A snapshot of the frontiers of fairness in machine learning
A Chouldechova, A Roth - Communications of the ACM, 2020 - dl.acm.org
A snapshot of the frontiers of fairness in machine learning Page 1 82 COMMUNICATIONS OF
THE ACM | MAY 2020 | VOL. 63 | NO. 5 review articles ILL US TRA TION B Y JUS TIN METZ …
THE ACM | MAY 2020 | VOL. 63 | NO. 5 review articles ILL US TRA TION B Y JUS TIN METZ …
[HTML][HTML] Towards Intelligent-TPACK: An empirical study on teachers' professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education
I Celik - Computers in Human Behavior, 2023 - Elsevier
The affordances of artificial intelligence (AI) have not been totally utilized in education. To
effectively integrate AI into education, teachers' AI-specific technological and pedagogical …
effectively integrate AI into education, teachers' AI-specific technological and pedagogical …
A survey on the fairness of recommender systems
Recommender systems are an essential tool to relieve the information overload challenge
and play an important role in people's daily lives. Since recommendations involve …
and play an important role in people's daily lives. Since recommendations involve …
Mitigating bias in algorithmic hiring: Evaluating claims and practices
There has been rapidly growing interest in the use of algorithms in hiring, especially as a
means to address or mitigate bias. Yet, to date, little is known about how these methods are …
means to address or mitigate bias. Yet, to date, little is known about how these methods are …
Fairness in ranking, part i: Score-based ranking
In the past few years, there has been much work on incorporating fairness requirements into
algorithmic rankers, with contributions coming from the data management, algorithms …
algorithmic rankers, with contributions coming from the data management, algorithms …
Bias in bios: A case study of semantic representation bias in a high-stakes setting
We present a large-scale study of gender bias in occupation classification, a task where the
use of machine learning may lead to negative outcomes on peoples' lives. We analyze the …
use of machine learning may lead to negative outcomes on peoples' lives. We analyze the …
The frontiers of fairness in machine learning
A Chouldechova, A Roth - arXiv preprint arXiv:1810.08810, 2018 - arxiv.org
The last few years have seen an explosion of academic and popular interest in algorithmic
fairness. Despite this interest and the volume and velocity of work that has been produced …
fairness. Despite this interest and the volume and velocity of work that has been produced …
Fairness-aware ranking in search & recommendation systems with application to linkedin talent search
SC Geyik, S Ambler, K Kenthapadi - Proceedings of the 25th acm sigkdd …, 2019 - dl.acm.org
We present a framework for quantifying and mitigating algorithmic bias in mechanisms
designed for ranking individuals, typically used as part of web-scale search and …
designed for ranking individuals, typically used as part of web-scale search and …
Fairness of exposure in rankings
A Singh, T Joachims - Proceedings of the 24th ACM SIGKDD …, 2018 - dl.acm.org
Rankings are ubiquitous in the online world today. As we have transitioned from finding
books in libraries to ranking products, jobs, job applicants, opinions and potential romantic …
books in libraries to ranking products, jobs, job applicants, opinions and potential romantic …