Leading a Local Chapter Challenge in My Home Country Nepal to Understand the Voices of Women, Youth and Marginalized Groups

Jasna Budhathoki, a computer scientist from Nepal, shares her story of becoming a local chapter lead at Omdena.

Hi Jasna, tell us your story

Originally, I am from Nepal and studied computer science in the United States. I am well aware of the potential that my country provides, so I am always wanting to show the potential that comes from technical talent in my country. Fortunately, one such opportunity came my way this summer. 

At the end of June, I received a LinkedIn message from Omdena’s Marketing Manager about helping their team promote an AI project. After two meetings, I realized how exciting this project was! I not only helped them promote this project in my network but also agreed to work as a Local Chapter Challenge Lead in the team. 

Right off the bat, I took on the task of managing a group of 60 ML/AI Engineers. As a fresh graduate from college who had never worked with a big group of engineers, let alone lead them, this seemed like a massive task. But my passion to use AI for social good is what led me to step out of my comfort zone and take on this role. 

And so it began. Three days later, I attended the Local Chapter Challenge’s kick-off meeting with engineers from all over the world. Then I introduced myself. It was official.

Three weeks later, I am proud of how far my team has come, and how much progress we have been making. The goal of this project is to collect media content to understand and improve the representation of women, youth, and marginalized groups in Nepal.

Tell us a bit more about the work as part of the Local Chapter challenge

In order to collect this massive amount of data from various news media sites, the engineers in my team are using several web scraping techniques. At the end of this challenge, we will be ready with data from various news platforms that have been scraped and ready for running an Omdena AI Innovation Challenge. In the AI Innovation Challenge, engineers from various levels of expertise will develop an AI-assisted scoring model that will help determine the representation of people belonging to different groups in Nepali media.

Only 27 percent of the news subjects are women in Nepali media according to the Global Media Monitoring Project (GMMP) in 2020. This number was as low as 13 percent in 2015 which shows that there continues to be a rise in women’s voices being heard in news media in Nepal (GMMP, 2015). But there is so much more we need to do to make media representation better and understanding how women, youth, and marginalized groups are represented across various media platforms is the first step. 

I am grateful to Mohanad Ayman, Omdena´s CTO, for supporting me as I continue to lead the project. I am also thankful to all the engineers who have worked tirelessly to collect thousands of articles from various news sources. 

I am looking forward to how all the data we have collected in this Local Chapter Challenge will be used in the AI Innovation Challenge to conduct media content analysis with the goal of measuring the diversity of content media content and representation of women, youth, and marginalized groups.