Recent EngSci graduate Inioluwa Deborah Raji (1T9) is among the leading innovators on the Forbes 30 Under 30 2021 list. She was recognized in the category of Enterprise Technology for her impactful research on racial and gender bias in AI, and for holding to account companies that use biased technology.
Her work, which she began while still an undergraduate student, has made international headlines and has already helped set new for accountability standards within the AI industry.
Raji was recently also named to MIT Technology Review’s Top Innovators Under 35.
Congratulations to recent graduate Anna Deza (EngSci 2T0)! Her fourth year thesis work has been selected as one of 10 finalists for the 2020 INFORMS Undergraduate Operations Research Prize. Deza conducted this research–titled A Multistage Stochastic Integer Programming Approach to Distributed Operating Room Scheduling–under the supervision of Professor Merve Bodur (MIE).
Deza’s gained extensive research experience during her undergraduate studies in EngSci. She completed three summer research placements, including two through the Engineering Science Research Opportunities Program (ESROP): first with Université Paris-Saclay after her first year, and at Technion in Israel after her third year. She is now a PhD student at the University of California at Berkeley, specializing in industrial engineering and operations research.
“EngSci is a program that really fosters undergraduate research,” says Deza. “I’m grateful to the thesis course coordinator, Professor Alan Chong, for some very helpful workshops he provided that contributed to the quality of my work.”
The final competition of research presentations will take place in the second week of November at the virtual INFORMS Annual Meeting. Good luck, Anna!
Deb Raji (Year 4 EngSci + PEY) and researchers at the MIT Media Lab identified a need for stronger evaluation practices to mitigate gender and racial biases of AI products. (Credit: Liz Do)
As artificial intelligence (AI) software becomes more widely used, questions have arisen about how social biases may inadvertently be amplified through it. One area of concern is facial detection and recognition software. Biases in the data sets used to ‘train’ AI software may lead to racial biases in the end products. Since these are sometimes used in law enforcement, this raises civil rights concerns.
Year 4 EngSci student Deb Raji (1T8 PEY) and collaborators at the Massachusetts Institute of Technology (MIT) recently won “best student paper” at the Artificial Intelligence, Ethics, and Society (AIES) Conference in Honolulu, Hawaii, for identifying performance disparities in commonly used facial detection software when used on groups of different genders and skin tones. Using Amazon’s Rekognition software, they found that darker-skinned women were misidentified as men in nearly one-third of cases.
Raji hopes that this work will show companies how to rigorously audit their algorithms to uncover hidden biases. “Deb Raji’s work highlights the critical need to place engineering work within a social context,” says Professor Deepa Kundur, Chair of the Division of Engineering Science. “We’re very proud of Deb’s achievements and look forward to her future contributions to the field.”
Read about Raji’s research here.