Aspen Tech Policy Hub Demo Day – Needles in Haystacks: Using Tech For Good

July 8, 2020  • Aspen Tech Policy Hub

The growing power of artificial intelligence and machine learning provides many opportunities to augment human-centered decisions and point out discrepancies and/or patterns of discrimination that individuals cannot easily see. How can we harness AI to find the needles in the proverbial haystacks and advance causes for social good?

In this Aspen Tech Policy Hub webinar, our Fellows showcased their projects focused on Needles in Haystacks: Using Tech for Good. Following the presentations of the projects, Rediet Abebe, co-founder of Mechanism Design for Social Good (MD4SG), gave further remarks.

The projects presented were:

Combating Domestic Terrorism: An FBI study on active shooters shows that there were on average three distinct witnesses who observed concerning behaviors about the suspect prior to their attack. Unfortunately, nearly 60 percent of witnesses did not report what they knew, resulting in many missed opportunities to save lives. Anjana Rajan demo’d one way to solve this low reporting rate: through the use of a digital escrow.

Fair Algorithmic Housing Loans: Mortgage lenders increasingly use machine learning algorithms to make loan approval and pricing decisions. While there are some benefits to this automation, how can we ensure fairness among historically marginalized and underbanked populations? Samara Trilling recommends that state lending regulators define a fairness metric for mortgage algorithms and pilot automated fair lending tests.

Our speakers included the following:

Rediet Abebe is co-founder of Mechanism Design for Social Good (MD4SG), an interdisciplinary research center focused on improving access to historically underserved and disadvantaged communities. In addition to co-founding MD4SG, she co-founded Black in AI, a global initiative focused on increasing the presence of Black individuals in the field of AI. Abebe’s research focuses on AI and algorithmic impacts on equity and justice, specifically building and analyzing data-driven techniques to mitigate opportunity inequality. Abebe is currently a Junior Fellow at the Harvard Society of Fellows and an incoming Assistant Professor at UC Berkeley EECS.

Samara Trilling is a software engineer researching machine learning fairness policy. At Sidewalk Labs, Samara builds next-generation city master planning software. Previously, Samara worked on tools to close the digital divide at Google Fiber and to democratize news reporting at Google News. Samara has a degree in computer science from Columbia University with a specialization in artificial intelligence and a concentration in history. Samara loves hiking, collects books on the history of computing, and plans to build a tiny house and tow it around with her electric truck.

Anjana Rajan is a technology entrepreneur with expertise in applying cryptography to social justice issues. Previously, she was the CTO of Callisto, a nonprofit that builds technology to combat sexual assault. Before that, she worked at Palantir Technologies, where she built and deployed products in the Middle East. She was a Knight Scholar at Cornell University’s Engineering School and received her bachelor’s and master’s degrees in Operations Research and Information Engineering. Anjana is also a former elite triathlete who raced for Team USA.

This conversation is part of the Aspen Tech Policy Hub’s Demo Day Video Series. Please visit our website to learn more about our series and RSVP for other events.