First Spark! Equity Innovation Fellowship Recipient Ready to Change the World

Words hold power and weight – disproportionately impacting Black, Indigenous, and people of color. “People claim that words don’t matter, yet they literally affect the way people are treated,” said Spark! Fellow Shateva Long.

“Racial bias is found all throughout medical textbooks and it is negatively affecting the lives of women of color, especially Black women. Even outside of textbooks, I see this bias and it is impacting the way information is being digested,” added Long.

In the wake of the Black Lives Matter movement – the Boston University computer science sophomore saw an opportunity to help combat bias in literature.

“My classmate was expressing their confusion with the Black Lives Matter movement and claimed that the sources they read had conflicting information. The first thing I thought was, how can I fix this?,” said Long. That’s where B Scanner comes in.

It’s a bias detection tool used to dissect such sources – a clear example of how social justice and technology intersect. Long created B (or Bias) Scanner, with a team of fellow Spark! developers and designers.

“The program is an online tool that scans words and phrases to display potential biases and provide explanations on how the text is biased,” said Long. B Scanner was developed while Long was a Spark! Innovation Fellow, but now a new grant is helping the project reach its full potential.

Long is the first recipient of the $2,000 Spark! Equity Innovation Fellowship. The fellowship is a grant award provided by an anonymous donor in recognition of their parents Khaled and Laila.

“My family loves to travel and meet people. Our significant others are from different parts of the world,” said the donor. “Since we were kids, my parents would recite from the Quran, ‘We have created you all out of a male and a female, and have made you into nations and tribes, so that you might come to know one another.’ Spark! Equity Innovation Fellowship is all about that! Diversity in ideas and diversity in reach!,” said the donor.

The grant supports students working on innovation projects that address issues related to diversity, equity, inclusion, and antiracism.

“My next steps are to conduct more research on how bias is shown through text, and then build a large library of biased words and phrases. After this is done, I can then focus on making a machine learning model using the words and phrases,” said Long.

For more on Long and B Scanner, check out this article from BU Today.