Tag Archives: Gaming

This blog sequel follows this one on Netsourcing, Crowdsourcing and Turksourcing. This new round of thinking is inspired by a recent dinner conversation (that made it to the New York Times!) with Riley Crane, Omar Wasow, Anand Giridharadas, and Jen Brea. If the ideas below seem a little off the wall, the bottle of Kirsch I brought over for the Swiss fondue is to blame. Some parts of this post were were also inspired by The Polymath Project and conversations with Kuang Chen, Abraham Flaxman and Rob Munro during the Symposium on Artificial Intelligence for Development (AI-D) at Stanford University.

I wonder how many indoor cycling bikes exist in the world, or at least in the US. The number may in part be a function of the number of gyms. In any event, to borrow the language of Douglas Adams, the number must be “vastly, hugely, mind-bogglingly big,” especially the total number of hours spent on these bikes everyday in California alone. I’ve often wondered how much energy these machines generate when used; enough to recharge my iPhone? Hundreds of iPhones?  Why do I ask?

I’ve been thinking about the number of hours that gamers spend playing computer games in the US. Hundreds of thousands hours? I’m not quite sure what the correct order of magnitude is, but I do know the number is increasing. So how does the cycling analogy come in? Simple: how can we harness the millions of hours spent playing computer games every year to turksource crisis information? Could real world information be subtly fed into these games when necessary to process Human Intelligence Tasks (HITs) that would help tag and/or geolocate crisis information? Can we think of mobile games akin to FourSquare that could generate collective action around HITs?

In other words, what is the game equivalent of reCAPTCHA for turksourcing crisis information? Remember the computer game “Where in the World is Carmen Sandiego?” Could a cross between that type of learning game, a treasure hunt and “The DaVinci Code” get gamers hooked? I’m probably thinking way too old school here. Perhaps taking the most popular games today and subtly embed some HITs is the way to go. As mentioned in my previous blog post, one of the most time consuming and human resource intensive tasks that volunteers carried out during the first weeks of Ushahidi-Haiti was the manual, near real-time geo-location of unfolding events.

So how about adding a fun gaming user interface to OpenStreetMap? Like any good game, a user would be able to specify a difficulty level. Making a mobile UI would also come in handy when tourists are abroad and want to help geolocate. You’ve heard of eco-tourism, welcome to geo-tourism. Maybe Lonely Planet or Rough Guides could partner on such a project. Or, as happened in Haiti, geo-coding was also crowdsourced thanks to the pro-active Haitian volunteers of Mission 4636 who were far quicker at tagging than student volunteers. But what happens if the only volunteers around are not country experts or familiar with satellite imagery? Is there a way to use a Mechanical Turk Service approach to greatly simplify this geocoding process?

Maybe the day will come when kids whose parents tell them to get off their computer game to do their homework will turn around and say: “But Mom, I’m learning about the geography of Mozambique, which is what my quiz is on tomorrow, and I’m playsourcing crisis information to save lives at the same time!”

Patrick Philippe Meier

The near real-time crisis mapping of the disasters in Haiti and Chile using Ushahidi required a substantial number of student volunteers. These volunteers were not the proverbial crowd but rather members of pre-existing, highly-connected social networks: universities. How do we move from netsourcing to crowdsourcing and on to turksourcing?

Student volunteers from Fletcher/Tufts, SIPA/Columbia and the Graduate Institute in Geneva all represent established social networks and not an anonymous crowd. They contributed over ten thousand free hours over the past 3 months to monitor hundreds of sources on the web and map actionable information on an ongoing basis. The Core Team at Fletcher spent dozens of hours training volunteers on media monitoring and mapping.

Netsourcing presents some important advantages. Pre-existing social ties can help mobilize a trusted volunteer network. I  just sent one email to the Fletcher list-serve and because the Fletcher student body is a tight community, this eventually let do hundreds of volunteers being trained and contributing to the crisis mapping of Haiti.

The first call for volunteers

At the same time, however, netsourcing is bounded crowdsourcing. In other words, netsourcing is scale-constrained. Imagine if Wikipedia contributions had been limited to professors only—that too would be bounded crowdsourcing. So how do we move from netsourcing to crowdsourcing crisis information? How do we move from having 300 volunteers connected via existing social networks to 300,000 or even 3,000,000 anonymous volunteers?

This was one of the many questions that my colleague Riley Crane, a friend of his and I discussed for almost 4 hours over dinner. (Riley recently rose to fame when he and his team at MIT that won DARPA’s Red Balloon competition). The answer, we think, is to develop a Mechanical Turk Service plug-in for Ushahidi. I’m calling this turksourcing. The two most time-consuming tasks that volunteers labored on was media monitoring and geo-location. Both processes can be disaggregated into human intelligence tasks (HITs) combined with some automation, like Swift River. And none of this would require prior training.

This is a conversation I very much look forward to continuing with Riley and one that I also plan to bring up at Nathan Eagle‘s Symposium on Artificial Intelligence for Development (AI-D) at Stanford next Monday. There is another related conversation that I’m excited to continue—namely the use of distributed, mobile gaming as an incentive catalytic for collective action, an area that Riley has spent a lot of time thinking about.

In terms of Ushahidi, If turksourcing crisis information can be combined with gaming, users could compete for altruism points, e.g., for how many HITs they contributed to a disaster response. This could be a proxy for how “good” a person is; a kind of public social ranking score for those who opt in. I imagine having individuals include their score and ranking on their blog (much like the number of Twitter followers they have). Who knows, a high altruism score could even get you more dates on Match.com.

Patrick Philippe Meier