FATES 2020


FATES on the Web 2020

Second Workshop on Fairness, Accountability, Transparency,
Ethics and Society on the Web


DEADLINE extended to January 13th, 2020

Joint with The Web Conference 2020
Taipei, Taiwan
20-24 April 2020

About the Workshop

Following the successful edition of FATES 2019, this edition of the FATES workshop will 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, particularly 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
  • Fairness Warnings
  • 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.

Submission Guidelines

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=fates2020, 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.

Important Dates

Paper submission deadline: EXTENDED January 13, 2020
Paper acceptance notification: February 7th, 2020
Paper camera-ready version (firm deadline): February 17, 2020
FATES on the Web 2020: April 20 or 21, 2020

Program Committee

Aline Paes, Universidade Federal Fluminense, Brazil
Anastasios Giovanidis, LIP6/Sorbonne Univ. (CNRS), France
Ana-Andreea Stoica, Columbia University, USA
Anna Monreale, University of Pisa, Italy
Arkaitz Zubiaga, Queen Mary University of London, UK
Arthi Manohar, Brunel University, UK
Bettina Berendt, Univ. of Leuven, Belgium
Claudio Lucchese, Università Ca’ Foscari Venezia, Italy
Cristina Muntean, ISTI/CNR, Italy
David Millen, IBM T.J. Watson Research, USA
Ida Mele , ISTI/CNR, Italy
Jean Garcia-Gathright, Spotify
Jefferson Silva, Pontifical Catholic University of São Paulo, Brazil
Josep Domingo-Ferrer, Rovira i Virgili University, Catalonia
Lucy Vasserman, Google, USA
Marco Antonio Casanova, Pontifical Catholic University of Rio de Janeiro, Brazil
Marília Guterres Ferreira, UDESC, Brazil
Maria Luiza Machado Campos, Federal University of Rio de Janeiro, Brazil
Michele Melchiori, University of Brescia, Italy
Nisha Talagala, Pyxeda AI, USA
Raffaele Perego, ISTI/CNR, Italy
Roberto Trani, ISTI/CNR, Italy
Toshihiro Kamishima, National Institute of Advanced Industrial Science and Technology (AIST), Japan

Program Committee Co-Chairs and Organizers

Jeanna Matthews, Clarkson University, USA (Organizing Committee Chair)
Lívia Ruback, Federal University of Rio de Janeiro, Brazil
Chiara Renso, ISTI/CNR, Italy
Caroline Burle, Ceweb.br at Brazilian Network Information Center (NIC.br) and W3C Brazil Office, Brazil
Diogo Cortiz, Ceweb.br at Brazilian Network Information Center (NIC.br) and PUC São Paulo, Brazil
Heloisa Candello, IBM Research, Brazil
Daniel Lim, Duke Kunshan University China
Jonice Oliveira, Federal University of Rio de Janeiro, Brazil

You can contact organizers at fates @ isti.cnr.it

FAT* network

FATES is proudly part of the FAT* network

and adheres to the ACM code of conduct:

For further information about the workshop please contact organizers at fates [at] isti.cnr.it

Dissemination Material

Textual CFP


Web site graphics

Marcos Arrais, Federal University of Rio de Janeiro, Brazil