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ICSE 2023
Sun 14 - Sat 20 May 2023 Melbourne, Australia
Thu 18 May 2023 14:00 - 14:15 at Meeting Room 101 - Diversity and inclusion in SE Chair(s): Xiao Liu

Inequitable software is a common problem. Bias may be caused by developers, or even software users. As a society, it is crucial that we understand and identify the causes and implications of software bias from both users and the software itself. To address the problems of inequitable software, it is essential that we inform and motivate the next generation of software developers regarding bias and its adverse impacts. However, research shows that there is a lack of easily adoptable ethics-focused educational material to support this effort. To address the problem of inequitable software, we created an easily adoptable, self-contained experiential activity that is designed to foster student interest in software ethics, with a specific emphasis on AI/ML bias. This activity involves participants selecting fictitious teammates based solely on their appearance. The participant then experiences bias either against themselves or a teammate by the activity’s fictitious AI. The created lab was then utilized in this study involving 173 real-world users (age 18-51+) to better understand user bias. The primary findings of our study include: I) Participants from minority ethnic groups have stronger feeling regarding being impacted by inequitable software/AI, II) Participants with higher interest in AI/ML have a higher belief for the priority of unbiased software, III) Users do not act in an equitable manner, as avatars with ‘dark’ skin color are less likely to be selected, and IV) Participants from different demographic groups exhibit similar behavior bias. The created experiential lab activity may be executed using only a browser and internet connection, and is publicly available on our project website: [hidden double anonymous].

Thu 18 May

Displayed time zone: Hobart change

13:45 - 15:15
Diversity and inclusion in SESEIS - Software Engineering in Society at Meeting Room 101
Chair(s): Xiao Liu School of Information Technology, Deakin University
13:45
15m
Paper
At the Margins: Marginalized Groups' Ethical Concerns about Software
SEIS - Software Engineering in Society
Lauren Olson Vrije Universiteit Amsterdam, Emitzá Guzmán Vrije Universiteit Amsterdam, Florian Kunneman Vrije Universiteit Amsterdam
Pre-print File Attached
14:00
15m
Paper
Do Users Act Equitably? Understanding User Bias Through a Large In-Person Study
SEIS - Software Engineering in Society
Yang Liu Rochester Institute of Technology, Heather Moses Rochester Institute of Technology, Mark Sternefeld Rochester Institute of Technology, Samuel Malachowsky Rochester Institute of Technology, Daniel Krutz Rochester Institute of Technology
14:15
15m
Paper
Developing Software for Diverse Socio-Economic End Users: Lessons Learned from A Case Study of Fisherfolk Communities in Bangladesh
SEIS - Software Engineering in Society
Tanjila Kanij Monash University, Misita Anwar Monash University, Gillian Oliver Monash University, Md Khalid Hossain Monash Universit
14:30
15m
Full-paper
Walking Down the Road to Independent Mobility: An Adaptive Route Training System for the Cognitively Impaired
SEIS - Software Engineering in Society
Konstantin Rink Bielefeld University of Applied Sciences, Tristan Gruschka Bielefeld University of Applied Sciences, Patrick Palsbröker Bielefeld University of Applied Sciences, Marcos Baez Bielefeld University of Applied Sciences, Dominic Becking Bielefeld University of Applied Sciences, Udo Seelmeyer Bielefeld University of Applied Sciences, Gudrun Dobslaw Bielefeld University of Applied Sciences, Patricia Stolz Bielefeld University of Applied Sciences and Arts
14:45
15m
Paper
Diversity Awareness in Software Engineering Participant Research
SEIS - Software Engineering in Society
Riya Dutta Concordia University, Diego Costa Concordia University, Canada, Emad Shihab Concordia Univeristy, Tanja Tajmel Concordia University
Pre-print
15:00
7m
Vision and Emerging Results
Harmful Terms in Computing: Towards Widespread Detection and Correction
SEIS - Software Engineering in Society
Hana Winchester Saint Ursula Academy, Alicia Boyd New York University, Brittany Johnson George Mason University