FATES 2021 : 3rd Workshop on Fairness, Accountability, Transparency, Ethics and Society on the Web
Call For Papers
CALL FOR PAPERS
FATES on the Web 2021
Third Workshop on Fairness, Accountability, Transparency,
Ethics and Society on the Web
Joint with The Web Conference 2021
19-23 April 2021
About the Workshop
Following the successful editions of FATES in 2019 and 2020, this third edition of the FATES workshop will again promote the discussion around these critical questions and join forces towards a Web that is truly inclusive, transparent and open.
Data is learned from people. Personal data collected from social media and mobile devices, often considered sensitive information, has been extensively used by systems for a number of purposes, including user behavior forecasting, content recommendation and fraud detection. User behavior, in turn, is changing based on the algorithms that users are exposed to. Recent studies have revealed that many machine-learning based systems exhibit biases, including racial and gender bias. This scenario raises new challenges concerning algorithmic fairness and accountability, transparency of machine-learning models, the importance of developing better AI systems on the Web and tools to deal with privacy matters, and ethics on modeling and analyzing online communities, such as social media interactions, mobility data, political engagement networks, healthcare communities, and so on.
The goal of this workshop is to gather researchers and developers from academia, industry, and civil society to present and debate topics of the importance of developing better AI systems on the Web and tools to deal with privacy matters. To achieve this, we will seek contributions that describe research initiatives, projects, results, and design techniques and experiments that are being developed to deal with fairness and accountability, transparency, and ethics on AI and privacy. In this sense, we will encourage submissions in various degrees of progress, such as new results, visions, techniques, innovative application papers, and progress reports.
In this way, we will stimulate an interdisciplinary debate about emerging topics on the Web, creating an open forum for Web researchers, professionals, and industrial practitioners to share evolving knowledge and report ongoing work.
Topics and Themes
Algorithmic fairness and algorithmic bias, particularly on web data
Credibility and reputation in social media
Fairness, accountability, transparency, and ethics in web search and (social) web mining
Fairness-aware recommender systems and diversity in recommendation
Ethics of opinion mining and opinion formation on the web
Ethical models/frameworks around web platforms and data
Investigation of black-box systems, particular web platforms and algorithms
Innovative methods for studying/analyzing the fairness, accountability, transparency and ethics of web platforms
Impact of web platforms and algorithms on employment and the future of work
Transparency and ethics of web-scale data analysis
Transparency, fairness, and ethics of crowd-sourcing
Transparency-aware algorithms for online civic engagement
Web platforms and the public interest
Algorithmic fairness and bias for smart cities
Ethical and privacy aspects in mobility data analysis
Ethical-aware machine learning models
Ethics and legal audits on the use of sensitive data
Evaluation methods for human-centered machine learning
Fairness Metrics with Human Supervision
Fake news, social bots, misinformation, and disinformation on social media
Hate speech in social media
Human-centered research for end-user ML
Human-in-the-loop for privacy-aware machine learning
Humans perceived consequences of surveillance algorithms
Information/knowledge design/visualization for Privacy
Methods and models for Social Computing and Digital Humanities
Models for ensuring transparency and responsibility of government data
Privacy-preserving and fairness-aware machine learning on the web
Search Design for services on the webSocial web mining
Usability challenges of machine learning
User Experience (UX) for Privacy
Design patterns and design research for ML Systems
Transparency and Explainability in ML
All submissions will be peer reviewed and evaluated on the basis of originality, relevance, quality, and technical contribution. Submissions must present original work. Concurrent submissions are not allowed.
The papers accepted as full papers or short papers will be published jointly with The Web Conference proceedings. Papers accepted as discussion papers will ** not ** be published jointly with The Web Conference proceedings.
Authors can submit full papers (up to 10 pages in length), short papers (up to 6 pages in length), and discussion papers (up to 2 pages in length), written in English. The number of pages does not include references. Papers must be submitted at https://easychair.org/conferences/?conf=fates2021, in PDF according to the ACM format published in the ACM guidelines (www.acm.org/publications/proceedings-template), selecting the generic “sigconf” sample.
The PDF files must have all non-standard fonts embedded. PDF files must be double-blind. Submissions containing author identifying information are subject to rejection without review.
Paper abstract deadline EXTENDED*: January 20 2021 * AOE
Paper submission deadline *: January 25, 2021 * AOE
Paper acceptance notification: February 8, 2021 AOE
Paper camera-ready version (firm deadline): March 1, 2021 AOE
FATES on the Web 2021: April 19 or 20, 2021
*Paper registration in the EasyChair web site
****Program Committee Co-Chairs and Organizers
Chiara Renso, ISTI/CNR, Italy
Jeanna Matthews, Clarkson University, USA
Please see the website for the full Program Committee List