Hacking for Inclusion: MIT Students Are Fighting Inequality with Technology

MIT students, professors and alumni are credited with the creation of concepts and inventions as varied as refined oil, the Internet and the Human Genome Project. Now, they’re coming together to craft solutions to combat discrimination and bias.

WOC in Tech / Creative Commons

Students at the MIT Sloan School of Management will embark this weekend on a mission to tackle inequality the best way they know how: via a two-day Hackathon. Participants at the Hack for Inclusion will be challenged to break into groups and design comprehensive, tech-based solutions to social problems—ranging from issues as specific as the isolation of the Black community in the city of Boston and the lack of technology supplementing community approaches to Diabetes prevention to issues as ambient as the role that bias plays in the hiring practices of large corporations and the discrimination that the LGBTQ community faces in the workplace.

The Hack for Inclusion is being organized by two MIT student groups: Breaking The Mold and Hacking Discrimination. Breaking the Mold, started in 2014 by two female MIT Sloan students who aimed to start a discussion about unconscious bias, has since provided a platform for three conferences, four workshops and countless discussions that have educated thousands on how to address stereotypes. Hacking Discrimination is a campus Black Alumni group that has facilitated several Ideathons and Hackathons centered around various issues of racial bias. They were inspired, in part, by a call to action by MIT President Rafael Reif around roadblocks to progress for racial minorities: What are we to do?

These two powerhouses of equity in the MIT community knew exactly what to do. That’s why they combined forces to create the Hack for Inclusion—their biggest endeavor yet. Ms. talked with three Hack for Inclusion organizers about their campaign to combat bias, what participants can expect during this weekend’s event and the unique role tech can play in pushing social progress.

How has BTM evolved from when it was founded to today? What are some of the conferences and workshops it has served/sponsored?

The first BTM conference was in the 2014-2015 academic year; it was started by Elena and Maria, who are two Sloan graduates who graduated in 2015. The first conference was centered around bias in the workplace, specifically around the current structure of separating family and work and how that affects gender equality. Since then, one of the major things that has evolved is that we’re focusing on unconscious bias across all spheres, whether its gender, race, ethnicity, sexual orientation. It’s really been our focus to touch on all of these different challenges, mostly in the workplace but also beyond the workplace.

I would also add that we’re not just focusing on unconscious bias anymore, we’re starting to move into more explicit forms of bias as well. So a lot of the dynamics we’re addressing in the workplace we can call implicit and unconscious, we’re also starting to attack some meatier issues. This year we partnered with the Association of Women in Management to elevate discussions on sexual harassment, which we think goes beyond implicit bias. And we even last year talked about topics such as community policing and police/community of color race relations, which again goes beyond implicit bias into cognitive bias, which has been around for decades if not longer. We’re really trying to amp up our resources to tackle some of these bigger problems as well.

What defines a hackathon? Can you walk me through what happens during one? Does there need to be a specific end result?

A hackathon, in our case, is the idea that we have specific challenges that we decide on beforehand, like for example last year we had “how do we help prevent bias when employers are looking through resumes and see different types of names that signify different ethnic backgrounds.” So that might be the challenge statement, and then we have teams of about eight to 10 students who have a mentor and also a team lead. They will have the time allotted to think through what could be possible solutions.  And we do use designed thinking, which is a certain set of principles about how to address the challenge and how to think about possible solutions. And so they’ll go through this process of breaking down the problem and come up with different solutions and then ultimately they have a prototype of some sort, whether that’s something technological like an app or some other type of solution, and they present that to a team of judges. And we’ll have finalists and winners for whichever prototype was best.

How many participants will be on-site? 

We’re aiming to have 125-175 participants. We are reaching out to all of MIT. It’s important for us to have representation from the Business School, which is where we’re based, but also to other graduate students. It’s important for us to have community members, anyone who’s interested, as well as professionals, anyone in the field who feels like they want to participate. In terms of making sure the teams are diverse, we have these different quotas and we’re doing a lot of outreach right now. We look at interest and how to organize the teams. And the other important piece is we’re going to name team leads, which we’re thinking criteria about who would be best for this team and they get a lot of pre-work on the topics and how to lead the teams to make sure its structured well. We’ll have mentors, who are industry professionals who have specific experience in the specific topic area. Thats another part that goes into the teams.

How did you decide on the challenges?

The way we thought about the challenges is we looked at what we came up last years. This time we partnered with Hacking Discrimination and they were able to bring in some of the topics they were interested in covering. We did have a challenge writing workshop where MIT students drafted challenges based off the topics we discussed. And then we invited anyone at MIT and beyond to discuss the challenge statements that were written to make sure they were devoid of bias, more inclusive, and to see if we maybe needed to shift the direction of some of them.

We tried to make the challenge writing process as inclusive as possible to have a diverse set of eyes look at the challenge. Also, on the day of the Hackathon, I’ve been reaching out to people, mostly in the Boston area, looking at grassroots initiatives that combat bias in various industries and inviting those people to participate as well. We’re also looking for businesses to partner with us on certain challenges, to make sure we have challenges that are coming straight out of a workplace environment.

What are some of the ways that technology can combat discrimination and bias that other fields cannot? What are some of the ways that technology is limited in combating bias?

I have a great example of this that applies to both questions. Machine learning. Machine learning is basically teaching pattern recognition to computers for a given task. At the highest levels of machine learning, you’d train a computer to recognize pictures of dogs by showing it pictures of dogs, saying this is a dog, and doing that thousands of times with pictures that you select. And then you should be able to show it a random picture of a dog and it should be able to recognize it on its own. And within the field of bias and discrimination, specifically within the domain of hiring, machine learning has started to be used to understand what are the accurate predictors of success, what are the accurate indicators for someone who can be promoted. There’s a lot of potential to use machine learning in this space and that’s awesome because we can remove some of the human error and the human biases we have. That’s one area where it can actually mitigate bias.

But the limitation then is that humans are still the ones training these technologies. Often times within machine learning, that has to be set up by an individual or a team of individuals. So in that sense, until we get the people who are training these algorithms and building these computer softwares to be as diverse as possible, there are are still biases in how they are detecting things.

How is tech being used to solve problems of discrimination against women—and how women can contribute to that technology?

There’s one company that was started in Silicon Valley called Project Include, which removes bias from the hiring process for women and for communities of color and particularly for the intersection of women and communities of color.

Tiernan Hebron is a Los Angeles-based activist and writer and an Editorial Intern at Ms. Her work has appeared in LA Magazine, ATTN, Feministing, Galore, Tribe de Mama, LadyClever, Elite Daily and Adolescent. Tiernan is a sexual and reproductive rights peer educator for Amnesty International and manages digital communications for DIGDEEP and the Los Angeles Black Worker Center. You can find her being very opinionated on Instagram.

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