In this paper, we report on the initial results of an explorative study that aims to investigate the occurrence of cognitive biases when designers use generative AI in the ideation phase of a creative design process. When observing current AI models utilised as creative design tools, potential negative impacts on creativity can be identified, namely deepening already existing cognitive biases but also introducing new ones that might not have been present before. Within our study, we analysed the emergence of several cognitive biases and the possible appearance of a negative synergy when designers use generative AI tools in a creative ideation process. Additionally, we identified a new potential bias that emerges from interacting with AI tools, namely prompt bias.
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Abstract Technology has a major impact on the way nurses work. Data-driven technologies, such as artificial intelligence (AI), have particularly strong potential to support nurses in their work. However, their use also introduces ambiguities. An example of such a technology is AI-driven lifestyle monitoring in long-term care for older adults, based on data collected from ambient sensors in an older adult’s home. Designing and implementing this technology in such an intimate setting requires collaboration with nurses experienced in long-term and older adult care. This viewpoint paper emphasizes the need to incorporate nurses and the nursing perspective into every stage of designing, using, and implementing AI-driven lifestyle monitoring in long-term care settings. It is argued that the technology will not replace nurses, but rather act as a new digital colleague, complementing the humane qualities of nurses and seamlessly integrating into nursing workflows. Several advantages of such a collaboration between nurses and technology are highlighted, as are potential risks such as decreased patient empowerment, depersonalization, lack of transparency, and loss of human contact. Finally, practical suggestions are offered to move forward with integrating the digital colleague
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This study provides a comprehensive analysis of the AI-related skills and roles needed to bridge the AI skills gap in Europe. Using a mixed-method research approach, this study investigated the most in-demand AI expertise areas and roles by surveying 409 organizations in Europe, analyzing 2,563 AI-related job advertisements, and conducting 24 focus group sessions with 145 industry and policy experts. The findings underscore the importance of both general technical skills in AI related to big data, machine learning and deep learning, cyber and data security, large language models as well as AI soft skills such as problemsolving and effective communication. This study sets the foundation for future research directions, emphasizing the importance of upskilling initiatives and the evolving nature of AI skills demand, contributing to an EU-wide strategy for future AI skills development.
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