May 2022 9

Fairware'22

The International Workshop on Equitable Data & Technology brings together academic researchers, industry researchers, and practitioners interested in exploring ways to build fairer, more equitable, data-driven software.

Co-located with ICSE’22, the FairWare’22 meeting will include keynotes on software fairness form different perspectives. FairWare’22 will also host panel sessions to invite researchers and the audience to engage in discussion.

Since many issues associated with fairness are often sociological in nature, we welcome commentaries from outside of computer science that can shed light on the complex issue of fairness.

CFP in PDF


About FairWare

There are too many recent examples where software has been implicated in the perpetuation of social injustice. For example, facial recognition software used by police historically, still today, mimic the inequities in the criminal justice system. Healthcare software contributes to disparities in access and treat ment. Online search engines perpetuate societal stereotypes. E-commerce uses (and contributes to) differences in treatment and expectations of economic classes.
 

Why is this important?

Society now demands that its software be fairer and more equitable. Governments, companies and professional societies such as the European Union, Microsoft, and the IEEE have white papers discussing requirements for fair and ethical software. While these documents differ in the details, they all agree that ethical software should must be "FAT"; i.e. fair, accountable and transparent and include:
  • Integration with human agency
  • Accountability where conclusions are challenged
  • Transparency of how conclusions are made
  • Oversight on what must change to fix bad conclusions
  • Inclusiveness such that no specific segment of society is especially and unnecessarily privileged or discriminated

Keynote: Centering the Margins: An inquiry into equity, justice, & society

Speaker: Dr. Angela D.R. Smith https://angeladrsmith.com/
Dr. Angela D.R. Smith is an Assistant Professor at the School of Information, University of Texas at Austin. She received her doctoral degree from Northwestern University in Technology & Social Behavior, a joint degree in Communications and Computer Science. Her research is in the field of Human-Computer Interaction, Computer-Supported Cooperative Work, and Information Sciences. Her current research explores how critical and intersectional theoretical lenses can inform an assets-based participatory design of technologies to support historically marginalized groups, such as individuals of color and individuals experiencing homelessness, in pursuing sustainable, emancipatory transformations and socially responsible technology experiences. Through qualitative, participatory design methods, she seeks to co-construct knowledge, conscientization, and design interventions with these populations.


Topics of Interest

  • Socio-technical challenges
    • How to determine the trade-off between making fair(er) systems and other objectives of a system?
    • How do we build equitable software given the inherently unfair social pressures behind it?
  • Algorithmic challenges
    • How to identify bias in AI models?
    • How to explain the source or reason for this bias?
    • How to measure the level of bias in systems?
    • How to mitigate the effect of this bias by changing how models are trained?
    • How to provide support for explanation of automated decisions and redress for stakeholders and other mechanisms for accountability and transparency of deployed systems?

Fairware'22 welcomes papers that:

  • Explore problems of equity in data-driven software
  • Propose and critique ways to improve inclusiveness
  • Define tools and techniques for supporting the development of data-driven solutions
  • Enumerate challenges that need to be addressed to improve data-driven software development


Paper Submission

Papers will be submitted through HotCRP, and will be subjected to double-blind reviews. Submissions must use the official “ACM Primary Article Template” from the ACM proceedings template. LaTeX users should use the sigconf option, as well as the review (to produce line numbers for easy reference by the reviewers) and anonymous (omitting author names) options. In addition, submitted papers must not exceed the 7-page limit, be written in English, must present an original contribution, and must not be published or under review elsewhere.

Two members of the program committee will review each paper and the committee will select the papers for presentation at workshop based on quality, relevance, and the potential for starting meaningful and productive conversations.

Workshop Participation

At least one author of each accepted paper must register for the workshop. Each paper will be presented in a 15-20 minute presentation with follow-up questions and discussion.

Special Issue

Following on from the workshop, there will be an open call for a special journal issue on fair and equitable data and technology. In that special issue, reviewers from this workshop will review extended versions of the FairWare'22 papers. For more details see our journal special issue call for papers.

 

Important Dates

  • Submission: 21 Jan
  • Notification of acceptance: 25 Feb
  • Camera-ready submission: 18 Mar
  • Workshop date: 9 May
  • Submission for follow-up journal special issue: Sept 15, 2022 [details]

Programme Committee

  • Saba Alimadadi, Simon Fraser University
  • Christian Bird, Microsoft Research
  • Alicia Boyd, DePaul University, USA
  • Marc Canellas, Office of the Public Defender for Arlington County and Falls Church
  • Joymallya Chakraborty, NC State University
  • Denae Ford, Microsoft Research
  • Lelia Hampton, MIT
  • Jürgen Cito, TU Wien
  • Siobahn Day Grady, North Carolina Central University
  • Austin Henley, University of Tennessee Knoxville
  • Brittany Johnson, George Mason University, USA
  • Jeanna Matthews, Clarkson University, USA
  • Tim Menzies, NC State University, USA
  • Kevin Moran, George Mason University
  • Mei Nagappan, University of Waterloo
  • Rahul Pandita, GitHub
  • Liliana Pasquale, University College Dublin
  • Gema Rodriguez-Perez, University of British Columbia
  • Joanna C. S. Santos, University of Notre Dame
  • Justin Smith, Lafayette College, USA
  • Leonardo Villalobos-Arias, NC State University, USA

Organizing Committee

  • Brittany Johnson, George Mason University, USA
  • Alicia Boyd, DePaul University, USA
  • Justin Smith, Lafayette College, USA
  • Leonardo Villalobos-Arias, NC State University, USA
  • Tim Menzies, NC State University, USA
  • Jeanna Matthews, Clarkson University, USA

Previous editions