poster

Algorithmic Fairness in Online Information Mediating Systems

Authors:

Giles LaneAuthors Info & Claims

WebSci '17: Proceedings of the 2017 ACM on Web Science Conference

Pages 391 - 392

https://doi.org/10.1145/3091478.3098864

Published: 25 June 2017 Publication History

Get Access

Abstract

This paper explores the challenges around fair information access when the limits of human attention require algorithmic assistance for 'finding the diamond in the coal mountain'. While often demanded by users, the seemingly intuitive concept of fairness has proven to be very difficult to operationalise for implementation in algorithms. Here we present two pilot studies aimed at getting a better understanding of the conceptualisation of algorithmic fairness by users. The first was a multi-stakeholder focus-group discussion, the second a user experiment/questionnaire. Based on our data we arrive at a picture of fairness that is highly dependent on context and informedness of users, and possibly inherently misleading due to the implied projecting of human intentions onto an algorithmic process.

References

[1]

Toniann Pitassi Omer Reingold Cynthia Dwork, Moritz Hardt and Richard Zemel. 2012. Fairness through awareness. In ITCS '12 Proceedings of the 3rd Innovations in Theoretical Computer Science Conference. ITCS, 214--226. https://www.cs.toronto.edu/?Etoni/Papers/awareness.pdf.

Digital Library

Google Scholar

[2]

IEEE 2016. Ethically Aligned Design. A Vision for Prioritizing Human Wellbeing with Artificial Intelligence and Autonomous Systems. Version 1. IEEE. http://standards.ieee.org/develop/indconn/ec/autonomoussystems.html.

Google Scholar

[3]

J. Moeller C. Scheidegger M. Feldman, S. A. Friedler and S. Venkatasubramanian. 2015. Certifying and removing disparate impact. In 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 259--268.

Digital Library

Google Scholar

[4]

Suresh Venkatasubramanian Sorelle A. Friedler, Carlos Scheidegger. On the (im)possibility of fairness. In arXiv:1609.07236.

Google Scholar

[5]

U.S. Executive Office of the President 2016. Big Data: A Report on Algorithmic Systems, Opportunities, and Civil Rights. U.S. Executive Office of the President. https://obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/2016_0504_data_discrimination.pdf.

Google Scholar

Cited By

View all

Petterson ACheng KChandra P(2023)Playing with Power Tools: Design Toolkits and the Framing of EquityProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581490(1-24)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581490
Starke CBaleis JKeller BMarcinkowski F(2022)Fairness perceptions of algorithmic decision-making: A systematic review of the empirical literatureBig Data & Society10.1177/205395172211151899:2Online publication date: 10-Oct-2022
https://doi.org/10.1177/20539517221115189
Krafft PYoung MKatell MLee JNarayan SEpstein MDailey DHerman BTam AGuetler VBintz CRaz DJobe PPutz FRobick BBarghouti B(2021)An Action-Oriented AI Policy Toolkit for Technology Audits by Community Advocates and ActivistsProceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency10.1145/3442188.3445938(772-781)Online publication date: 3-Mar-2021
https://dl.acm.org/doi/10.1145/3442188.3445938
Show More Cited By

Recommendations

Making Algorithmic Systems More Meaningfully Transparent for Users Through Visualisation
DIS '22 Companion: Companion Publication of the 2022 ACM Designing Interactive Systems Conference

Transparency over algorithmic systems is increasingly asked for, though it is unclear how it can be realised in practice. Transparency is largely recognised as helpful – eg. to redress information asymmetries – but not as an end in and of itself. ...
Role of fairness, accountability, and transparency in algorithmic affordance
Abstract
As algorithm-based services increase, social topics such as fairness, transparency, and accountability (FAT) must be addressed. This study conceptualizes such issues and examines how they influence the use and adoption of algorithm ...
Highlights
- Conceptualizes fairness, transparency, and accountability.
- How they influence ...
Mediating the Undercurrents: Using Social Media to Sustain a Social Movement
CHI '16: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems

While studies of social movements have mostly examined prevalent public discourses, undercurrents' the backstage practices consisting of meaning-making processes, narratives, and situated work-have received less attention. Through a qualitative ...

Comments

Information & Contributors

Information

Published In

WebSci '17: Proceedings of the 2017 ACM on Web Science Conference

June 2017

438 pages

ISBN:9781450348966

DOI:10.1145/3091478

Conference Chairs:
Peter Fox
Rensselaer Polytechnic Institute, USA
,
Deborah McGuinness
Rensselaer Polytechnic Institute, USA
,
Lindsay Poirer
Rensselaer Polytechnic Institute, USA
,
Program Chairs:
Paolo Boldi
Universita degli Studi di Milano, Italy
,
Katharina Kinder-Kurlanda
GESIS - Leibniz Institute for the Social Sciences, Germany

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 June 2017

Check for updates

Author Tags

Qualifiers

Poster

Funding Sources

EPSRC

Conference

WebSci '17

Sponsor:

SIGWEB

WebSci '17: ACM Web Science Conference

June 25 - 28, 2017

New York, Troy, USA

Acceptance Rates

WebSci '17 Paper Acceptance Rate 30 of 85 submissions, 35%;

Overall Acceptance Rate 245 of 933 submissions, 26%

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

5
Total Citations
View Citations
175
Total Downloads

Downloads (Last 12 months)10
Downloads (Last 6 weeks)0

Reflects downloads up to 08 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Petterson ACheng KChandra P(2023)Playing with Power Tools: Design Toolkits and the Framing of EquityProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581490(1-24)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581490
Starke CBaleis JKeller BMarcinkowski F(2022)Fairness perceptions of algorithmic decision-making: A systematic review of the empirical literatureBig Data & Society10.1177/205395172211151899:2Online publication date: 10-Oct-2022
https://doi.org/10.1177/20539517221115189
Krafft PYoung MKatell MLee JNarayan SEpstein MDailey DHerman BTam AGuetler VBintz CRaz DJobe PPutz FRobick BBarghouti B(2021)An Action-Oriented AI Policy Toolkit for Technology Audits by Community Advocates and ActivistsProceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency10.1145/3442188.3445938(772-781)Online publication date: 3-Mar-2021
https://dl.acm.org/doi/10.1145/3442188.3445938
Webb HPatel MRovatsos MDavoust ACeppi SKoene ADowthwaite LPortillo VJirotka MCano M(2019)“It would be pretty immoral to choose a random algorithm”Journal of Information, Communication and Ethics in Society10.1108/JICES-11-2018-009217:2(210-228)Online publication date: 13-May-2019
https://doi.org/10.1108/JICES-11-2018-0092
Webb HPatel M(2018)Can video-based qualitative analysis help us understand user-algorithm interaction?Proceedings of the 32nd International BCS Human Computer Interaction Conference10.14236/ewic/HCI2018.141(1-5)Online publication date: 4-Jul-2018
https://dl.acm.org/doi/10.14236/ewic/HCI2018.141

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Cited By

Index Terms

Recommendations

Making Algorithmic Systems More Meaningfully Transparent for Users Through Visualisation

Role of fairness, accountability, and transparency in algorithmic affordance

Mediating the Undercurrents: Using Social Media to Sustain a Social Movement