Related papers: Fixing Inclusivity Bugs for Information Processing…
Although some previous research has found ways to find inclusivity bugs (biases in software that introduce inequities), little attention has been paid to how to go about fixing such bugs. Without a process to move from finding to fixing,…
How can software practitioners assess whether their software supports diverse users? Although there are empirical processes that can be used to find "inclusivity bugs" piecemeal, what is often needed is a systematic inspection method to…
While much research has shown the presence of AI's "under-the-hood" biases (e.g., algorithmic, training data, etc.), what about "over-the-hood" inclusivity biases: barriers in user-facing AI products that disproportionately exclude users…
Social coding platforms such as GitHub have become defacto environments for collaborative programming and open source. When these platforms do not support specific cognitive styles, they create barriers to programming for some populations.…
Modern society is diverse, multicultural, and multifaceted. Because of these characteristics, we are currently observing an increase in the debates about equity, diversity, and inclusion in different areas, especially because several groups…
One source of software project challenges and failures is the systematic errors introduced by human cognitive biases. Although extensively explored in cognitive psychology, investigations concerning cognitive biases have only recently…
Motivations: Recent research has emerged on generally how to improve AI product user experiences, but relatively little is known about an AI product's inclusivity. For example, what kinds of users does it support well, and who does it leave…
The increasing use of Machine Learning (ML) software can lead to unfair and unethical decisions, thus fairness bugs in software are becoming a growing concern. Addressing these fairness bugs often involves sacrificing ML performance, such…
Gender diversity in the tech sector is - not yet? - sufficient to create a balanced ratio of men and women. For many women, access to computer science is hampered by socialization-related, social, cultural and structural obstacles. The…
Ensuring equitable access to computing education for all students-including those with autism, dyslexia, or ADHD-is essential to developing a diverse and inclusive workforce. To understand the state of disability research in computing…
Software engineers use code-fluent large language models (LLMs) to help explain unfamiliar code, yet LLM explanations are not adapted to engineers' diverse problem-solving needs. We prompted an LLM to adapt to five problem-solving style…
Deep learning has gained substantial popularity in recent years. Developers mainly rely on libraries and tools to add deep learning capabilities to their software. What kinds of bugs are frequently found in such software? What are the root…
\textbf{Background:} Fairness and diversity are receiving growing attention in software engineering, particularly as AI and machine learning systems increasingly influence decision-making processes. While fairness is often examined at the…
As Machine Learning technologies become increasingly used in contexts that affect citizens, companies as well as researchers need to be confident that their application of these methods will not have unexpected social implications, such as…
Emerging research shows that individual differences in how people use technology sometimes cluster by socioeconomic status (SES) and that when technology is not socioeconomically inclusive, low-SES individuals may abandon it. To understand…
Gender diversity enhances research by bringing diverse perspectives and innovative approaches. It ensures equitable solutions that address the needs of diverse populations. However, gender disparity persists in research where women remain…
Recently, workforce shortage has become a popular issue in information technology (IT). One solution to increasing the workforce supply is to increase the number of female IT professionals. This is because there is gender imbalance in…
Introduction: Digital products increasingly reshape industries, influencing human behavior and decision-making. However, the software development teams developing these systems often lack diversity, which may lead to designs that overlook…
Today, software systems have a significant role in various domains among which are healthcare, entertainment, transport and logistics, and many more. It is only natural that with this increasing dependency on software, the number of…
Machine Learning models have been deployed across many different aspects of society, often in situations that affect social welfare. Although these models offer streamlined solutions to large problems, they may contain biases and treat…