{"id":36454,"date":"2018-11-13T19:56:43","date_gmt":"2018-11-14T00:56:43","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/machine-learning-vs-poachers\/"},"modified":"2018-11-13T19:56:43","modified_gmt":"2018-11-14T00:56:43","slug":"machine-learning-vs-poachers","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/machine-learning-vs-poachers\/","title":{"rendered":"Machine Learning vs Poachers"},"content":{"rendered":"

Is wildlife conservation important?<\/strong><\/p>\n

The wildlife of our planet is endangered. But why do we care? The preservation of wildlife costs us millions of dollars, while there are many other problems of humankind that require immediate support such as fighting hunger or poverty.<\/p>\n

One reason is that we want to: \u201cmany of us love the natural world. We think animals are cute, majestic, or just plain fascinating\u201d[1]<\/sup>.<\/p>\n

Figure 1: Young elephant is playing<\/p>\n

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The wildlife is something we inherited and responsible for. Moreover, the decrease in the variety of spices has a direct negative impact on natural ecosystems and local economies[2]<\/sup>.<\/p>\n

Poaching is one of the most significant threats to wildlife. \u201cEvery day in Africa nearly 100 elephants are killed for their ivory\u201d[3]<\/sup>. The global tiger population has dropped over 95% from the start of the 1900s and has resulted in three out of nine species extinctions[4]<\/sup>.<\/p>\n

Exhibit 1: Wildlife population is in decline[5]<\/sup><\/p>\n

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Poaching also provides significant profits to terrorist organizations, \u201cwhich are which are attracted to wildlife trafficking because of its low risk of detection, high profits, and weak penalties\u201d[6]<\/sup>.<\/p>\n

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Predicting poaching behavior<\/strong><\/p>\n

Fighting against poaching is not easy. A population of animals is spread across huge area making patrolling very difficult. For example, Uganda Queen Elizabeth National Park, a home of 5,000 elephants, is spread across 763 sq miles[7]<\/sup>. To protect animals on such vast territory \u201cUganda Wildlife Authority uses 50 to 90 percent of its budget on ranger patrols\u201d[8]<\/sup>.<\/p>\n

In 2013 researchers from the University of South California (USC) in collaboration with Uganda Wildlife Authority (UWA) developed PAWS (Protection Assistant for Wildlife Security), an AI algorithm which analyses historical information on previous poaching activities and designs the most effective routes for patrolling by trying to predict where the next poaching activity will happen. The AI algorithm every time develops new routes for patrolling units to prevent poachers from predicting patrol’s activity[9]<\/sup>.<\/p>\n

Exhibit 2: PAWS Overview[10]<\/sup><\/p>\n

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As in other AI platforms, improvement of the PAWS machine learnings algorithms relies on large data available to analyze. Before the launch of the program, the wildlife data from UWA collected by rangers over 12 years from 2003 to 2014 were analyzed[2]<\/sup>. When patrollers execute the patrol strategy generated by PAWS over a period, more information is collected and become part of the input in the next round[10]<\/sup>. After an initial launch in Uganda, in 2014 PAWS was rolled out in Malaysia to further increase the amount of data available for analysis and test adaptability of PAWS in other geographical zones[11]<\/sup>.<\/p>\n

Currently, the project team is working on:<\/p>\n