For programmers and engineers, the classroom is a great place to learn difficult skills such as programming languages. However, when it comes to soft skills, such as working with non-technical people, the narrow scope of technical majors can hinder student growth.
In early 2021, Daniel Monteiro, a software engineer in JPMorgan Chase’s Software Engineering Program (SEP), was concerned. This program is a two-year training program that helps young engineers make the transition from the classroom to the office. Shortly after joining the bank, I realized that if I wanted to advance my career, I needed to combine mastery of hard skills with a deep understanding of soft skills. At the same time, he worried that he would not have the opportunity to continue honing his difficult skills. This is a serious concern if you want to stay on the cutting edge of your area of expertise.
Fortunately, SEP had options to help strengthen both sides of his skill set. It’s Force for Good.
building relationships
Force for Good is a JPMorgan Chase program that brings teams of 6-8 engineers together with nonprofits for eight months. The team meets with nonprofits to assess their needs and build technology solutions that can be used to advance their mission.
Force for Good is not only a great opportunity to help organizations in need, it is also an opportunity for technicians to connect directly with end users. At Force for Good, engineers meet with clients on a regular basis to understand their needs and decide what to build together.
“This experience helped me learn how to empathize with the needs of our users, which is a key skill needed to build great products,” explains Monteiro.
Get authentic feedback and experience
Monteiro’s first Force for Good project is for the Rural Entrepreneurship and Livelihood Foundation, an Indian nonprofit focused on providing members of rural communities, especially women, with the training they need to start their own businesses. (REAL).
REAL connects with participants through online modules. This is a great tool for communicating with remote participants. Unfortunately, like REAL, it can be difficult to get useful feedback on training modules (like REAL, it’s a must if you want to improve your training modules). For example, the student may not understand the lesson, may not be able to imagine how it could be improved, or may be an introverted student who is reluctant to give clear answers. REAL needed a way to get useful feedback, and Monteiro’s team found machine learning to be the perfect tool to provide it.
Machine learning is a form of artificial intelligence in which computers analyze data, identify patterns, and make educated hypotheses based on that information. In essence, it has little human interaction and “learns” about something before acting on it. Spam filters are an example of machine learning that impacts millions of users every day.
Unfortunately, designing and creating machine learning tools requires time, money, and expertise. Also, like many nonprofits, REAL had limited time and resources to address the issue. That’s where Force for Good comes in. By leveraging machine learning, the team was able to create an emotion recognition system that can get useful feedback from users, even when they can’t provide useful feedback.
“We study the learner’s facial expressions frame by frame. While the camera is on, the learner’s emotions are tracked frame by frame to see if they are happy, sad, confused, or surprised. I see,” says Monteiro.
Of course, participants must agree to be monitored and their cameras must be turned on to participate. At the end of the session, machine learning feedback is sent to the trainer to see how the participant’s emotions changed during the session, especially if the participant was distracted at any point.
By better understanding where students are losing focus or misunderstanding the subject matter, teachers can change the way they deliver materials. REAL can rewrite lessons to improve student comprehension. This allows nonprofits to help more people in less time and make more difference in the world.
REAL’s in-house technical team is still working on the eventual launch of the overall training platform with facial recognition components, so Monteiro has yet to see the fruits of his work in the field, but that Excited about the possibilities. “Helping more people is really great, and I’m looking forward to seeing how that unfolds,” he says.
learn and grow
Technologists’ skills must constantly evolve as technology is constantly changing. Prior to this project, Monteiro had never worked on machine learning at his JP Morgan his Chase, but found machine learning to be an in-demand skill and help him stay on the cutting edge. knew.
On the soft skills side, I made friends within the program and interacted with people I would never have met in any other program. “It’s been very fulfilling, especially considering it’s part of my job. I always wanted to see if I could make a social impact in the world. It allowed me to do my part,” he says. Helping underprivileged people and supporting really great nonprofits like real work. ”He looks forward to working on another of his Force for Good programs in the future.
Monteiro’s interest in improving the world continues long after the project ends. “We spend a lot of time at work and are generally unaware of so many problems that exist in today’s world,” he says. “Force for Good has made me more aware of what’s going on in the world and made me want to find out how I can help.” • Volunteered as an English teacher at Four India, teaching 15-year-old children.
Between the development of technical know-how and new activities to the community, Monteiro is well on his way to becoming a force in his own right for good.
