Auflistung nach Schlagwort "human-AI interaction"
1 - 3 von 3
Treffer pro Seite
Sortieroptionen
- WorkshopbeitragAutocompletion as a Basic Interaction Concept for User-Centered AI(Mensch und Computer 2020 - Workshopband, 2020) Lehmann, Florian; Buschek, DanielWith this position paper we propose that autocompletion can be interpreted as a basic interaction concept in the interaction between humans and systems using artificial intelligence (AI). Autocompletion is well known from text input where the system predicts intended user input, e.g. in search engines. In our research on human-AI collaboration we observe parallels to such textual autocompletion but in different application contexts, such as text generation, mock-up generation, and layout solvers. We compare exemplary related work to highlight autocompletion as a reoccurring and reusable interaction concept. We discuss that identifying underlying interaction primitives in user-centered AI can help to inform concrete design solutions for interactions and user interfaces, and could be a starting point for future research in this area.
- KonferenzbeitragConfigurations of human-AI work in agriculture(43. GIL-Jahrestagung, Resiliente Agri-Food-Systeme, 2023) Hüllmann, Joschka Andreas; Precht, Hauke; Wübbe, CarolinAgriculture is making leaps in digitalization and the development of artificial intelligence (AI) systems, e.g., decision support systems, sensors, or autonomous vehicles. However, adoption and widespread use of these technologies remains below expectations with negative consequences for digitally advancing the agricultural industry. Therefore, this study investigates the configurations of human-AI work, in particular, human-AI decision-making. Configurations describe the interactions between workers and intelligent systems, emphasizing the adoption and use of technologies in-situ. This study targets agricultural farms in Germany, collecting qualitative data at small and medium-sized businesses. From this data, the paper examines how configurations of human-AI work emerge and how explanations influence these configurations in the context of agricultural work. Theoretical contributions include a new understanding of how agricultural workers adopt and work with AI to make decisions. Practical contributions include more accessible AI systems, easing transfer into practice, and improving agricultural workers’ interactions with AI.
- ZeitschriftenartikelExamining Autocompletion as a Basic Concept for Interaction with Generative AI(i-com: Vol. 19, No. 3, 2021) Lehmann, Florian; Buschek, DanielAutocompletion is an approach that extends and continues partial user input. We propose to interpret autocompletion as a basic interaction concept in human-AI interaction. We first describe the concept of autocompletion and dissect its user interface and interaction elements, using the well-established textual autocompletion in search engines as an example. We then highlight how these elements reoccur in other application domains, such as code completion, GUI sketching, and layouting. This comparison and transfer highlights an inherent role of such intelligent systems to extend and complete user input, in particular useful for designing interactions with and for generative AI. We reflect on and discuss our conceptual analysis of autocompletion to provide inspiration and a conceptual lens on current challenges in designing for human-AI interaction.