Getting Humans to do Quantum Optimization - User Acquisition, Engagement and Early Results from the Citizen Cyberscience Game Quantum Moves

TL;DR

This paper discusses the design, user engagement, and early results of Quantum Moves, a citizen science game that combines human intuition with quantum computing algorithms, highlighting diverse player profiles and motivation factors.

Contribution

It introduces the design process of Quantum Moves, analyzes player engagement and performance, and explores psychological motivation factors in a quantum physics citizen science game.

Findings

Diverse player base with different backgrounds and motivations.

Players recruited via real-world physics interest show higher engagement.

Female players outperform males in game performance.

Abstract

The game Quantum Moves was designed to pit human players against computer algorithms, combining their solutions into hybrid optimization to control a scalable quantum computer. In this midstream report, we open our design process and describe the series of constitutive building stages going into a quantum physics citizen science game. We present our approach from designing a core gameplay around quantum simulations, to putting extra game elements in place in order to frame, structure, and motivate players' difficult path from curious visitors to competent science contributors. The player base is extremely diverse - for instance, two top players are a 40 year old female accountant and a male taxi driver. Among statistical predictors for retention and in-game high scores, the data from our first year suggest that people recruited based on real-world physics interest and via real-world events, but only with an intermediate science education, are more likely to become engaged and skilled contributors. Interestingly, female players tended to perform better than male players, even though men played more games per day. To understand this relationship, we explore the profiles of our top players in more depth. We discuss in-world and in-game performance factors departing in psychological theories of intrinsic and extrinsic motivation, and the implications for using real live humans to do hybrid optimization via initially simple, but ultimately very cognitively complex games.