[Sds-seminars] Wednesday, Feb 26, Berk Ustun on "Designing for the Last Mile in Machine Learning"

[Dan Spielman]

We have two exciting talks this coming week.

Emma Pierson on Monday, and Berk Ustun on Wednesday.

Here's the announcement of Ustun's talk:

S&DS|CS JOINT SEMINAR, BERK USTUNHarvard University
Designing for the Last Mile in Machine Learning
Wednesday, February 26, 20204:00PM to 5:00PM
YINS see map
<http://maps.google.com/?q=17+Hillhouse+Avenue%2C+Rm.+328%2C+New+Haven%2C+CT%2C+06511%2C+us>

17 Hillhouse Avenue, Rm. 328
New Haven, CT 06511
Website <https://www.berkustun.com/>
Information and Abstract:

Machine learning is now a general-purpose technology. In many domains, we
can build models to support important decisions or automate routine tasks.
Yet we may not reap their benefits due to disuse, or even inflict harm due
to misuse. In this talk, I will present methodological advances that
address these “last mile” challenges. First, I will describe a method to
learn simple risk scores that are readily adopted for medical decision
support, and discuss applications to adult ADHD diagnosis and ICU seizure
prediction. Next, I will describe how machine learning models may harm
individuals in consumer-facing applications by violating their right to
autonomy. I will then introduce the notion of “recourse” and formalize
methods to prevent such harms without interfering in model development.

*Bio: *Berk Ustun
<https://nam05.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.berkustun.com%2F&data=02%7C01%7Cdawn.hemstock%40yale.edu%7C8c929108844b42742a5108d7af302e53%7Cdd8cbebb21394df8b4114e3e87abeb5c%7C0%7C0%7C637170493785328756&sdata=znhsnEe%2BSrwNf4aMkLD5YR8Uue7MVPeFEOYkvyG%2BTUo%3D&reserved=0>
is
a postdoc at the Harvard Center for Research on Computation and Society.
His research interests are in machine learning, optimization, and
human-centered design. In particular, he focuses on developing methods to
promote the adoption and responsible use of machine learning in domains
such as medicine, consumer finance, and criminal justice.

Berk has built machine learning systems that are now used by major
healthcare providers for hospital readmissions prediction, ICU seizure
prediction, and adult ADHD screening. His work has been covered by various
media outlets, including NPR and Wired, and has won major awards, including
the INFORMS Informative Applications in Analytics Award in 2016 and 2019,
and the INFORMS Computing Society Best Student Paper.

Berk holds a PhD in Electrical Engineering and Computer Science from MIT,
an MS in Computation for Design and Optimization from MIT, and BS degrees
in Operations Research and Economics from UC Berkeley.

For links to papers, videos, and software, see: https://www.berkustun.com
<https://nam05.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.berkustun.com%2F&data=02%7C01%7Cdawn.hemstock%40yale.edu%7C8c929108844b42742a5108d7af302e53%7Cdd8cbebb21394df8b4114e3e87abeb5c%7C0%7C0%7C637170493785328756&sdata=znhsnEe%2BSrwNf4aMkLD5YR8Uue7MVPeFEOYkvyG%2BTUo%3D&reserved=0>
.
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