posted by organizer: kamisima || 2337 views || tracked by 3 users: [display]

FATREC 2018 : The 2nd FATREC Workshop on Responsible Recommendation

FacebookTwitterLinkedInGoogle

Link: https://piret.gitlab.io/fatrec2018/
 
When Oct 6, 2018 - Oct 6, 2018
Where Vancouver, Canada
Submission Deadline Jul 23, 2018
Notification Due Aug 13, 2018
Final Version Due Aug 27, 2018
Categories    recommender systems   ethics   machine learning   data mining
 

Call For Papers

The 2nd FATREC Workshop on Responsible Recommendation
=====================================================

The 2nd FATREC Workshop on Responsible Recommendation at [RecSys 2018](https://recsys.acm.org/recsys18/) 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](http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32016R0679).
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.

## Topics of Interest

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?

## Submission Guidelines

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 https://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.

### Position Papers

Position papers addresses one or more of the above themes, or practical issues in building responsible recommendations. These could be both research systems or production systems in industry. The number of pages should be limited to two (2) pages.

### Research Papers

Research papers presents empirical or analytical results related to the social impact of recommender systems or algorithms.
These could be explorations of bias in recommender systems (either live systems or sandboxed algorithms), explainability and transparency of recommender systems, experiments regarding the impact of the recommender on its users or others, etc.
We will construe the topics broadly. The number of pages should be limited from four (4) to six (6) pages.

## Submission

### Paper format

We strongly encourage to format in [ACM sigconf format](https://www.acm.org/publications/proceedings-template) with the subsequent options.

* set the `sigconf` options in `documentclass`
* `\setcopyright{none}`
* a `CCS` class and keywords parts can be omitted

However, we will not limit to this format, and will accept one of the IEEE proceedings format, the NIPS format, and the ICML proceedings format.

### Submission site

* Manuscripts must be submitted electronically in the EasyChair https://easychair.org/conferences/?conf=fatrec2018 .
* Please add your favorite track name, Position or Research, at the first keyword field.

## Important Dates

* 2018-07-16: Paper submission deadline
* 2018-08-13: Author notification
* 2018-08-27: Camera-ready version deadline
* 2018-10-06: Workshop (full day)

TIMEZONE: Anywhere On Earth

Related Resources

MLDM 2019   15th International Conference on Machine Learning and Data Mining MLDM 2019
UMUAI FatRec 2019   UMUAI Special issue on: Fair, Accountable, and Transparent Recommender Systems
ICCV 2019   International Conference on Computer Vision
SAREC 2018   1st Workshop on Scalable and Applicable Recommendation Systems
ICML 2019   36th International Conference on Machine Learning
SIR 2018   CIKM 2018 Workshop on Social Interaction-based Recommendation
ICDMML 2019   【ACM ICPS EI SCOPUS】2019 International Conference on Data Mining and Machine Learning
2nd HBP Ethics WS 2018   2nd HBP Curriculum Workshop Series - RESEARCH, ETHICS AND SOCIETAL IMPACT DUAL USE AND RESPONSIBLE RESEARCH. ETHICAL CHALLENGES
ICDM 2019   19th Industrial Conference on Data Mining ICDM 2019
INRA 2018   CIKM 2018 Workshop: 6th International Workshop on News Recommendation and Analytics