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Item ranking systems support users in multi-criteria decision-making tasks. Users need to trust rankings and ranking algorithms to reflect user preferences nicely while avoiding systematic errors and biases. However, today only few…
Privacy policies govern how personal data is collected, used, and shared. Yet, in most privacy-policy consent flows, agreement is operationalized as a single click at the end of a long, opaque policy document. Recent privacy-law scholarship…
Nowadays, interactive technologies are used almost everywhere. As a result, designers need to increasingly make them "socially acceptable". Previous work recommends "subtle" forms of interaction to increase social acceptability and avoid…
Understanding the correct API usage sequences is one of the most important tasks for programmers when they work with unfamiliar libraries. However, programmers often encounter obstacles to finding the appropriate information due to either…
Privacy, security, and accessibility, like ethical concerns in mobile applications (a.k.a. apps), commonly subsumed under non-functional requirements, are generally reported by users through app reviews available in app stores. However,…
Explainability and its emerging counterpart contestability have become important normative and design principles for trustworthy AI as they enable users and subjects to understand and challenge AI decisions. However, realizing these…
Question-and-answer platforms such as Stack Overflow are an important way for software developers to share and retrieve knowledge. However, reusing poorly understood code can lead to serious problems, such as bugs or security…
Explainability, i.e. the ability of a system to explain its behavior to users, has become an important quality of software-intensive systems. Recent work has focused on methods for generating explanations for various algorithmic paradigms…
Evaluating developer satisfaction with conversational AI assistants at scale is critical but challenging. User studies provide rich insights, but are unscalable, while large-scale quantitative signals from logs or in-product ratings are…
Context. Code understandability is fundamental. Developers need to understand the code they are modifying clearly. A low understandability can increase the amount of coding effort, and misinterpreting code impacts the entire development…
Users often interpret and select agent skills through their SKILL markdown specifications. To protect users, existing audits mainly focus on malicious or unsafe skills. We study the complementary question of whether specifications help…
The rapid rise of Large Language Models (LLMs) has changed software development, with tools like Copilot, JetBrains AI Assistant, and others boosting developers' productivity. However, developers now spend more time reviewing code than…
Developers spend a large portion of their time and effort on comprehending source code. While many studies have investigated how developers approach these comprehension tasks and what factors influence their success, less is known about how…
Calls for heightened consideration of fairness and accountability in algorithmically-informed public decisions---like taxation, justice, and child protection---are now commonplace. How might designers support such human values? We…
Rules could be an information extraction (IE) default option, compared to ML and LLMs in terms of sustainability, transferability, interpretability, and development burden. We suggest a sustainable and combined use of rules and ML as an IE…
An increasing number of web articles engage the reader with the feeling of being immersed in the data space. However, the exact characteristics of spatial immersion in the context of visual storytelling remain vague. For example, what are…
Background: Research software is crucial for enabling research discoveries and supporting data analysis, simulation, and interpretation across domains. However, evolving requirements, complex inputs, and legacy dependencies hinder the…
Responsible AI principles provide ethical guidelines for developing AI systems, yet their practical implementation in software engineering lacks thorough investigation. Therefore, this study explores the practices and challenges faced by…
To investigate the level of support and awareness developers possess for dealing with sensitive data in the metaverse, we surveyed developers, consulted legal frameworks, and analyzed API documentation in the metaverse. Our preliminary…
Individuals lack oversight over systems that process their data. This can lead to discrimination and hidden biases that are hard to uncover. Recent data protection legislation tries to tackle these issues, but it is inadequate. It does not…