</ref>
Improvisational actors also experience a type of collective intelligence which they term "group mind", as theatrical improvisation relies on mutual cooperation and agreement, leading to the unity of "group mind".
Improvisational actors also experience a type of collective intelligence which they term "group mind", as theatrical improvisation relies on mutual cooperation and agreement, leading to the unity of "group mind".
课后即兴表演的演员们学到了一堂关于即兴表演和生活的重要课程，即兴表演的演员们也体验到一种他们称之为“群体思维”的集体智慧，因为戏剧性的即兴表演依赖于相互合作和协议，从而导致“群体思维”的统一。
Growth of the Internet and mobile telecom has also produced "swarming" or "rendezvous" events that enable meetings or even dates on demand.<ref name="Wolpert arXiv:cs/9905004"/> The full impact has yet to be felt but the [[anti-globalization movement]], for example, relies heavily on e-mail, cell phones, pagers, SMS and other means of organizing.<ref>{{Cite book|url=https://books.google.com/books?id=vskz1poDuvoC&q=anti+globalization+collective+intelligence&pg=PR7|title=Globalization / Anti-Globalization: Beyond the Great Divide|last1=Held|first1=David|last2=McGrew|first2=Anthony|date=2007-11-19|publisher=Polity|isbn=9780745639116}}</ref> The [[Indymedia]] organization does this in a more journalistic way.<ref name=":19">{{Cite web|url=http://www.indymedia.org.uk/en/2001/09/11129.html|title='Anti-Globals' Use Internet As Collective Intelligence – UK Indymedia|website=www.indymedia.org.uk|access-date=2016-12-11|archive-url=https://web.archive.org/web/20161220122251/http://www.indymedia.org.uk/en/2001/09/11129.html|archive-date=20 December 2016|url-status=live}}</ref> Such resources could combine into a form of collective intelligence accountable only to the current participants yet with some strong moral or linguistic guidance from generations of contributors – or even take on a more obviously democratic form to advance shared goal.<ref name=":19" />
Growth of the Internet and mobile telecom has also produced "swarming" or "rendezvous" events that enable meetings or even dates on demand.<ref name="Wolpert arXiv:cs/9905004"/> The full impact has yet to be felt but the [[anti-globalization movement]], for example, relies heavily on e-mail, cell phones, pagers, SMS and other means of organizing.<ref>{{Cite book|url=https://books.google.com/books?id=vskz1poDuvoC&q=anti+globalization+collective+intelligence&pg=PR7|title=Globalization / Anti-Globalization: Beyond the Great Divide|last1=Held|first1=David|last2=McGrew|first2=Anthony|date=2007-11-19|publisher=Polity|isbn=9780745639116}}</ref> The [[Indymedia]] organization does this in a more journalistic way.<ref name=":19">{{Cite web|url=http://www.indymedia.org.uk/en/2001/09/11129.html|title='Anti-Globals' Use Internet As Collective Intelligence – UK Indymedia|website=www.indymedia.org.uk|access-date=2016-12-11|archive-url=https://web.archive.org/web/20161220122251/http://www.indymedia.org.uk/en/2001/09/11129.html|archive-date=20 December 2016|url-status=live}}</ref> Such resources could combine into a form of collective intelligence accountable only to the current participants yet with some strong moral or linguistic guidance from generations of contributors – or even take on a more obviously democratic form to advance shared goal.<ref name=":19" />
Collective actions or tasks require different amounts of coordination depending on the complexity of the task. Tasks vary from being highly independent simple tasks that require very little coordination to complex interdependent tasks that are built by many individuals and require a lot of coordination. In the article written by Kittur, Lee and Kraut the writers introduce a problem in cooperation: "When tasks require high coordination because the work is highly interdependent, having more contributors can increase process losses, reducing the effectiveness of the group below what individual members could optimally accomplish". Having a team too large the overall effectiveness may suffer even when the extra contributors increase the resources. In the end the overall costs from coordination might overwhelm other costs.Kittur, A., Lee, B. and Kraut, R. E. (2009) 'Coordination in collective intelligence: The role of team structure and task interdependence', Conference on Human Factors in Computing Systems - Proceedings, pp. 1495–1504.
Collective actions or tasks require different amounts of coordination depending on the complexity of the task. Tasks vary from being highly independent simple tasks that require very little coordination to complex interdependent tasks that are built by many individuals and require a lot of coordination. In the article written by Kittur, Lee and Kraut the writers introduce a problem in cooperation: "When tasks require high coordination because the work is highly interdependent, having more contributors can increase process losses, reducing the effectiveness of the group below what individual members could optimally accomplish". Having a team too large the overall effectiveness may suffer even when the extra contributors increase the resources. In the end the overall costs from coordination might overwhelm other costs.Kittur, A., Lee, B. and Kraut, R. E. (2009) 'Coordination in collective intelligence: The role of team structure and task interdependence', Conference on Human Factors in Computing Systems - Proceedings, pp. 1495–1504.
