Information architectures: a framework for understanding socio-technical systems

被引：0

作者：

Paul E. Smaldino ^{[1
]}

Adam Russell ^{[2
]}

Matthew R. Zefferman ^{[3
]}

Judith Donath ^{[4
]}

Jacob G. Foster ^{[5
]}

Douglas Guilbeault ^{[2
]}

Martin Hilbert ^{[6
]}

Elizabeth A. Hobson ^{[7
]}

Kristina Lerman ^{[8
]}

Helena Miton ^{[9
]}

Cody Moser ^{[3
]}

Jana Lasser ^{[7
]}

Sonja Schmer-Galunder ^{[1
]}

Jacob N. Shapiro ^{[10
]}

Qiankun Zhong ^{[11
]}

Dan Patt ^{[12
]}

机构：

[1] University of California-Merced,Department of Cognitive and Information Sciences

[2] Santa Fe Institute,Information Sciences Institute

[3] University of Southern California,Department of Defense Analysis

[4] Naval Postgraduate School,Berkman Klein Center

[5] Harvard University,Departments of Informatics and Cognitive Science

[6] Indiana University-Bloomington,Graduate School of Business

[7] Stanford University,Department of Communication

[8] University of California-Davis,Department of Biological Sciences

[9] University of Cincinnati,IDea_Lab

[10] University of Graz,Department of Computer & Information Science & Engineering

[11] Complexity Science Hub Vienna,Department of Politics, School of Public and International Affairs

[12] University of Florida,undefined

[13] Princeton University,undefined

[14] Max Planck Institute for Human Development,undefined

[15] Hudson Institute,undefined

来源：

npj Complexity | / 2卷 / 1期

关键词：

D O I：

10.1038/s44260-025-00037-z

中图分类号：

学科分类号：

摘要：

A sequence of technological inventions over several centuries has dramatically lowered the cost of producing and distributing information. Because societies ride on a substrate of information, these changes have profoundly impacted how we live, work, and interact. This paper explores the nature of information architectures (IAs)—the features that govern how information flows within human populations. IAs include physical and digital infrastructures, norms and institutions, and algorithmic technologies for filtering, producing, and disseminating information. IAs can reinforce societal biases and lead to prosocial outcomes as well as social ills. IAs have culturally evolved rapidly with human usage, creating new affordances and new problems for the dynamics of social interaction. We explore societal outcomes instigated by shifts in IAs and call for an enhanced understanding of the social implications of increasing IA complexity, the nature of competition among IAs, and the creation of mechanisms for the beneficial use of IAs.

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