Gaming the Attention Economy
Daniel Estrada, Jonathan Lawhead

TL;DR
This paper explores how natural human computation can be harnessed through attention management in crowds, exemplified by the Swarm! app, to solve economic optimization problems and enhance human computation.
Contribution
It introduces the concept of natural human computation and proposes using attention economy principles via Swarm! to improve collective problem-solving.
Findings
Attention dynamics can be leveraged for economic optimization
Swarm! demonstrates practical application of attention-based NHC
Managing attention economies offers promising future for human computation
Abstract
The future of human computation (HC) benefits from examining tasks that agents already perform and designing environments to give those tasks computational significance. We call this natural human computation (NHC). We consider the possible future of NHC through the lens of Swarm!, an application under development for Google Glass. Swarm! motivates users to compute the solutions to a class of economic optimization problems by engaging the attention dynamics of crowds. We argue that anticipating and managing economies of attention provides one of the most tantalizing future applications for NHC.
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Taxonomy
TopicsIoT and Edge/Fog Computing · Mobile Crowdsensing and Crowdsourcing · Blockchain Technology Applications and Security
