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The integration of artificial intelligence (AI) and optimization hold substantial promise for improving the efficiency, reliability, and resilience of engineered systems. Due to the networked nature of many engineered systems, ethically…
Generative AI (genAI) tools promise productivity gains, yet miscalibrated trust and usage friction still hinder adoption. Moreover, genAI can be exclusionary, failing to adequately support diverse users. One such aspect of diversity is…
As reliance on AI systems for decision-making grows, it becomes critical to ensure that human users can appropriately balance trust in AI suggestions with their own judgment, especially in high-stakes domains like healthcare. However, human…
Artificial intelligence (AI) is interacting with people at an unprecedented scale, offering new avenues for immense positive impact, but also raising widespread concerns around the potential for individual and societal harm. Today, the…
Generative artificial intelligence systems increasingly participate in research, law, education, media, and governance. Their fluent and adaptive outputs create an experience of collaboration. However, these systems do not bear…
Artificial intelligence (AI) ethics has gained significant momentum, evidenced by the growing body of published literature, policy guidelines, and public discourse. However, the practical implementation and adoption of AI ethics principles…
As Artificial Intelligence (AI) advances toward Artificial General Intelligence (AGI) and eventually Artificial Superintelligence (ASI), it may potentially surpass human control, deviate from human values, and even lead to irreversible…
The growing trend of artificial intelligence (AI) as a solution to social and technical problems reinforces AI Realism -- the belief that AI is an inevitable and natural order. In response, this paper argues that participatory design (PD),…
Artificial intelligence has become a part of the provision of governmental services, from making decisions about benefits to issuing fines for parking violations. However, AI systems rarely live up to the promise of neutral optimisation,…
Using LLMs in healthcare, Computer-Supported Cooperative Work, and Social Computing requires the examination of ethical and social norms to ensure safe incorporation into human life. We conducted a mixed-method study, including an online…
The integration of artificial intelligence (AI) into the industrial sector has not only driven innovation but also expanded the ethical landscape, necessitating a reevaluation of principles governing technology and its applications and…
In an era characterized by the pervasive integration of artificial intelligence into decision-making processes across diverse industries, the demand for trust has never been more pronounced. This thesis embarks on a comprehensive…
A computational ethics framework is essential for AI and autonomous systems operating in complex, real-world environments. Existing approaches often lack the adaptability needed to integrate ethical principles into dynamic and ambiguous…
The increasing integration of artificial intelligence into various domains, including design and creative processes, raises significant ethical questions. While AI ethics is often examined from the perspective of technology developers, less…
The increasing prevalence of Artificial Intelligence (AI) in safety-critical contexts such as air-traffic control leads to systems that are practical and efficient, and to some extent explainable to humans to be trusted and accepted. The…
As Artificial Intelligence (AI) systems exert a growing influence on society, real-life incidents begin to underline the importance of AI Ethics. Though calls for more ethical AI systems have been voiced by scholars and the general public…
This workshop proposal focuses on best practices in UI/UX design for AI applications aimed at children, emphasising safety, engagement, and ethics. It aims to address the challenge of measuring the safety, trustworthiness, and reliability…
The use of dialogue systems as a medium for human-machine interaction is an increasingly prevalent paradigm. A growing number of dialogue systems use conversation strategies that are learned from large datasets. There are well documented…
Mainstream AI ethics, with its reliance on top-down, principle-driven frameworks, fails to account for the situated realities of diverse communities affected by AI (Artificial Intelligence). Critics have argued that AI ethics frequently…
The AI landscape demands a broad set of legal, ethical, and societal considerations to be accounted for in order to develop ethical AI (eAI) solutions which sustain human values and rights. Currently, a variety of guidelines and a handful…