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The increasing use of Artificial Intelligence (AI) in critical societal domains has amplified concerns about fairness, particularly regarding unequal treatment across sensitive attributes such as race, gender, and socioeconomic status.…
This study explores perceptions of fairness in algorithmic decision-making among users in Bangladesh through a comprehensive mixed-methods approach. By integrating quantitative survey data with qualitative interview insights, we examine how…
The ethics of artificial intelligence (AI) systems has risen as an imminent concern across scholarly communities. This concern has propagated a great interest in algorithmic fairness. Large research agendas are now devoted to increasing…
Artificial intelligence (AI) is everywhere, with many children having increased exposure to AI technologies in daily life. We aimed to understand middle school girls' (a group often excluded group in tech) perceptions and knowledge gaps…
Critical examinations of AI systems often apply principles such as fairness, justice, accountability, and safety, which is reflected in AI regulations such as the EU AI Act. Are such principles sufficient to promote the design of systems…
Assessing fairness in artificial intelligence (AI) typically involves AI experts who select protected features, fairness metrics, and set fairness thresholds to assess outcome fairness. However, little is known about how stakeholders,…
Benchmarks are seen as the cornerstone for measuring technical progress in Artificial Intelligence (AI) research and have been developed for a variety of tasks ranging from question answering to facial recognition. An increasingly prominent…
This whitepaper offers normative and practical guidance for developers of artificial intelligence (AI) systems to achieve "Trustworthy AI". In it, we present overall ethical requirements and six ethical principles with value-specific…
Artificial Intelligence (AI) applications are being used to predict and assess behaviour in multiple domains, such as criminal justice and consumer finance, which directly affect human well-being. However, if AI is to improve people's…
As generative AI systems are integrated into educational settings, students often encounter AI-generated output while working through learning tasks, either by requesting help or through integrated tools. Trust in AI can influence how…
As Artificial Intelligence (AI) systems become increasingly integrated into various aspects of daily life, concerns about privacy and ethical accountability are gaining prominence. This study explores stakeholder perspectives on privacy in…
How can we build AI systems that can learn any set of individual human values both quickly and safely, avoiding causing harm or violating societal standards for acceptable behavior during the learning process? We explore the effects of…
Generative AI blurs the lines of authorship in computing education, creating uncertainty around how students should attribute AI assistance. To examine these emerging norms, we conducted a factorial vignette study with 94 computer science…
The rapid uptake of generative artificial intelligence (AI) in higher education is reshaping assessment practices and intensifying concerns around academic integrity, fairness, and learning quality. While institutional responses…
Automated decision systems (ADS) have become ubiquitous in many high-stakes domains. Those systems typically involve sophisticated yet opaque artificial intelligence (AI) techniques that seldom allow for full comprehension of their inner…
Decisions made by various Artificial Intelligence (AI) systems greatly influence our day-to-day lives. With the increasing use of AI systems, it becomes crucial to know that they are fair, identify the underlying biases in their…
Grading in large undergraduate STEM courses often yields minimal feedback due to heavy instructional workloads. We present a large-scale empirical study of AI grading on real, handwritten single-variable calculus work from UC Irvine. Using…
This concluding chapter explores how artificial intelligence (AI) is reshaping the purposes, practices, and outcomes of science education, and proposes a human-centered framework for its responsible integration. Drawing on insights from…
Artificial intelligence (AI) has rapidly transformed various sectors, including healthcare, where it holds the potential to revolutionize clinical practice and improve patient outcomes. However, its integration into medical settings brings…
Modern AI systems are reaping the advantage of novel learning methods. With their increasing usage, we are realizing the limitations and shortfalls of these systems. Brittleness to minor adversarial changes in the input data, ability to…