Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: On the (im)possibility of fairness   What does it mean for an algorithm to be fair? Different papers use different
notions of algorithmic fairness, and although these appear internally
consistent, they also seem mutually incompatible. We present a mathematical
setting in which the distinctions in previous papers can be made formal. In
addition to characterizing the spaces of inputs (the "observed" space) and
outputs (the "decision" space), we introduce the notion of a construct space: a
space that captures unobservable, but meaningful variables for the prediction.
  We show that in order to prove desirable properties of the entire
decision-making process, different mechanisms for fairness require different
assumptions about the nature of the mapping from construct space to decision
space. The results in this paper imply that future treatments of algorithmic
fairness should more explicitly state assumptions about the relationship
between constructs and observations.

21
The categories of this paper are: adap-org
28
The categories of this paper are: alg-geom
24
The categories of this paper are: dg-ga
20
The categories of this paper are: acc-phys
26
The categories of this paper are: bayes-an
37
The categories of this paper are: supr-con
3
The categories of this paper are: physics
11
The categories of this paper are: hep-lat
12
The categories of this paper are: nucl-th
5
The categories of this paper are: gr-qc
6
The categories of this paper are: astro-ph
25
The categories of this paper are: patt-sol
2
The categories of this paper are: math
15
The categories of this paper are: nucl-ex
10
The categories of this paper are: q-bio
30
The categories of this paper are: q-alg