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Amritansh Kwatra & Kenny Peng
Amritansh Kwatra & Kenny Peng

Cornell Tech

When (ET)


"Asynchronous Workflows for Maintaining Hardware" &
"Algorithmic Monoculture: Modeling Risks and Benefits"


Amritansh Kwatra will discuss "Asynchronous Workflows for Maintaining Hardware", and Kenny Peng will present research on "Algorithmic Monoculture: Modeling Risks and Benefits."

"Asynchronous Workflows for Maintaining Hardware"

Hardware is challenging for end-users to troubleshoot, repair, and maintain on their own. As a result, they seek out expert technicians to remedy their issues. This kind of synchronous support is limited by expert availability and is challenging to scale. DLI Doctoral Fellow Amritansh Kwatra will introduce SplatOverflow, a workflow that enables asynchronous maintenance of hardware; allowing experts to assist end-users without the need for live communication. SplatOverflow allows end-users to easily capture the context and specifics of the issue they are facing by demonstrating it in a video, while allowing experts to leverage the detailed CAD model of the hardware to guide end-users to a solution. SplatOverflow achieves this by constructing a shared 3D environment representing the end-user’s workspace, and overlaying the digital artifacts that describe the hardware onto the environment in order to mediate communication between the expert and the end-user. Such an asynchronous workflow not only allows maintenance to scale without the bottleneck of expert availability, but also allows issues to be indexed, retrieved and examined by other end-users to learn from, as is the case in software with platforms such as Github and StackOverflow.

"Algorithmic Monoculture: Modeling Risks and Benefits"

More than half of the 100 largest companies in the U.S. now use HireVue's screening algorithms. What are the risks and (perhaps) benefits of an emerging algorithmic monoculture, where many decision-makers rely on the same algorithm to make consequential decisions? In this talk, DLI Doctoral Fellow Kenny Peng will present findings from a new mathematical model of algorithmic monoculture, challenging some prevailing intuitions. In particular, the model suggests that monoculture can (1) improve outcomes for applicants overall, and (2) level the playing field between applicants who submit differing numbers of applications. I will conclude by suggesting some policy implications.


Amritansh Kwatra is a PhD student in the information science department at Cornell University, based in New York City. He is interested in rapid prototyping, physical computing, and visualization tools that support artists, designers, and researchers to develop and communicate their ideas.

Kenny Peng is a PhD student in computer science at Cornell Tech. He studies interactions between machine learning, algorithmic decision-making, and society. His current work focuses on the use of algorithms in employment and school choice/admissions. He received his undergraduate degree in mathematics at Princeton University, where he especially enjoyed serving as a managing editor for The Daily Princetonian.

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