This year at Mobile World Congress, co-founder and CPO Georg Polzer delivered a keynote about inclusive data’s role in establishing an artificially intelligent future. For those that couldn’t make it to snowy Barcelona this year, you can watch the talk or read a quick summary below.
Mobile network data from telecoms is truly inclusive data. It doesn’t matter if you can afford the iPhone X or use a specific app, anonymized telco data represents everyone. Using inclusive data, our A.I. can provide solutions to major issues the world is facing.
By applying our A.I. technology to mobile network data, we can shed light on how people move and their rationale for choosing a particular mode of transportation or route over another. City and transportation planners, governments and automotive and ride-sharing companies now have access to new information to understand their citizens’ and customers’ behavior and transform products and services accordingly.
Census and survey data used in transport planning and infrastructure investment neither captures how people move in real time nor properly represents a diverse population. Inclusive data in place of these antiquated methods means bus routes, roads and new transportation developments will be built based on facts rather than assumptions. This leads to improvements that will help the population move more efficiently within and between cities. Faster public transport built in the correct locations also means a better work-life balance and more time spent with your family.
The number and severity of natural disasters is expected to rise over the coming years. This is where inclusive data is vital to get real-time insights into the movement of a population during times of emergency.
With close to 70 percent of the global population expected to be using cell phones by 2019, telco data will become even more valuable in identifying where aid is most needed and the best locations to set up emergency shelters. Inclusive data can even help us understand the movement of people during disasters to determine the best evacuation routes.
Using inclusive data to train A.I. isn’t just about fixing what’s already there. It’s about truly representing an entire population. When used effectively — as in the case of city planning and disaster relief — inclusive data moves us a step closer to a more equal world that is built for everyone regardless of economic or cultural backgrounds.