Attention-Based Stigmergic Distributed Collaborative Organizations

Introduction

"Attention is a scarce resource, information is not!"

In biological networks such as ant colonies, bee hives, or termites, you see self organization which builds and maintains critical architecture. Human beings can also take advantage of this self organizing mechanism to build and maintain institutions. The process is called stigmergy and to take advantage of this concept fully we have to revisit the fundamental theory of "the firm" as form of organization.

An attention based view of the firm

As human beings we are guided by our attention. It is also a fact that our attention is a scarce resource which many competing entities seek to capture. In an attention based view (ABV) of a firm it is attention which is the most precious resource and the allocation of attention is critical to the successful management of the firm. In a traditional top down hierarchical firm managerial attention is considered to be the most precious (Tseng & Chen, 2009), and is an very scarce resource. The allocation of attention within a firm can facilitate knowledge search. Knowledge search is part of the process of producing innovation and is effective or ineffective based on how management allocates their attention.

In the top down hierarchical model of the firm you must rely on managers properly allocating their attention because their attention is scarce. The problem of attention allocation (Tseng & Chen, 2009) and attention scarcity both plague traditional top down firms. In heterarchical flat organizations this may not be true anymore and when stigmergy comes into play it opens a door to a whole new method of knowledge search.

Attention-based stigmergic Distributed Collaborative Organizations

A Distributed Collaborative Organization (DCO) is a new model of human organization which did not exist until recently. Now that technology allows for Distributed Ledgers such as what we see with the Bitcoin blockchain it opens the door to new forms of human organizations such as the Distributed Collaborative Organization. Distributed Collaborative Organizations have unique capabilities and work by utilizing a token which represents "membership" in the DCO. Because of how DCOs are set up the tokens likely do not represent securities as they would if the traditional firm were used.

Attention-based stigmergic DCOs can take advantage of swarm intelligence to direct the attention of the members of the DCO. Stigmergy can be implemented through attractor patterns/attractor tokens, and incentive design patterns, both which would direct the attention and shape the activities of the swarm through simple algorithmic rules written as smart contracts. In this instance as Larry Lessig is famously quoted as saying: "Code is Law" but in a non-hierarchical swarm the user's attention is the most precious resource.

Because attention is the most precious resource in a swarm there should be a mechanism allowing advertisers, or others, to pay for the attention of individual members within the swarm. In this case the DCO would have to be designed in such a way that attention is treated as extremely scarce, something to be preserved by use of bots/autonomous agents (personal preference swarms?) and automation. These personal swarms or personal drone networks if you'd like to call them that would seek out knowledge and information on behalf of individuals without the possibility of distraction.

These swarms could seek out the best deals for individuals. It could collect an extremely detailed amount of information about each and every product and use algorithms to compare products. This would allow swarms to evaluate anything from video games, to supermarket food, to stocks, to populate a list and buy, or to apply swarm intelligence to the construction of investment portfolios. All of this leads to a completely new paradigm of human organization through self organizing stigmergic institutions.

References
Grosan, C., Abraham, A., & Chis, M. (2006). Swarm intelligence in data mining (pp. 1-20). Springer Berlin Heidelberg.

Martens, D., Baesens, B., & Fawcett, T. (2011). Editorial survey: swarm intelligence for data mining. Machine Learning, 82(1), 1-42.

Ocasio, W. (1997). TOWARDS AN ATTENTION-BASED VIEW OF THE FIRM WILLIAM OCASlO. Psychology, 1, 403-404.

Tseng, C. C., & CHEN, P. C. (2009, August). SEARCH ACTIVITIES FOR INNOVATION--AN ATTENTION-BASED VIEW. In Academy of Management Proceedings (Vol. 2009, No. 1, pp. 1-6). Academy of Management.