# Fairness through awareness

@article{Dwork2012FairnessTA, title={Fairness through awareness}, author={C. Dwork and Moritz Hardt and T. Pitassi and O. Reingold and R. Zemel}, journal={ArXiv}, year={2012}, volume={abs/1104.3913} }

We study fairness in classification, where individuals are classified, e.g., admitted to a university, and the goal is to prevent discrimination against individuals based on their membership in some group, while maintaining utility for the classifier (the university). [...] Key Method The main conceptual contribution of this paper is a framework for fair classification comprising (1) a (hypothetical) task-specific metric for determining the degree to which individuals are similar with respect to the… Expand

#### Figures and Topics from this paper

#### Paper Mentions

#### 1,469 Citations

Average Individual Fairness: Algorithms, Generalization and Experiments

- Computer Science, Mathematics
- NeurIPS
- 2019

This work designs an oracle-efficient algorithm for the fair empirical risk minimization task and shows that given sufficiently many samples, the ERM solution generalizes in two directions: both to new individuals, and to new classification tasks, drawn from their corresponding distributions. Expand

Fairness Under Composition

- Computer Science, Mathematics
- ITCS
- 2019

This work identifies pitfalls of naive composition and gives general constructions for fair composition, demonstrating both that classifiers that are fair in isolation do not necessarily compose into fair systems and also that seemingly unfair components may be carefully combined to construct fair systems. Expand

Temporal Aspects of Individual Fairness

- Computer Science, Mathematics
- ArXiv
- 2018

Two definitions of fairness-across-time can have drastically different implications in the setting where the principal needs to learn the utility model: one can achieve a vanishing asymptotic loss in long-run average utility relative to the full-information optimum under the fairness-in-hindsight constraint, whereas this asymPTotic loss can be bounded away from zero under the fair-ACross- time constraint. Expand

Metric Learning for Individual Fairness

- Computer Science, Mathematics
- FORC
- 2020

This work proposes a solution to the problem of approximating a metric for Individual Fairness based on human judgments by assuming that the arbiter can answer a limited set of queries concerning similarity of individuals for a particular task, is free of explicit biases and possesses sufficient domain knowledge to evaluate similarity. Expand

On the Compatibility of Privacy and Fairness

- Computer Science
- UMAP
- 2019

This work investigates whether privacy and fairness can be simultaneously achieved by a single classifier in several different models and gives an efficient algorithm for classification that maintains utility and satisfies both privacy and approximate fairness with high probability. Expand

Eliciting and Enforcing Subjective Individual Fairness

- Computer Science, Mathematics
- ArXiv
- 2019

A framework for fairness elicitation is considered, in which fairness is indirectly specified only via a sample of pairs of individuals who should be treated (approximately) equally on the task, and a provably convergent oracle-efficient algorithm is provided for minimizing error subject to the fairness constraints. Expand

What's Fair about Individual Fairness?

- Computer Science
- AIES
- 2021

It is suggested that individual fairness cannot be a definition of fairness, and instead should be seen as one tool among several for ameliorating algorithmic bias. Expand

Distributional Individual Fairness in Clustering

- Computer Science, Mathematics
- ArXiv
- 2020

This paper adopts the individual fairness notion, which mandates that similar individuals should be treated similarly for clustering problems, and introduces a framework for assigning individuals, embedded in a metric space, to probability distributions over a bounded number of cluster centers. Expand

Individual Fairness in Hindsight

- Computer Science
- EC
- 2019

Fairness-across-time and fairness-in-hindsight are introduced and a new algorithm is designed, Cautious Fair Exploration (CAFE), which satisfies FH and achieves sub-linear regret guarantees for a broad range of settings. Expand

The cost of fairness in binary classification

- Computer Science
- FAT
- 2018

This work relates two existing fairness measures to cost-sensitive risks, and shows that for such costsensitive fairness measures, the optimal classifier is an instance-dependent thresholding of the class-probability function. Expand

#### References

SHOWING 1-10 OF 42 REFERENCES

Mechanism Design via Differential Privacy

- Computer Science
- 48th Annual IEEE Symposium on Foundations of Computer Science (FOCS'07)
- 2007

It is shown that the recent notion of differential privacv, in addition to its own intrinsic virtue, can ensure that participants have limited effect on the outcome of the mechanism, and as a consequence have limited incentive to lie. Expand

On allocations that maximize fairness

- Mathematics, Computer Science
- SODA '08
- 2008

This work considers a problem known as the restricted assignment version of the max-min allocation problem with indivisible goods, and presents a rounding technique that recovers an allocation of value at least Ω(log log log m/log log m) of the optimum. Expand

Incorporating Fairness into Game Theory and Economics

- Economics
- 1993

People like to help those who are helping them and to hurt those who are hurting them. Outcomes rejecting such motivations are called fairness equilibria. Outcomes are mutual-max when each person… Expand

Mechanism design with uncertain inputs: (to err is human, to forgive divine)

- Computer Science, Mathematics
- STOC '11
- 2011

A task of scheduling with a common deadline on a single machine is considered, where players are uncertain about their own job lengths, and hence are incapable of providing truthful reports, and a probabilistic model for uncertainty is shown that even with relatively little uncertainty, no mechanism can guarantee a constant fraction of the maximum welfare. Expand

Differential Privacy

- Computer Science
- ICALP
- 2006

A general impossibility result is given showing that a formalization of Dalenius' goal along the lines of semantic security cannot be achieved, which suggests a new measure, differential privacy, which, intuitively, captures the increased risk to one's privacy incurred by participating in a database. Expand

Calibrating Noise to Sensitivity in Private Data Analysis

- Computer Science
- TCC
- 2006

The study is extended to general functions f, proving that privacy can be preserved by calibrating the standard deviation of the noise according to the sensitivity of the function f, which is the amount that any single argument to f can change its output. Expand

Fairness in scheduling

- Computer Science
- SODA '95
- 1995

This paper explores the issue of fairness in scheduling in settings where there are long-lived processes which should be repeatedly scheduled for various tasks throughout the lifetime of a system, and develops a notion of desired load of a process, which is a function of the tasks it participates in. Expand

Gaydar: Facebook Friendships Expose Sexual Orientation

- Computer Science
- First Monday
- 2009

It is determined that the percentage of a given user's friends who self-identify as gay male is strongly correlated with the sexual orientation of that user, and a logistic regression classifier with strong predictive power is developed. Expand

On the geometry of differential privacy

- Mathematics, Computer Science
- STOC '10
- 2010

The lower bound is strong enough to separate the concept of differential privacy from the notion of approximate differential privacy where an upper bound of O(√{d}/ε) can be achieved. Expand

Decentralizing equality of opportunity and issues concerning the equality of educational opportunity

- Economics
- 2005

Decentralizing Equality of Opportunity and Issues Concerning the Equality of Educational Opportunity Caterina Calsamiglia 2005 This dissertation explores issues concerning local versus global… Expand