Collective intelligence最新文献_第3页

New books on collective intelligence: Growing the field: Interesting new books on collective intelligence 关于集体智慧的新书:发展领域:有趣的关于集体智慧的新书

Collective intelligence Pub Date : 2022-08-01 DOI: 10.1177/26339137221114176

G. Mulgan

引用次数: 0

Editorial to the Inaugural Issue of Collective Intelligence 《集体智慧》创刊号社论

Collective intelligence Pub Date : 2022-08-01 DOI: 10.1177/26339137221114179

J. Flack, Panos Ipeirotis, T. Malone, G. Mulgan, S. Page

{"title":"Editorial to the Inaugural Issue of Collective Intelligence","authors":"J. Flack, Panos Ipeirotis, T. Malone, G. Mulgan, S. Page","doi":"10.1177/26339137221114179","DOIUrl":"https://doi.org/10.1177/26339137221114179","url":null,"abstract":"Collective behavior is a universal property of biological, social, and many engineered systems. However, the study of collective intelligence—roughly, the production of adaptive, wise, or clever structures and behaviors by groups— remains nascent. Despite that, it is growing in various disciplines, from biology and psychology to computer science and economics, management, and political science to mathematics, complexity science, and neuroscience. With the launch of Collective Intelligence, we aim to create a publication that transcends disciplines, methodologies, and traditional formats. We hope to help discover principles that can be useful to both basic and applied science and encourage the emergence of a unified discipline of study. Collective Intelligence (the Journal) is a global, peerreviewed, open-access journal. It will feature research articles, perspectives, dialogues, and artistic expressions, all geared toward a community of scholars in many disciplines. In this editorial, we highlight issues in collective intelligence research where attention will aid in discovering principles, concepts, and tools needed to unify the discipline. We proceed with a light hand, guided by recognizing that our role is to facilitate deep, provocative analyses and discussions rather than to define and, therefore, delimit the field.","PeriodicalId":93948,"journal":{"name":"Collective intelligence","volume":"53 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87703266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Self-organization in online collaborative work settings 在线协作工作环境中的自组织

Collective intelligence Pub Date : 2022-08-01 DOI: 10.1177/26339137221078005

Ioanna Lykourentzou, F. Vinella, F. Ahmed, Costas Papastathis, Konstantinos Papangelis, Vassilis-Javed Khan, J. Masthoff

{"title":"Self-organization in online collaborative work settings","authors":"Ioanna Lykourentzou, F. Vinella, F. Ahmed, Costas Papastathis, Konstantinos Papangelis, Vassilis-Javed Khan, J. Masthoff","doi":"10.1177/26339137221078005","DOIUrl":"https://doi.org/10.1177/26339137221078005","url":null,"abstract":"As the volume and complexity of distributed online work increases, collaboration among people who have never worked together in the past is becoming increasingly necessary. Recent research has proposed algorithms to maximize the performance of online collaborations by grouping workers in a top-down fashion and according to a set of predefined decision criteria. This approach often means that workers have little say in the collaboration formation process. Depriving users of control over whom they will work with can stifle creativity and initiative-taking, increase psychological discomfort, and, overall, result in less-than-optimal collaboration results—especially when the task concerned is open-ended, creative, and complex. In this work, we propose an alternative model, called Self-Organizing Pairs (SOPs), which relies on the crowd of online workers themselves to organize into effective work dyads. Supported but not guided by an algorithm, SOPs are a new human-centered computational structure, which enables participants to control, correct, and guide the output of their collaboration as a collective. Experimental results, comparing SOPs to two benchmarks that do not allow user agency, and on an iterative task of fictional story writing, reveal that participants in the SOPs condition produce creative outcomes of higher quality, and report higher satisfaction with their collaboration. Finally, we find that similarly to machine learning-based self-organization, human SOPs exhibit emergent collective properties, including the presence of an objective function and the tendency to form more distinct clusters of compatible collaborators.","PeriodicalId":93948,"journal":{"name":"Collective intelligence","volume":"54 5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84815269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Collective intelligence as a public good 集体智慧是一种公共产品

Collective intelligence Pub Date : 2022-08-01 DOI: 10.1177/26339137221083293

N. Leonard, S. Levin

引用次数: 8

We the swarm—Methodological, theoretical, and societal (r)evolutions in collective decision-making research 我们研究群体——在集体决策研究中的方法论、理论和社会(r)进化

