Getting the crowd to perform small tasks has been popular for over a decade now.  Arguably the most interesting of these kind of projects have been those that have tapped into things we would do normally to perform something worthwhile at the same time.

I wrote recently about the continued success of the Folding@Home distributed computer application that taps into our latent computing power to form a supercomputer that can perform scientific work.  The reCAPTCHA project has also been highly successful, with it enlisting the input of users decoding captcha messages being used to digitize hard to decode pieces of text.  An offshoot of this project has seen users translating texts as part of the Duolingo service.

A service along similar lines is Twitch.  Twitch is an Android app that attaches itself to the screen most smartphones present us with when the device is locked.  It asks you to complete a few simple tasks, such as ranking images or structuring data whenever you unlock your phone.  The information is then collated and compiled with the hope that it could prove useful to groups such as university academics or market researchers.

The app was built to try and exploit the 160 million people in the US alone that have smartphones, and therefore have lock screens that are ordinarily under-used.  The brainchild of a number of academics, the app has recently been the subject of a research paper that hoped to delve deeper into the possibilities of such a service.

It saw 82 Twitch users complete 19 tasks per day over a three week period.  These tasks ranged from saying what they were wearing, how energetic they felt and how many people were nearby.  The study discovered that these simple tasks typically took no longer than the traditional slide to unlock motion, with each task taking on average 1.6 seconds, vs 1.4 seconds for the normal swipe.

“All we did was replace that gesture that makes sure you’re paying attention with something else that makes sure you’re paying attention and also happens to contribute to some global goal,” the researchers say.

There was no payment for performing these tasks, but users were informed of how many other people near them chose the same answer.  That proved of limited success however, as nearly 50% of participants in the study uninstalled the app within a single day.

Slide to X is a similar service, but they pay people to participate.  They present users with a number of options when unlocking their phone.  They might for instance answer a question around their health or recent activities, or they may simply swipe as usual.

It emerged that by paying people, early participants answered on average 50 questions per day, or over 750 over a two week period.  The compensation, albeit a small one of < 3c per question, seemed sufficient to encourage continued participation.  The hope is that the service will be expanded so that non-profits can utilise the platform for simple data collection style research.

Both represent an interesting way of tapping into the wisdom of crowds.  Despite two contrasting approaches, both are undergoing quite rapid development, so will no doubt evolve considerably from these early models.  Certainly an area to keep an eye on.