How Artificial Intelligence Can Make Public Transportation Safer

How Artificial Intelligence Can Make Public Transportation Safer

In the history of London's Underground rail network, the underground fire hazard incident of 1987 at the King’s cross station was one the biggest disasters. It claimed 31 lives and also severely scarred the reputation of London Underground. After multiple inquiries, it was concluded that the fire had started because someone dropped a lit match onto a wooden escalator. But how did such a trivial incident snowball into a full-blown disaster?

Pulitzer prize-winning author and journalist Charles Duhigg analyzed this question in his international bestseller The Power of Habit. Among many other factors that contributed to the disaster, the following chain of events in the run-up to the accident caught our eye:

Charles concluded that it was a total failure of communication within the organization that led to this accident. He suggests that, like individuals, organizations also have habits which define how they function and like any habit these can also be changed by taking the right steps. We agree with Charles' insights about how altering the routine habits of people can have a wide-ranging impact on an organization. However, there is one constraint that acts as a glass ceiling on the level of performance: a reliance on humans.

In the words of Daniel Kahneman, humans are very susceptible to "biases, shortcuts, and cognitive illusions." Constant undivided attention requires a lot of mental effort and is difficult for humans to sustain for a long time. Also, people are emotional and their decisions in an organization are impacted by many dynamics related to personal mental state, relationships with co-workers, office politics, etc. The understanding of what is an emergency is also not consistent across people. We see a strong case for an Artificial Intelligence system to step in and aid humans in making decisions relating to safety.

With the advent of smartphones, wireless data, and social media, the times are changing. Users of public transport now actively share their feedback to network operators via social media. Even a technologically laggard network like the Indian railways now gets ~5,000 tweets per day from customers. India’s railway minister has even made it mandatory for all his senior officers to be active on Twitter. All the stars now seem to have aligned for AI to enter the emergency response and customer service space.

We propose a solution where an Artificial Intelligence algorithm will monitor all the incoming customer communication via Twitter, Facebook, and online chats and identify whether they relate to some critical emergency situation (like fire, faulty equipment, crime, etc). Once identified as an emergency case, the system will figure out which department and location (i.e. safety department of King's Cross Station) are best equipped to handle the situation and automatically push the customer complaint to mobile phones of all the relevant stakeholders. By getting the first-hand information directly from the customer and facilitating quick communication, response to the emergency will become more effective.

To drive home the point, we can see how the above-proposed system could have potentially averted the King's Cross fire on multiple levels. The commuter who first saw the burning tissue paper could have registered an online complaint via online chat or social media.

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