Collective intelligence Pub Date : 2022-08-01 DOI: 10.1177/26339137221133400

S. Garnier, M. Moussaïd

{"title":"We the swarm—Methodological, theoretical, and societal (r)evolutions in collective decision-making research","authors":"S. Garnier, M. Moussaïd","doi":"10.1177/26339137221133400","DOIUrl":"https://doi.org/10.1177/26339137221133400","url":null,"abstract":"Collective decision-making constitutes a core function of social systems and is, therefore, a central tenet of collective intelligence research. From fish schools to human crowds, we start by interrogating ourselves about the very definition of collective decision-making and the scope of the scientific research that falls under it. We then summarize its history through the lenses of social choice theory and swarm intelligence and their accelerating collaboration over the past 20 or so years. Finally, we offer our perspective on the future of collective decision-making research in 3 mutually inclusive directions. We argue (1) that the possibility to collect data of a new nature, including fine-grain tracking information, virtual reality, and brain imaging inputs, will enable a direct link between plastic individual cognitive processes and the ontogeny of collective behaviors; (2) that current theoretical frameworks are not well suited to describe the long-term consequences of individual plasticity on collective decision-making processes and that, therefore, new formalisms are necessary; and finally (3) that applying the results of collective decision-making research to real-world situations will require the development of practical tools, the implementation of monitoring processes that respect civil liberties, and, possibly, government regulations of social interventions by public and private actors.","PeriodicalId":93948,"journal":{"name":"Collective intelligence","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74306342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A descriptive analysis of collective intelligence publications since 2000, and the emerging influence of artificial intelligence 对2000年以来集体智能出版物的描述性分析，以及人工智能的新兴影响

Collective intelligence Pub Date : 2022-08-01 DOI: 10.1177/26339137221107924

A. Berditchevskaia, Eirini Maliaraki, Konstantinos Stathoulopoulos

{"title":"A descriptive analysis of collective intelligence publications since 2000, and the emerging influence of artificial intelligence","authors":"A. Berditchevskaia, Eirini Maliaraki, Konstantinos Stathoulopoulos","doi":"10.1177/26339137221107924","DOIUrl":"https://doi.org/10.1177/26339137221107924","url":null,"abstract":"Collective intelligence (CI) is an interdisciplinary field that draws on a wide range of academic disciplines but has struggled to capitalise on cross-pollination between fields, particularly ones which do not self-identify with the collective intelligence label. Past studies have largely undertaken a qualitative and manual approach to classifying different trends in the CI literature. This method risks missing a significant proportion of publications in the field. To this end, we present the first attempt to reflect the field to itself through an automated and quantitative descriptive approach using Microsoft Academic Graph (MAG) to collect and analyse 39,334 CI papers. We further focus our investigation on a subset of the CI literature, at the intersection of artificial intelligence (AI) and CI to understand how these two fields are interacting. We show that while the annual number of CI-only publications has remained steady since 2015, AI+CI research has continued to increase. Publications in the crossover of AI+CI are growing at a faster rate than CI-only papers but show less topical and disciplinary breadth. This may be having a spillover effect on the topical focus of non-AI collective intelligence research. We hope this analysis sheds more light on the dynamics of the CI ecosystem.","PeriodicalId":93948,"journal":{"name":"Collective intelligence","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86204647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Bridging the polarization gap: Maximizing diffusion among dissimilar communities 弥合两极分化差距:在不同社区之间最大限度地扩散

Collective intelligence Pub Date : 2022-08-01 DOI: 10.1177/26339137221128542

Marcin Waniek, César A. Hidalgo

{"title":"Bridging the polarization gap: Maximizing diffusion among dissimilar communities","authors":"Marcin Waniek, César A. Hidalgo","doi":"10.1177/26339137221128542","DOIUrl":"https://doi.org/10.1177/26339137221128542","url":null,"abstract":"Polarized networks, composed of weakly connected and self-reinforcing groups, can limit the diffusion of ideas, behaviors, and innovations. Here, we use a complex contagion model, in which diffusion depends on both the connectivity and the similarity of individuals, to ask how to optimally build bridges and enhance diffusion in networks characterized by fragmentation and homophily. First, we show that the problem is NP-hard. Then, we explore the space of solutions using heuristics, finding that connecting high degree nodes, or hubs, is an ineffective strategy to accelerate diffusion in fragmented and homophilous networks. We show that in these networks, diffusion is more effectively accelerated by connecting similar but low degree nodes. These results tell us that, in the presence of homophily and polarization, connecting communities through their most central actors may impede rather than facilitate diffusion. Instead, strategies to accelerate the diffusion of innovation, behaviors, and ideas should focus on creating links among the most similar members of different communities. These findings shed light on the diffusion of ideas and innovations in polarized networks. CCS Concepts: • Mathematics of computing → Network optimization; • Information systems → Social networks","PeriodicalId":93948,"journal":{"name":"Collective intelligence","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88182355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Examining the limits of the Condorcet Jury Theorem: Tradeoffs in hierarchical information aggregation systems 考察孔多塞陪审团定理的局限性:层次信息聚合系统中的权衡

