Fwd: Thesis defense on principled machine learning for high-stakes decisions

[Artur Dubrawski]

Dear Autonians,

Amanda is a friend of the Lab and a coorganizer of our series of NeurIPS
workshops on ML for the Developing World (ML4D).

She will be defending her thesis this Thursday.

The topic is relevant to at least a few of us.

Cheers,
Artur

---------- Forwarded message ---------
From: Amanda Coston <acoston at andrew.cmu.edu>
Date: Mon, Apr 24, 2023, 11:01 AM
Subject: Thesis defense on principled machine learning for high-stakes
decisions
To:


Hi!

Would you be able to attend my thesis (on Zoom) this Thursday at 3:30 pm?
Details below.

Thanks in advance!
Amanda

*Location*
I will be defending virtually over zoom.
Topic: Thesis Defense - Amanda Coston
Time: Apr 27, 2023 03:30 PM Eastern Time (US and Canada)

Zoom Meeting
https://cmu.zoom.us/j/91007768295?pwd=WkRoWmxQckR6MEE0U0Z2YWVuM2loQT09

Meeting ID: 910 0776 8295
Passcode: 813156

*Title: *Principled machine learning for societally consequential decision
making

*Abstract: * Machine learning algorithms are widely used for
decision-making in societally high-stakes settings such as child welfare,
criminal justice, healthcare, hiring, and consumer lending. Recent history
has illuminated numerous examples where these algorithms proved unreliable
or inequitable. This thesis proposes a principled approach to the use of
machine learning in societally high-stakes settings, guided by three
pillars: validity, equity, and oversight. We address data problems that
challenge the validity of algorithmic decision support systems by
developing methods for algorithmic risk assessments that account for
selection bias, confounding, and bandit feedback. A central focus of this
research is identifying when algorithms and human decisions
disproportionately impact marginalized groups. Throughout we propose novel
methods that use doubly-robust techniques for bias correction. We present
empirical analysis in the child welfare, criminal justice and consumer
lending domains.

*Committee: *Edward Kennedy, Alexandra Chouldechova, Hoda Heidari, &
Sendhil Mullainathan (U Chicago).

Regards,

Amanda Coston
PhD candidate in Machine Learning and Public Policy
amandacoston.com <http://www.cs.cmu.edu/~acoston/>
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