集体行动或任务需要不同程度的协调，这取决于任务的复杂程度。任务从高度独立的简单任务到复杂的相互依赖的任务，这些任务是由许多个人构建的，需要大量的协调。在 Kittur、 Lee 和 Kraut 撰写的文章中，作者介绍了合作中的一个问题:”当任务需要高度协调，因为工作是高度相互依赖的，有更多的贡献者可能会增加流程损失，降低团队的效率，低于个人成员可以最佳完成的水平”。即使额外的捐助者增加了资源，如果团队过于庞大，整体效率可能会受到影响。最后，协调的总成本可能会超过其他成本。“集体智慧中的协调: 团队结构和任务相互依赖的作用”，计算机系统中的人为因素会议论文集，页。1495–1504.
Group collective intelligence is a property that emerges through coordination from both bottom-up and top-down processes. In a bottom-up process the different characteristics of each member are involved in contributing and enhancing coordination. Top-down processes are more strict and fixed with norms, group structures and routines that in their own way enhance the group's collective work.<ref>[18] Woolley, A. W., Aggarwal, I. and Malone, T. W. (2015) 'Collective Intelligence and Group Performance', Current Directions in Psychological Science, 24(6), pp. 420–424.</ref>
Group collective intelligence is a property that emerges through coordination from both bottom-up and top-down processes. In a bottom-up process the different characteristics of each member are involved in contributing and enhancing coordination. Top-down processes are more strict and fixed with norms, group structures and routines that in their own way enhance the group's collective work.<ref>[18] Woolley, A. W., Aggarwal, I. and Malone, T. W. (2015) 'Collective Intelligence and Group Performance', Current Directions in Psychological Science, 24(6), pp. 420–424.</ref>
===A tool for combating self-preservation===
===A tool for combating self-preservation===
= = = 替代观点 = = = = 一个打击自我保存的工具 = = =
= = = 打击自我保存的工具 = =
Tom Atlee reflects that, although humans have an innate ability to gather and analyze data, they are affected by culture, education and social institutions.<ref>{{Cite book|url=https://books.google.com/books?id=YV4dCwAAQBAJ&pg=PA140|title=In Search of The Black Seed|last=Abdul-Karim|first=Kashif|date=2015-11-23|publisher=Lulu.com|isbn=9781329694897|page=140}}{{self-published source|date=February 2020}}</ref>{{self-published inline|date=February 2020}} A single person tends to make decisions motivated by self-preservation. Therefore, without collective intelligence, humans may drive themselves into extinction based on their selfish needs.<ref name=":21">Atlee, T. (2008). [http://www.communicationagents.com/tom_atlee/2008/05/15/reflections_on_the_evolution_of_choice_and_collective_intelligence.htm Reflections on the evolution of choice and collective intelligence] {{Webarchive|url=https://web.archive.org/web/20080522033150/http://www.communicationagents.com/tom_atlee/2008/05/15/reflections_on_the_evolution_of_choice_and_collective_intelligence.htm |date=22 May 2008 }}, Retrieved 26 August 2008</ref>
Tom Atlee reflects that, although humans have an innate ability to gather and analyze data, they are affected by culture, education and social institutions.<ref>{{Cite book|url=https://books.google.com/books?id=YV4dCwAAQBAJ&pg=PA140|title=In Search of The Black Seed|last=Abdul-Karim|first=Kashif|date=2015-11-23|publisher=Lulu.com|isbn=9781329694897|page=140}}{{self-published source|date=February 2020}}</ref>{{self-published inline|date=February 2020}} A single person tends to make decisions motivated by self-preservation. Therefore, without collective intelligence, humans may drive themselves into extinction based on their selfish needs.<ref name=":21">Atlee, T. (2008). [http://www.communicationagents.com/tom_atlee/2008/05/15/reflections_on_the_evolution_of_choice_and_collective_intelligence.htm Reflections on the evolution of choice and collective intelligence] {{Webarchive|url=https://web.archive.org/web/20080522033150/http://www.communicationagents.com/tom_atlee/2008/05/15/reflections_on_the_evolution_of_choice_and_collective_intelligence.htm |date=22 May 2008 }}, Retrieved 26 August 2008</ref>
Phillip Brown and Hugh Lauder quotes Bowles and Gintis (1976) that in order to truly define collective intelligence, it is crucial to separate 'intelligence' from IQism. They go on to argue that intelligence is an achievement and can only be developed if allowed to. For example, earlier on, groups from the lower levels of society are severely restricted from aggregating and pooling their intelligence. This is because the elites fear that the collective intelligence would convince the people to rebel. If there is no such capacity and relations, there would be no infrastructure on which collective intelligence is built. This reflects how powerful collective intelligence can be if left to develop.
Phillip Brown and Hugh Lauder quotes Bowles and Gintis (1976) that in order to truly define collective intelligence, it is crucial to separate 'intelligence' from IQism. They go on to argue that intelligence is an achievement and can only be developed if allowed to. For example, earlier on, groups from the lower levels of society are severely restricted from aggregating and pooling their intelligence. This is because the elites fear that the collective intelligence would convince the people to rebel. If there is no such capacity and relations, there would be no infrastructure on which collective intelligence is built. This reflects how powerful collective intelligence can be if left to develop.
