Fairness in recommender systems: research landscape and future directions
Recommender systems can strongly influence which information we see online, eg, on
social media, and thus impact our beliefs, decisions, and actions. At the same time, these …
social media, and thus impact our beliefs, decisions, and actions. At the same time, these …
Fair ranking: a critical review, challenges, and future directions
GK Patro, L Porcaro, L Mitchell, Q Zhang… - Proceedings of the …, 2022 - dl.acm.org
Ranking, recommendation, and retrieval systems are widely used in online platforms and
other societal systems, including e-commerce, media-streaming, admissions, gig platforms …
other societal systems, including e-commerce, media-streaming, admissions, gig platforms …
Towards understanding and mitigating unintended biases in language model-driven conversational recommendation
Abstract Conversational Recommendation Systems (CRSs) have recently started to
leverage pretrained language models (LM) such as BERT for their ability to semantically …
leverage pretrained language models (LM) such as BERT for their ability to semantically …
Algorithmic fairness datasets: the story so far
Data-driven algorithms are studied and deployed in diverse domains to support critical
decisions, directly impacting people's well-being. As a result, a growing community of …
decisions, directly impacting people's well-being. As a result, a growing community of …
Toward fair recommendation in two-sided platforms
Many online platforms today (such as Amazon, Netflix, Spotify, LinkedIn, and AirBnB) can be
thought of as two-sided markets with producers and customers of goods and services …
thought of as two-sided markets with producers and customers of goods and services …
A survey of research on fair recommender systems
Recommender systems can strongly influence which information we see online, eg, on
social media, and thus impact our beliefs, decisions, and actions. At the same time, these …
social media, and thus impact our beliefs, decisions, and actions. At the same time, these …
Tackling documentation debt: a survey on algorithmic fairness datasets
A growing community of researchers has been investigating the equity of algorithms,
advancing the understanding of risks and opportunities of automated decision-making for …
advancing the understanding of risks and opportunities of automated decision-making for …
Fairfoody: Bringing in fairness in food delivery
A Gupta, R Yadav, A Nair, A Chakraborty… - Proceedings of the …, 2022 - ojs.aaai.org
Along with the rapid growth and rise to prominence of food delivery platforms, concerns
have also risen about the terms of employment of the``gig workers''underpinning this growth …
have also risen about the terms of employment of the``gig workers''underpinning this growth …
Fairness in agreement with european values: An interdisciplinary perspective on ai regulation
With increasing digitalization, Artificial Intelligence (AI) is becoming ubiquitous. AI-based
systems to identify, optimize, automate, and scale solutions to complex economic and …
systems to identify, optimize, automate, and scale solutions to complex economic and …
AdaTaskRec: An adaptive task recommendation framework in spatial crowdsourcing
Spatial crowdsourcing is one of the prime movers for the orchestration of location-based
tasks, and task recommendation is a crucial means to help workers discover attractive tasks …
tasks, and task recommendation is a crucial means to help workers discover attractive tasks …