[Air-L] "Is Algorithmic Fairness Possible?" 3/23 at 10:30AM Mountain Standard (via Zoom)

[Alexander Halavais]

Please join us for a brief informal talk & discussion by Marcello di Bello
this Wednesday. Register (for free) here:  https://bit.ly/b2c2-di-bello
<https://urldefense.com/v3/__https://bit.ly/b2c2-di-bello__;!!IKRxdwAv5BmarQ!MjFkaAmQSj3Hr45VRclOUGvBDR_6sZqowE1PdoWGMAeS4XaSiPDB3EQOyJOvRbk$>

B2C2 Seminar, Wednesday, March 23, 10:30-11:30 MST
"Is Algorithmic Fairness Possible?"

The literature on algorithmic fairness in computer science is replete with
impossibility theorems. They show that no predictive algorithm can
concurrently achieve different formal criteria of fairness. So any
algorithm is necessarily unfair under one criterion or another. What has
been little appreciated is that these impossibility theorems apply to any
evidence-based decision, whether or not it is algorithmic. I offer a few
examples of this fact, drawing from medical diagnoses and trial
proceedings. So then, are all decisions inherently unfair? To avoid
despair, I will outline a possibility theorem, a way to concurrently
satisfy a restricted family of fairness criteria. This is the best our
decisions can aspire to achieve, and--perhaps--it is all they should aspire
to achieve.

Marcello Di Bello is Assistant Professor of Philosophy in the School of
Historical, Philosophical and Religious Studies at Arizona State
University. His research lies at the intersection of philosophy of law and
epistemology, with a focus on questions about risk and probability, and
evidence and quantitative information.

-- 
// Alexander Halavais (he/him)   @halavais   alex.halavais.net
// Associate Professor of Data & Society         dasprogram.org
// New College, Arizona State University       theprof at asu.edu
<http://asu.edu/>
// Emails generally checked 2x a day.               five.sentenc.es