菲利普 · 布朗和休 · 兰黛引用鲍尔斯和金蒂斯(1976)的话说，为了真正定义集体智慧，将“智慧”与智商分开是至关重要的。他们继续争辩说，智力是一种成就，只有在被允许的情况下才能得到发展。例如，早些时候，来自社会底层的群体在聚集和汇集他们的智力方面受到严格限制。这是因为精英们害怕集体智慧会说服人民起来反抗。如果没有这种能力和关系，就不会有建立集体智慧的基础设施。这反映了如果任其发展，集体智慧是多么强大。
===Artificial intelligence views===
===Artificial intelligence views===
Skeptics, especially those critical of artificial intelligence and more inclined to believe that risk of bodily harm and bodily action are the basis of all unity between people, are more likely to emphasize the capacity of a group to take action and withstand harm as one fluid mass mobilization, shrugging off harms the way a body shrugs off the loss of a few cells. This train of thought is most obvious in the anti-globalization movement and characterized by the works of John Zerzan, Carol Moore, and Starhawk, who typically shun academics. These theorists are more likely to refer to ecological and collective wisdom and to the role of consensus process in making ontological distinctions than to any form of "intelligence" as such, which they often argue does not exist, or is mere "cleverness".
Skeptics, especially those critical of artificial intelligence and more inclined to believe that risk of bodily harm and bodily action are the basis of all unity between people, are more likely to emphasize the capacity of a group to take action and withstand harm as one fluid mass mobilization, shrugging off harms the way a body shrugs off the loss of a few cells. This train of thought is most obvious in the anti-globalization movement and characterized by the works of John Zerzan, Carol Moore, and Starhawk, who typically shun academics. These theorists are more likely to refer to ecological and collective wisdom and to the role of consensus process in making ontological distinctions than to any form of "intelligence" as such, which they often argue does not exist, or is mere "cleverness".
怀疑论者，尤其是那些批评人工智能的人，更倾向于相信身体伤害和身体行为的风险是人与人之间所有团结的基础，更可能强调一个群体采取行动和承受伤害的能力，就像一个体液政治动员一样，无视身体对少数细胞损失的危害。这种思路在反全球化运动和拥有属性的 John Zerzan，Carol Moore 和 Starhawk 的著作中最为明显，他们通常回避学者。这些理论家更可能提到生态和集体智慧以及协商一致进程在作出本体论区分方面的作用，而不是任何形式的”智慧”本身，因为他们常常认为这种智慧并不存在，或者仅仅是”聪明”。
Harsh critics of artificial intelligence on ethical grounds are likely to promote collective wisdom-building methods, such as the [[new tribalists]] and the [[Gaianism|Gaians]].<ref>{{Cite web|url=http://metamorphoptics.blogspot.com/|title=m e t a m o r p h o p t i c s|website=metamorphoptics.blogspot.com|access-date=2016-12-12|archive-url=https://web.archive.org/web/20161213143103/http://metamorphoptics.blogspot.com/|archive-date=13 December 2016|url-status=live}}</ref> Whether these can be said to be collective intelligence systems is an open question. Some, e.g. [[Bill Joy]], simply wish to avoid any form of autonomous artificial intelligence and seem willing to work on rigorous collective intelligence in order to remove any possible niche for AI.<ref>{{Cite news|url=https://www.wired.com/2000/04/joy-2/|title=Why the Future Doesn't Need Us|last=Joy|first=Bill|newspaper=WIRED|access-date=2016-12-12|archive-url=https://web.archive.org/web/20161204003455/https://www.wired.com/2000/04/joy-2/|archive-date=4 December 2016|url-status=live}}</ref>
Harsh critics of artificial intelligence on ethical grounds are likely to promote collective wisdom-building methods, such as the [[new tribalists]] and the [[Gaianism|Gaians]].<ref>{{Cite web|url=http://metamorphoptics.blogspot.com/|title=m e t a m o r p h o p t i c s|website=metamorphoptics.blogspot.com|access-date=2016-12-12|archive-url=https://web.archive.org/web/20161213143103/http://metamorphoptics.blogspot.com/|archive-date=13 December 2016|url-status=live}}</ref> Whether these can be said to be collective intelligence systems is an open question. Some, e.g. [[Bill Joy]], simply wish to avoid any form of autonomous artificial intelligence and seem willing to work on rigorous collective intelligence in order to remove any possible niche for AI.<ref>{{Cite news|url=https://www.wired.com/2000/04/joy-2/|title=Why the Future Doesn't Need Us|last=Joy|first=Bill|newspaper=WIRED|access-date=2016-12-12|archive-url=https://web.archive.org/web/20161204003455/https://www.wired.com/2000/04/joy-2/|archive-date=4 December 2016|url-status=live}}</ref>
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*
* 分布式认知
*
* 促进(商业)
*
* 主持人
*
* 第一百次猴子效应
*
* 间谍大邻演
*
* 图书馆
*
* 亚历山大图书馆
*
* 开放空间会议
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== Further reading ==
== Further reading ==
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*
*
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* CIA。(2008).世界概况。(2008年9月3日访问)
* CIA.(2008).世界概况。(2008年9月3日访问)
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