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Artificial intelligence algorithms have been used to enhance a wide variety of products and services, including assisting human decision making in high-stakes contexts. However, these algorithms are complex and have trade-offs, notably…

Large Language Models (LLMs) are increasingly embedded in academic writing practices. Although numerous studies have explored how researchers employ these tools for scientific writing, their concrete implementation, limitations, and design…

Fair classification is a critical challenge that has gained increasing importance due to international regulations and its growing use in high-stakes decision-making settings. Existing methods often rely on adversarial learning or…

Human lives are increasingly being affected by the outcomes of automated decision-making systems and it is essential for the latter to be, not only accurate, but also fair. The literature of algorithmic fairness has grown considerably over…

The ongoing pandemic has highlighted the importance of reliable and efficient clinical trials in healthcare. Trial sites, where the trials are conducted, are chosen mainly based on feasibility in terms of medical expertise and access to a…

Consequential decisions are increasingly informed by sophisticated data-driven predictive models. However, to consistently learn accurate predictive models, one needs access to ground truth labels. Unfortunately, in practice, labels may…

Humans can learn from very few samples, demonstrating an outstanding generalization ability that learning algorithms are still far from reaching. Currently, the most successful models demand enormous amounts of well-labeled data, which are…

Datasets sourced from people with disabilities and older adults play an important role in innovation, benchmarking, and mitigating bias for both assistive and inclusive AI-infused applications. However, they are scarce. We conduct a…

Making technology design inclusive requires facing multiple challenges in different dimensions: the populations we work with, who we are, what interaction possibilities we consider, and what context we examine. We reflect on these…

Research studies involving human participants present challenges, including strict ethical considerations, participant recruitment, costs, and many human factors. While human-computer interaction researchers are familiar with these…

Artificial intelligence literature suggests that minority and fragile communities in society can be negatively impacted by machine learning algorithms due to inherent biases in the design process, which lead to socially exclusive decisions…

Equal access to digital technologies is critical for education, employment, and social participation. However, mainstream interfaces are visually oriented, creating steep learning curves and frequent obstacles for screen reader users, and…

If public trust is lost in a new technology early in its life cycle it can take much more time for the benefits of that technology to be realised. Eventually tens-of-millions of people will collectively have the power to determine…

Computer-based tests (CBTs) play an important role in the professional career of any person. Universities use CBTs for admissions. Further, many large courses use CBTs for evaluation and grading. Almost all software companies use CBTs to…

Within the relatively busy area of fair machine learning that has been dominated by classification fairness research, fairness in clustering has started to see some recent attention. In this position paper, we assess the existing work in…

Interface design can directly influence trustworthiness of a software. Thereby, it affects users' intention to use a tool. Previous research on user trust has not comprehensively addressed user interface design, though. We lack an…

Social robots, also known as service or assistant robots, have been developed to improve the quality of human life in recent years. Socially assistive robots (SAR) are a special type of social robots that focus on providing support through…

Robotics has been a popular field of research in the past few decades, with much success in industrial applications such as manufacturing and logistics. This success is led by clearly defined use cases and controlled operating environments.…

This thesis addresses the question of how usable openEHR-aware clinical decision support can be designed and developed in order to improve the quality of health care. To answer this research question, several sub-questions were identified…

Numerous studies have examined issues such as sustainable transport and urban inclusion; yet there is a gap about disadvantaged people and the hindrances they encounter in terms of public transportation. This study assesses sustainability…