The first AAAI Conference on Human Computation and Crowdsourcing (HCOMP-2013) was be held November 6-9, 2013 in Palm Springs, California. Three workshops took place on Saturday, November 9th: Crowdsourcing at Scale (full day), Human and Machine Learning in Games (full day) and Scaling Speech, Language Understanding and Dialogue through Crowdsourcing (half day).

The aim of the Disco: Human and Machine Learning in Games workshop was to extend upon the focus of two past workshops and explore the intersection of entertainment, learning and human computation. The goal of the workshop was to examine both human learning and machine learning in games and human computation. Human computation methods let machines learn from humans where games can provide humans the opportunity to learn. The workshop was thus devoted to I learn, in Latin disco, for machines and humans alike. The First AAAI Conference on Human Computation and Crowdsourcing Was Held in the Southern California Desert Community of Palm Springs.

Exploiting the playfulness of games has been extremely successful in bringing humans “in the loop” to solve com­plex computational tasks that would otherwise be hardly tractable. Although many proposals and systems after this paradigm have been developed, deployed, and tested, the relationship between play and human computation still de­serves more investigations. Most work in human computa­tion focuses on the ability for the machine to exploit, or learn from, humans. The workshop has a slightly different focus: the exploration of extending “I learn” (“disco” in Latin) to machines and humans alike. Games hold tremen­dous potential for discovery related to human and machine computation because of the intrinsic relation between play and learning. Extending and building upon the focus of past workshops on games and human computation Disco aims at exploring the intersection of entertainment, learning and human computation.

In recent years various games have been developed to generate useful data for scientific and commercial purposes. Current human computation games are tailored around a task they aim to solve, adding game mechanics to conceal monotonous workflows. These gamification approaches, although providing valuable gaming experience, do not cover the wide range of experiences seen in digital games today. This work presents a new use for design concepts for human computation games and an evaluation of player experiences.