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Legislation and public sentiment throughout the world have promoted fairness metrics, explainability, and interpretability as prescriptions for the responsible development of ethical artificial intelligence systems. Despite the importance…
Conventional automated decision-support systems often prioritize predictive accuracy, overlooking the complexities of real-world settings where stakeholders' preferences may diverge or conflict. This can lead to outcomes that disadvantage…
Today's AI deployments often require significant human involvement and skill in the operational stages of the model lifecycle, including pre-release testing, monitoring, problem diagnosis and model improvements. We present a set of enabling…
As AI systems increasingly shape decision making in creative design contexts, understanding how humans engage with these tools has become a critical challenge for interactive intelligent systems research. This paper contributes a challenge…
Artificial intelligence (AI) is rapidly being integrated into educational contexts, promising personalized support and increased efficiency. However, growing evidence suggests that the uncritical adoption of AI may produce unintended harms…
Artificial Intelligence (AI) is one of the most discussed technologies today. There are many innovative applications such as the diagnosis and treatment of cancer, customer experience, new business, education, contagious diseases…
The increasing deployment of Artificial Intelligence (AI) and other autonomous algorithmic systems presents the world with new systemic risks. While focus often lies on the function of individual algorithms, a critical and underestimated…
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 advent of Generative AI has marked a significant milestone in artificial intelligence, demonstrating remarkable capabilities in generating realistic images, texts, and data patterns. However, these advancements come with heightened…
Agentic Artificial Intelligence (AI) can autonomously pursue long-term goals, make decisions, and execute complex, multi-turn workflows. Unlike traditional generative AI, which responds reactively to prompts, agentic AI proactively…
Tensions between AI Safety (AIS) and AI Ethics (AIE) have increasingly surfaced in AI governance and public debates about AI, leading to what we term the "responsible AI divides". We introduce a model that categorizes four modes of…
Human-AI co-creativity represents a transformative shift in how humans and generative AI tools collaborate in creative processes. This chapter explores the synergies between human ingenuity and AI capabilities across four levels of…
The perception that the convergence of biological engineering and artificial intelligence (AI) could enable increased biorisk has recently drawn attention to the governance of biotechnology and artificial intelligence. The 2023 Executive…
This paper proposes a Right to AI, which asserts that individuals and communities should meaningfully participate in the development and governance of the AI systems that shape their lives. Motivated by the increasing deployment of AI in…
As the possibilities for Artificial Intelligence (AI) have grown, so have concerns regarding its impacts on society and the environment. However, these issues are often raised separately; i.e. carbon footprint analyses of AI models…
Participatory approaches to artificial intelligence (AI) and machine learning (ML) are gaining momentum: the increased attention comes partly with the view that participation opens the gateway to an inclusive, equitable, robust, responsible…
Artificial intelligence (AI) is increasingly reshaping lifelong learning by introducing new possibilities for personalized, flexible, and data-informed educational practices. In the field of adult education, AI has gained particular…
Humanity is progressing towards automated product development, a trend that promises faster creation of better products and thus the acceleration of technological progress. However, increasing reliance on non-human agents for this process…
Contemporary discussions in AI ethics often treat culture as a source of normative divergence that needs to be accommodated, tolerated, or managed due to its resistance to universal standards. This paper offers an alternative vision through…
Disagreements are widespread across the design, evaluation, and alignment pipelines of artificial intelligence (AI) systems. Yet, standard practices in AI development often obscure or eliminate disagreement, resulting in an engineered…