Data Science for fighting Human Trafficking

 

Recently one of my dear friends has made me aware of human trafficking problem in India. Human trafficking is a global scourge with its roots in poverty, lack of opportunities, and related difficult socioeconomic conditions.

I am a data scientist and it makes me wonder if Big Data can be used to understand and to solve such social problems. How can we employ tools of modern data science for social good?

At New College of Florida, the honors liberal arts college of Florida, my colleagues and students and I were recently discussing about role of data science for socially relevant projects. This post is inspired by this discussion and my friend’s work in India.

It will have to be interdisciplinary work in which people from social sciences, computer science, economics, policy making, law and enforcement, and non-governmental organizations will have to come together to pool in their efforts.

First step will be data collection. Due to many stakeholders, the data can be collected at multiple points and in different forms. Data could be collected from hotlines, from monitoring of real-time microeconomic factors, and from census and surveys about detailed picture of local society, education, economy and employment.

More than 80% of data science is hard work involved in collecting data and cleaning it. The data will be in different formats, both structured and unstructured. Getting the data is truly a big task in itself. Having lots of real-time good quality clean data can go a long way in making the exercise successful.

The data can be then summarized and visualized. It will portray a complex picture of not only actual incidents and traffic patterns as collected by law and enforcement but of underlying economic, demographic, geographical and social factors.

One can then proceed to statistical analysis of the data to answer many questions:

  • What are the patterns in human trafficking?
  • How can human trafficking be detected?
  • What factors correlate with high incidence of human trafficking?
  • What are potential causes?
  • What law and enforcement techniques are most effective?
  • What is the profile of perpetrators? How do they operate?
  • What is demographic profile of affected areas?
  • What is the profile of victims?
  • How can people in affected areas be educated to combat the problem?
  • What are the sources and destinations of human trafficking at regional, national and international levels?
  • Which programs for victim rehabilitation are most effective?

Here role of statistics and data science is to provide technological tools. These tools come in form of distributed data collection, database software, visualization software, geographical mapping software and statistical techniques.

Backed by data science and deep understanding of ground realities, one will be able to conquer this social evil which plagues humanity. My hope is that such effort will lead to application of data science for social good in many other projects.

Deep Learning brainstorming at a Lucknow (India) school

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I recently got opportunity to give talks at two very different places in India. One is the Indian Institute of Technology (IIT), Kanpur, one of elite technical institutes in India with stellar alumni. I spoke on Computer Vision, Machine Learning and Deep Learning, highlighting how my own career has been intertwined with progress in these fields. As expected, audience was highly learned and technically strong. I have now signed up with IIT Kanpur’s Machine Learning Special Interest Group and am happy to see the group is very active and versed with the latest developments.

This post is however about my experience at a very different place. I was invited to talk at St. Anjani’s Public School in suburb of Lucknow, Uttar Pradesh, India. Students at St. Anjani’s School come from modest backgrounds in this North Indian belt where people are still struggling hard to make ends meet.

When I arrived on the campus, I was greeted by the school manager and the school principal and they took me to one of their class rooms where I spoke on Machine Learning, Deep Learning and Data Science in an interactive format assisted by a power-point presentation. It was a great experience for me as the audience consisted of 10th and 11th grade students.

I was highly impressed by the questions asked by students. How do Internet Search Engines work? What are the conditions in which Artificial Intelligence cannot be used? What steps can students take to learn more about Data Science, Deep Learning and AI? How can one succeed in entrepreneurship in the IT sector?

Students came up with ideas for applications where data science and machine learning can be used which were at par with those being considered and funded in Silicon Valley. Here were some of children’s suggestions: smart home, ensuring safety of children using robotic babysitters, applications of deep learning in health care, smart governance, remote medicine, and educational apps.

I came back with the following observations:

  • There are smart children everywhere, including the poorest areas of the world. And, all these children harbor in their hearts desire to learn about the cutting edge in sciences and technology.
  • Success depends on opportunities. Not everyone gets opportunities and resources to succeed.

Next day in Indian newspapers, I read articles about the latest trends in technology. As the technology juggernaut of data science, deep learning and AI marches forward in Silicon Valleys of the world, I paused to ask if deserving children around the world will all have opportunities and resources to participate in this effort or if they will get held back because of unfortunate circumstances not in their control. I am very much part of Silicon Valleys of the world, and it is my hope that some of the aspiring students I met will make informed decisions in future when they have to choose their college majors and careers. That also made me reflect on corporate social responsibility programs and how I can be a part of such an initiative to ensure scholarships for these deserving children who will design our future world.