Digitale Infrastrukturen in der Demokratie

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Auflistung Digitale Infrastrukturen in der Demokratie nach Forschungsgruppen "Sicherheit und Transparenz digitaler Prozesse"

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    Artificial muses: Generative Artificial Intelligence Chatbots Have Risen to Human-Level Creativity
    (2023) Haase, Jennifer; Hanel, Paul H. P.
    A widespread view is that Artificial Intelligence cannot be creative. We tested this assumption by comparing human-generated ideas with those generated by six Generative Artificial Intelligence (GAI) chatbots: $alpa.\!ai$, $Copy.\!ai$, ChatGPT (versions 3 and 4), $Studio.\!ai$, and YouChat. Humans and a specifically trained AI independently assessed the quality and quantity of ideas. We found no qualitative difference between AI and human-generated creativity, although there are differences in how ideas are generated. Interestingly, 9.4 percent of humans were more creative than the most creative GAI, GPT-4. Our findings suggest that GAIs are valuable assistants in the creative process. Continued research and development of GAI in creative tasks is crucial to fully understand this technology's potential benefits and drawbacks in shaping the future of creativity. Finally, we discuss the question of whether GAIs are capable of being truly creative.
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    Priming creativity: Doing math reduces creativity and happiness whereas playing short online games enhance them
    (2022) Haase, Jennifer; Hanel, Paul H. P.
    Creative thinking is an indispensable cognitive skill that is becoming increasingly important. In the present research, we tested the impact of games on creativity and emotions in a between-subject online experiment with four conditions (N=658). (1) participants played a simple puzzle game that allowed many solutions (priming divergent thinking); (2) participants played a short game that required one fitting solution (priming convergent thinking); (3) participants performed mental arithmetic; (4) passive control condition. Results show that divergent and convergent creativity were higher after playing games and lower after mental arithmetic. Positive emotions did not function as a mediator, even though they were also heightened after playing the games and lower after mental arithmetic. However, contrary to previous research, we found no direct effect of emotions, creative self-efficacy, and growth- vs. fixed on creative performance. We discuss practical implications for digital learning and application settings.
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    Process model forecasting and change exploration using time series analysis of event sequence data
    (2023) De Smedt, Johannes; Yeshchenko, Anton; Polyvyanyy, Artem; De Weerdt, Jochen; Mendling, Jan
    Process analytics is a collection of data-driven techniques for, among others, making predictions for individual process instances or overall process models. At the instance level, various novel techniques have been recently devised, tackling analytical tasks such as next activity, remaining time, or outcome prediction. However, there is a notable void regarding predictions at the process model level. It is the ambition of this article to fill this gap. More specifically, we develop a technique to forecast the entire process model from historical event data. A forecasted model is a will-be process model representing a probable description of the overall process for a given period in the future. Such a forecast helps, for instance, to anticipate and prepare for the consequences of upcoming process drifts and emerging bottlenecks. Our technique builds on a representation of event data as multiple time series, each capturing the evolution of a behavioural aspect of the process model, such that corresponding time series forecasting techniques can be applied. Our implementation demonstrates the feasibility of process model forecasting using real-world event data. A user study using our Process Change Exploration tool confirms the usefulness and ease of use of the produced process model forecasts.
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    Why, with whom, and how to conduct interdisciplinary research? A review from a researcher’s perspective
    (2024) Vladova, Gergana; Haase, Jennifer; Friesike, Sascha
    Many complex problems and emerging phenomena require joint research efforts across academic disciplines. Interdisciplinary research (IDR) is therefore widely considered a promising approach to knowledge production. At the same time, however, this form of research poses significant challenges for those involved. In this paper, we review the literature on IDR from the perspective of individual researchers engaging in or considering this type of research. We conducted a broad literature review covering the past 35 years of research on IDR. The review is structured along four typical questions that researchers have regarding IDR: “Why bother?” (Reasons for considering IDR); “Is it for me?” (The profile of IDR researchers); “How do I work with ‘them’?” (Obstacles of interdisciplinary collaboration); “What am I getting myself into?” (Challenges for IDR researchers). We analyzed the literature so that we could distill answers to those questions. We conclude our paper by emphasizing the inherent ambiguities of interdisciplinary research and proposing a set of self-reflective questions to help navigate the complexities of this research approach.