Using Data To Solve Complex HUMANITARIAN Problems

I was scrolling through YouTube TED Talks when I found this witty video that really piqued my interest and gave a lot of insight into data analysis.

I am a firm believer that data will become one of the most important resources available as the variety, amount and access to data increases drastically over time. Data has the ability to form patterns and visualize trends that may otherwise go unseen. In the context of humanitarian crises, seemingly unconnected data, such as the cell phone pings mentioned in the video, can tell a story that lets us predict and prevent a catastrophe before it can even occur. Sometimes, analyzing these copious amounts of data is a task that can’t be reasonably done by hand. Instead, algorithms, such as the one used in the video to optimize food transport to those in need, can be used to analyze, relate, and compare massive amounts of data to find an optimized solution. Data Science has been (and is continuing to be) widely used by data scientists in recent years to solve a vast variety of problems, and the introduction of newer and better machine learning algorithms and AI should only continue to improve our understanding of the various humanitarian crises that challenge world policymaking, and in suggesting potential solutions.