2nd FATREC Workshop: Responsible Recommendation FATREC2018

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活动简介

The 2nd FATREC Workshop on Responsible Recommendation at RecSys 2018 is a venue for discussing problems of social responsibility in maintaining, evaluating, and studying recommender systems. The importance of the problem are now increasing due to the empowerment of social networking technologies and the change of social environment, such as the enforcement of the EU General Data Protection Regulation. In this workshop, we are welcome research and position papers about ethical, social, and legal issues brought by the development and the use of recommendation. And, we will conduct a discussion for research to contribute socially responsible recommendation.

征稿信息

重要日期

2018-07-16

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征稿范围

FATREC stands for Fairness, Accountability and Transparency in Recommender Systems and aims to draw attention to these issues at ACM RecSys, as has been done in the machine learning community through events such as FAT* conference ( https://fatconference.org/ ). There are many potential aspects of responsibility in recommendation, including (but not limited to):

Responsibility: what does it mean for a recommender system to be socially responsible? How can we assess the social and human impact of recommender systems?
Fairness: what might ‘fairness’ mean in the context of recommendation? How could a recommender be unfair, and how could we measure such unfairness?
Accountability: to whom, and under what standard, should a recommender system be accountable? How can or should it and its operators be held accountable? What harms should such accountability be designed to prevent?
Transparency: what is the value of transparency in recommendation, and how might it be achieved? How might it trade off with other important concerns?
Compliance: how should algorithms and especially recommendation algorithms be designed to adhere the laws or regulations, such as the EU GDPR ( http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32016R0679 ) or the IEEE EAD ( https://ethicsinaction.ieee.org/ )? How should data collection be rethought to meet those new privacy standards ? How to meet the requirements in terms of transparency and explainability of algorithmic decisions.
Safety: how can a recommender system distorts users' opinions? what is required to be resilient to such a distortion? What is a proper treatment of private or sensitive information when making recommendation?

作者指南

We encourage submissions in the above topics. No official proceedings will not be published, because the focus of this workshop is discussion about the directions to build and manage responsible recommender systems. All accepted papers manuscripts will be expected to be posted on arXiv.org by the authors. We allow manuscripts that have already published or that are currently submitted to another venue, so long as arXiv publication is compatible with that venue's requirements; already-published manuscripts should be accompanied by a cover abstract justifying their contribution specifically to FATREC.

Manuscripts must be submitted through an online submission system and will be reviewed by a program committee. The review process is a single-blind, the authors names do not needed to be anonymized. Presentations will be held in an oral or a poster style.