Work

CPFair: Personalized Consumer and Producer Fairness Re-ranking for Recommender Systems

Year: 2022

Type: conference-paper

Abstract: Recently, there has been a rising awareness that when machine learning (ML) algorithms are used to automate choices, they may treat/affect individuals unfairly, with legal, ethical, or economic consequences. Recommender systems are prominent examples of such ML systems that assist users in making high-stakes judgments.

Source: International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)

DOI: 10.1145/3477495.3531959

Authors: Mohammadmehdi Naghiaei, Hossein A. Rahmani, Yashar Deldjoo

Institutions: University of Southern California, University College London, Polytechnic University of Bari

Language: English

Topic: Ethics and Social Impacts of AI

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

SDG: Reduced inequalities

Open Access status: green

OpenAlex ID: W4284677642

FWCI: 26.83

Cites: 26

Cited by: 125

Related to: 10