Facts and Figuring: An Experimental Investigation of Network Structure and Performance in Information and Solution Spaces

Shore, Jesse; Bernstein, Ethan; Lazer, David

doi:10.2139/ssrn.2412492

Cited by 31 publications

(48 citation statements)

References 50 publications

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“…Past research shows that social influence leads individuals to adopt their peers’ opinions and copy their solutions to problems ( 5 ), especially under conditions of network clustering ( 13 , 14 ), leading to a loss of aggregate diversity. Under certain conditions—performing simple estimation tasks or searching simple solution spaces with clear performance feedback—more efficiently connected networks of problem solvers can collectively outperform disconnected individuals ( 12 , 15 , 16 ) and inefficient networks ( 17 , 18 ), as people learn from each other and better solutions spread rapidly.…”

mentioning

confidence: 99%

How intermittent breaks in interaction improve collective intelligence

Bernstein

Shore

Lazer

2018

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

108

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SignificanceMany human endeavors—from teams and organizations to crowds and democracies—rely on solving problems collectively. Prior research has shown that when people interact and influence each other while solving complex problems, the average problem-solving performance of the group increases, but the best solution of the group actually decreases in quality. We find that when such influence is intermittent it improves the average while maintaining a high maximum performance. We also show that storing solutions for quick recall is similar to constant social influence. Instead of supporting more transparency, the results imply that technologies and organizations should be redesigned to intermittently isolate people from each other’s work for best collective performance in solving complex problems.

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mentioning

confidence: 99%

How intermittent breaks in interaction improve collective intelligence

Bernstein

Shore

Lazer

2018

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

108

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“…In Shore et al (2015) the dependence of the problem solving perfomance on network architecture has been studied in more detail. Recently, in Becker et al (2017) the impact of social networks on the quality of a collective estimation challenge has been analyzed.…”

Section: Resultsmentioning

confidence: 99%

The balance of autonomous and centralized control in scheduling problems

et al. 2018

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The scheduling of processes in a network is a core logistic challenge with a multitude of applications in our complex industrialized world. Often, scheduling decisions are based on incomplete and unreliable information. Here, a simple rule of 'more information, better decisions' may no longer hold and heuristics balancing global and local information, or centralized and autonomous control, may yield better performance. So far, only anecdotal evidence for the potential benefit of autonomous control in scheduling exists. Here, we explore this hypothesis within a minimal model derived from scheduling principles and the phenomenology of dynamical processes on graphs. In this model, centralized and autonomous control can be represented and quantitatively assessed, performance is well defined and problem complexity can be varied. Our model shows that a balance of centralized and autonomous control can enhance the performance in networks of decision-making entities. The mechanistic insight gained from the model also reveals the limitations of hybrid control setups: We find that communication at a high hierarchy level can give an advantage to centralized control. Counter-intuitively, it arises not from a higher degree of coordination and quicker convergence towards a common solution, but rather from an accelerated sampling of candidate choices leading to a measurable increase in information flow from higher to lower hierarchical levels. Our study allows us to formulate a new view of autonomous control in industrial production and derive a set of suggestions with the potential to enhance performance under realistic conditions of scheduling heuristics of jobs in a production process.

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“…Second, CSOPs are an abstraction of many resource allocation and optimization problems; thus, they capture important features of real-world group problem-solving exercises without requiring participants to have specialized skills. Third, as with other complex problems ( 31 ) , the payoff function for CSOPs can be described as a "rugged landscape" characterized by many locally optimal but globally suboptimal solutions. Correspondingly, CSOPs are amenable to potentially many solution strategies and styles, where no single strategy is universally superior ( 32 ) .…”

Section: Room Assignment Taskmentioning

confidence: 99%

Collective Problem-Solving of Groups Across Tasks of Varying Complexity

Almaatouq¹,

Yin²,

Dj³

2020

Preprint

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As organizations gravitate to group-based structures, the problem of improving performance through judicious selection of group members has preoccupied scientists and managers alike. However, it remains poorly understood under what conditions groups outperform comparable individuals, which individual attributes best predict group performance, or how task complexity mediates these relationships. Here we describe a novel two-phase experiment in which individuals were evaluated on a series of tasks of varying complexity; then randomly assigned to solve similar tasks either in groups of different compositions or as individuals. We describe two main sets of findings. First, while groups are more efficient than individuals and comparable “nominal group” when the task is complex, this relationship is reversed when the task is simple. Second, we find that average skill level dominates all other factors combined, including social perceptiveness, skill diversity, and diversity of cognitive style. Our findings illustrate the utility of a “solution-oriented” approach to identifying principles of collective performance.

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Facts and Figuring: An Experimental Investigation of Network Structure and Performance in Information and Solution Spaces

Cited by 31 publications

References 50 publications

How intermittent breaks in interaction improve collective intelligence

How intermittent breaks in interaction improve collective intelligence

The balance of autonomous and centralized control in scheduling problems

Collective Problem-Solving of Groups Across Tasks of Varying Complexity

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