Date of Award

12-2018

Degree Name

MS in Computer Science

Department/Program

Computer Science

College

College of Agriculture, Food, and Environmental Sciences

Advisor

Franz Kurfess

Advisor Department

<--Please Select Department-->

Advisor College

College of Agriculture, Food, and Environmental Sciences

Abstract

In recent years, new Artificial Intelligence technologies have mimicked examples of collective intelligence occurring in the natural world including flocks of birds, schools of fish, and swarms of bees. One company in particular, Unanimous AI, built a platform (UNU Swarm) that enables a group of humans to make decisions as a single mind by forming a real-time closed-loop feedback system for individuals. This platform has proven the ability to amplify the predictive ability of groups of humans in realms including sports, medicine, politics, finance, and entertainment. Previous research has demonstrated it is possible to further enhance knowledge accumulation within a crowd through curation and bias methods applied to individuals in the crowd.\newline

This study explores the efficacy of applying a machine learning pipeline to identify the top performing individuals in the crowd based on a structural profile of survey responses. The ultimate goal is to select these users as Swarm participants to improve the accuracy of the overall system. Unanimous AI provided 24 weeks of survey data collection consisting of 1,139 users from the NHL 2017-2018 season. By applying a machine learning pipeline, this study able to curate a crowd consisting of users that had an average z-score 0.309 and Wisdom of the Crowd prediction accuracy of 61.5%, which is 4.1% higher than a randomly selected crowd and 1.4% lower than Vegas favorite picks.

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