Call for papers UMUAI Special issue on: Fair, Accountable, and Transparent Recommender Systems
USER MODELING AND USER-ADAPTED INTERACTION: The Journal of Personalization Research (UMUAI)
Abstracts due: June 5th, 2019, Paper submission deadline: Aug. 2nd, 2019,
UMUAI Website: http://www.umuai.org, Journal Impact Factor: 2.9
BACKGROUND AND SCOPE
This special issue addresses research on responsible design, maintenance, evaluation, and study of recommender systems. It is a venue for work that has evolved out of recent workshops and conferences (e.g, FairUMAP, FATRec, FATML, FAT*) on fair, accountable, and transparent (FAT) recommender systems. In particular, it addresses what it means for a recommender system to be responsible, and how to assess the social and human impact of recommender systems. The questions addressed under each criterion are seen as follows:
* 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?
TOPICS
* Modelling
* Fairness of user and item models (e.g., low confidence recommendations, disbalanced data, measures of diversity, low confidence recommendations)
* Accountability of user and item models (e.g., accountability by or for different stakeholders, requirements on modeling to enable accountability)
* Transparency of user and item models (e.g., explanatory needs for different user groups, explaining individual and global consumptions patterns)
* Recommendation
* Fairness of recommendations (e.g., trade-offs between criteria, bias for classes of items or users)
* Accountability of recommendations (e.g., mechanisms for reporting/accounting, balancing filtering and completeness)
* Transparency of recommendations (e.g., explanatory visualizations, user control, comparing explanatory aims)
* Methodologies
* Methodologies to assess Fairness (e.g., metrics for balance, diversity, and other social welfare criteria; evaluation simulations; assessing stakeholder specific bias)
* Methodologies to assess Accountability (e.g., metrics and user studies of accountability mechanisms)
* Methodologies to assess Transparency (e.g., metrics and evaluation frameworks for assessing the impact of interface or interaction strategies)
* Impacts
* Impacts of Fairness practices (e.g., balancing needs of different groups of users or stakeholders in recommender systems)
* Impacts of Accountability practices (e.g., mechanisms for reporting data and models or decisions about them)
* Impacts of Transparency practices (e.g., counterfactuals and what-if recommendations)
PAPER SUBMISSION & REVIEW PROCESS
Submissions will be pre-screened for topical fit based on extended abstracts. Extended abstracts (up to three pages in journal format) should be sent to [log in to unmask]<mailto:[log in to unmask]>. Detailed instructions for paper submissions and updates will be posted online.
Deadline for extended abstracts: June 5th, 2019
Notification about extended abstracts: June 19th, 2019
Deadline for full manuscript submission: August 2nd, 2019
Notification 1st cycle: October 14, 2019
Deadline for revised manuscripts: December 12, 2019
Notification 2nd and final cycle: January 17, 2020
Deadline for camera-ready manuscripts: February 28, 2020
GUEST EDITORS/CONTACT
Nava Tintarev, Delft University of Technology, [log in to unmask]<mailto:[log in to unmask]>
Michael D. Ekstrand, Boise State University, [log in to unmask]<mailto:[log in to unmask]>
Robin Burke, University of Colorado, Boulder, [log in to unmask]<mailto:[log in to unmask]>
Julita Vassileva, University of Saskatchewan, [log in to unmask]<mailto:[log in to unmask]>
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