Collective intelligence Pub Date : 2022-08-01 DOI: 10.1177/26339137221133401

L. Böttcher, G. Kernell

{"title":"Examining the limits of the Condorcet Jury Theorem: Tradeoffs in hierarchical information aggregation systems","authors":"L. Böttcher, G. Kernell","doi":"10.1177/26339137221133401","DOIUrl":"https://doi.org/10.1177/26339137221133401","url":null,"abstract":"Condorcet’s Jury Theorem states that the correct outcome is reached in direct majority voting systems with sufficiently large electorates as long as each voter’s independent probability of voting for that outcome is greater than 1/2. Previous research has found that switching to a hierarchical system always leads to an inferior result. Yet, in many situations direct voting is infeasible (e.g., due to high implementation or infrastructure costs), and hierarchical voting may provide a reasonable alternative. This paper examines differences in accuracy rates of hierarchical and direct voting systems for varying group sizes, abstention rates, and voter competences. We derive three main results. First, we prove that indirect two-tier systems differ most from their direct counterparts when group size and number are equal (i.e., when each equals N d , where Nd is the total number of voters in the direct system). In multitier systems, we prove that this difference is maximized when group size equals N d n , where n is the number of hierarchical levels. Second, we show that while direct majority rule always outperforms indirect voting for homogeneous electorates, hierarchical voting gains in accuracy when either the number of groups or the number of individuals within each group increases. Third, we prove that when voter abstention and competency are correlated within groups, hierarchical systems can outperform direct voting. The results have implications beyond voting, including information processing in the brain, collective cognition in animal groups, and information aggregation in machine learning.","PeriodicalId":93948,"journal":{"name":"Collective intelligence","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78098059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

An exchange of letters on the role of noise in collective intelligence 就噪音在集体智慧中的作用交换信件

Collective intelligence Pub Date : 2022-08-01 DOI: 10.1177/26339137221078593

D. Kahneman, D. Krakauer, O. Sibony, C. Sunstein, David Wolpert

引用次数: 3

The wisdom of crowds versus the madness of mobs: An evolutionary model of bias, polarization, and other challenges to collective intelligence 群体的智慧与暴民的疯狂:偏见、两极分化的进化模型，以及对集体智慧的其他挑战

Collective intelligence Pub Date : 2022-08-01 DOI: 10.1177/26339137221104785

A. Lo, Ruixun Zhang

{"title":"The wisdom of crowds versus the madness of mobs: An evolutionary model of bias, polarization, and other challenges to collective intelligence","authors":"A. Lo, Ruixun Zhang","doi":"10.1177/26339137221104785","DOIUrl":"https://doi.org/10.1177/26339137221104785","url":null,"abstract":"Despite its success in financial markets and other domains, collective intelligence seems to fall short in many critical contexts, including infrequent but repeated financial crises, political polarization and deadlock, and various forms of bias and discrimination. We propose an evolutionary framework that provides fundamental insights into the role of heterogeneity and feedback loops in contributing to failures of collective intelligence. The framework is based on a binary choice model of behavior that affects fitness; hence, behavior is shaped by evolutionary dynamics and stochastic changes in environmental conditions. We derive collective intelligence as an emergent property of evolution in this framework, and also specify conditions under which it fails. We find that political polarization emerges in stochastic environments with reproductive risks that are correlated across individuals. Bias and discrimination emerge when individuals incorrectly attribute random adverse events to observable features that may have nothing to do with those events. In addition, path dependence and negative feedback in evolution may lead to even stronger biases and levels of discrimination, which are locally evolutionarily stable strategies. These results suggest potential policy interventions to prevent such failures by nudging the “madness of mobs” towards the “wisdom of crowds” through targeted shifts in the environment.","PeriodicalId":93948,"journal":{"name":"Collective intelligence","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81544457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5