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The Technological Potential
Four presenters focused on the capabilities of new technologies in peacebuilding. The rapidly growing range and scope of applications point to tremendous potential, although the contributions of technology toward preventing and mitigating violence depend on both the specific application and the context.
THE TECHNOLOGICAL CAPABILITIES
Prabakhar Raghavan of Google described some of the many technological capabilities that are now available. For example, it is routine in many parts of the world to use the collective flow of information from smartphones on a highway to measure traffic; the information can then be conveyed back to individual drivers about the state of traffic and the time it will take to get somewhere. This approach of using a “swarm of sensors” has been completely mechanized and is no longer “deep” (futuristic) technology. Instead, creativity centers on the development of new applications for the technology. The variety of applications to which swarms of sensors could be applied was not foreseen ten years ago, Raghavan said. Indeed, people tend to overestimate what will be possible in one year but underestimate what will be possible in ten years.
Another new trend is the remarkable power of machine learning. In the past, computer scientists tried to dissect every problem in minute detail, analyze it, and come up with the optimum solution, but over the past two decades they have made great progress using a different approach. Instead of analyzing problems, they feed large amounts of data into computers along with a machine learning algorithm. The computers then “learn” how to carry out actions based on their analysis of the data. For example, Andrew Ng and his colleagues at Stanford University have used this approach to teach an autonomous model helicopter how to fly patterns that no human pilot would ever fly.1 “In some sense, 200 years of wisdom in fluid dynamics and aeronautics got compressed simply by throwing a lot of data” at the problem, said Raghavan. This approach is not universally applicable, but it has considerable promise. “This sort of machine learning and control has gotten us to the point where we almost have driverless cars on the road, and that’s a very exciting development if it can cut 30,000 road fatalities a year.”
The challenge is much greater for peacebuilding, Raghavan admitted. Once a machine learning program has seen 50 street corners, it has a pretty good model of what a street corner is. But machines will not perform as well after seeing 50 conflicts and trying to make inductive inferences about the 51st. Conflicts are far more detailed in their social and political under-pinnings, so technological solutions can only go so far. Nevertheless, said Raghavan, “I’m a convert. I have tremendous faith in what machine learning is capable of accomplishing. There are times when you don’t have to get to the bottom of the detailed analysis. Machines can do things for you that are remarkably powerful.”
Raghavan also pointed out that most computer cycles are used not to compute but to communicate. In many emerging markets, many people do not have a car but they have a smartphone. In that sense, transportation is falling behind communication in the modern pyramid of human needs. People may not have 24-hour electricity, but they have enough to keep their phones charged. “There is something very powerful about that,” said Raghavan, and peacebuilding needs to tap into that development.
As technologies continue to develop and be applied in unanticipated ways, Raghavan suggested that pressure from the peacebuilding community directed at technology developers to apply these new technologies to the cause of peace could have tremendous benefits.
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1 A video demonstration is available at http://heli.stanford.edu (May 14, 2013).