We need software to help us solve our collective problems

Cultural critic and educator David Goldberg calls for 'numeric foam' – software to help the community think through its problems.

David Goldberg

The people of Hawaiʻi need a scalable social software tool that simulates the various dimensions of life in these islands and explores the interactions and consequences of their challenges and opportunities. It would combine the increasing volume of data being accumulated by municipalities and the state, the collaborative and competitive pleasures of social media, the opinionistic narcissism of online democracy, and the tried and true joy of sandboxes, ant farms and terrariums. I imagine an ever-expanding foam of “alternate Hawaiis,” accessible via mobile phones, desktop computers and cable television.

“Scalable” refers to the complexity or depth of the representations expressing the userʻs the level of understanding. In a full-bore simulation like SimCity a successful metropolis is built by balancing variables determined by the designers. Technically, these variables must be understood and mastered before the game is played!

Though trial-and-error learning is great when nothing is at stake, and simulates the actual development of cities, in real life we don’t have all the variables at our disposal up front. Though we begin in prejudice and ignorance our understanding can change over time. True progress is attained by adding, removing and refining variables, not by figuring out the formulas that maximize them.

However, in software a problem is defined objectively by describing its variables in terms of numbers–this is the foundation of all games. We already think this way when we say something like “traffic on Oʻahu is bad,” especially when asked to rate it a scale of 1-10. This action is where the interface between politicians and their constituencies typically ends. But what if the next question was “why,” and you answered, “thereʻs too many cars,” or “the roads are in bad shape.” Both of answers can be quantified, and they form an implicit relationship with the original statement that anyone can understand… even if they disagree.

Here is where the social component comes in. If a system tracked my definition of the traffic problem in terms of assertive statements and related variables, anyone would be able to look at the resulting network and assess it. Others could identify dozens of traffic-affecting variables that I left out, or create new relationships between “thereʻs too many cars” and new variables. Rather than arguing with you about your understanding of Hawaii traffic you could tinker with a live representation of what I understand, on your terms, and we could both see the results of the change in the simulation.

And what if I don’t like where the simulation heads? I can challenge your variables or the new relationships you define, and vice versa, adding and subtracting until we both arrive at a model we like–but is it at that point realistic? A heaven? A hell? Answering that question is a matter of reviewing the variables and relationships again, not by dismissing someone for being “wrong.” We might also invite someone else entirely to play with the simulation.

Like any other digital medium, information structures made of this “Hawaiʻi Foam” could be traded, sampled (recombining the intuition of a kindergartener with the sophisticated analysis of a career economist,) link them together in hybrid models, or battle each other. They could be rapidly compared and searched, tracked against other factors such as the power of a news story or a freshly minted pop cultural trend. In any case, if the tool became popular enough, selecting for the best solutions from among the top users, sooner or later we might find ourselves wondering why we and our leaders simply can’t just solve the problems.