Madras believes the increased focus on algorithmic fairness alongside issues of privacy, security and safety, will help make machine learning more applicable to high-stakes applications. "It's raising important questions about the role of an automated system that's making important decisions, and how...
Algorithmic fairnessPublic engagementResponsible research and innovationJusticeDespite the widespread use of automated decision-making (ADM) systems, they are often developed without involving the public or those directly affected, leading to concerns about systematic biases that may perpetuate structural ...
The minitrack addresses topics related to imposing fairness requirements and conditions in algorithmic decision making. With the introduction of regulations such as GDPR and California algorithms used for automatization of human decision-making in areas such as classification, recommendation, ranking, are s...
Assuring fairness of an algorithmic decision making (ADM) system is a challenging task involving different and possibly conflicting views on fairness as expressed by multiple fairness measures. We argue that a combination of the agile development framework Acceptance Test-Driven Development (ATDD) and ...
[46] investigated the perception of fairness in algorithmic decision-making and found that people’s perception of a system’s decision as ‘not fair’ affects the participants’ trust in the system. Shin’s investigations [27,37] showed that perception of fairness had a positive effect on ...
In Int. Conf. Machine Learning 60–69 (PMLR, 2018). Corbett-Davies, S., Pierson, E., Feller, A., Goel, S. & Huq, A. Algorithmic decision making and the cost of fairness. In Proc. 23rd ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining 797–806 (2017). Pleiss, G., ...
On algorithmic fairness, discrimination and disparate impact.fairness.haverford.edu/press.html 当然...
Fairness, Accountability, and Transparency in Machine Learning (FATML)|November 2016 Download BibTex We explore the following question: Is a decision-making program fair, for some useful definition of fairness? First, we describe how several algorithmic ...
llreviewthepracticeofmachinelearninginawaythathighlightsethicalchal-lenges.We’llthendiscussapproachestomitigatetheseproblems.We’veaimedtomakethebookasbroadlyaccessibleaswecould,whilepreservingtechnicalrigorandconfrontingdifficultmoralques-tionsthatariseinalgorithmicdecisionmaking.Thisbookwon’thaveanall-encompassing...
Why the concept of algorithmic fairness is so challenging. These definitions involve different mathematical formulations and underlying philosophies. They also often conflict, highlighting thedifficulty of satisfying all fairness criteriasimultaneously in practice. ...