Over the past forty years, the use of process models in practice has grown extensively. Until twenty years ago, remarkably little was known about the factors that contribute to the human understandability of process models in practice. Since then, research has, indeed, been conducted on this important topic, by e.g. creating guidelines. Unfortunately, the suggested modelling guidelines often fail to achieve the desired effects, because they are not tied to actual experimental findings. The need arises for knowledge on what kind of visualisation of process models is perceived as understandable, in order to improve the understanding of different stakeholders. Therefore the objective of this study is to answer the question: How can process models be visually enhanced so that they facilitate a common understanding by different stakeholders? Consequently, five subresearch questions (SRQ) will be discussed, covering three studies. By combining social psychology and process models we can work towards a more human-centred and empirical-based solution to enhance the understanding of process models by the different stakeholders with visualisation.
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Terms like ‘big data’, ‘data science’, and ‘data visualisation’ have become buzzwords in recent years and are increasingly intertwined with journalism. Data visualisation may further blur the lines between science communication and graphic design. Our study is situated in these overlaps to compare the design of data visualisations in science news stories across four online news media platforms in South Africa and the United States. Our study contributes to an understanding of how well-considered data visualisations are tools for effective storytelling, and offers practical recommendations for using data visualisation in science communication efforts.
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Organisations are increasingly embedding Artificial Intelligence (AI) techniques and tools in their processes. Typical examples are generative AI for images, videos, text, and classification tasks commonly used, for example, in medical applications and industry. One danger of the proliferation of AI systems is the focus on the performance of AI models, neglecting important aspects such as fairness and sustainability. For example, an organisation might be tempted to use a model with better global performance, even if it works poorly for specific vulnerable groups. The same logic can be applied to high-performance models that require a significant amount of energy for training and usage. At the same time, many organisations recognise the need for responsible AI development that balances performance with fairness and sustainability. This KIEM project proposal aims to develop a tool that can be employed by organizations that develop and implement AI systems and aim to do so more responsibly. Through visual aiding and data visualisation, the tool facilitates making these trade-offs. By showing what these values mean in practice, which choices could be made and highlighting the relationship with performance, we aspire to educate users on how the use of different metrics impacts the decisions made by the model and its wider consequences, such as energy consumption or fairness-related harms. This tool is meant to facilitate conversation between developers, product owners and project leaders to assist them in making their choices more explicit and responsible.
"Speak the Future" presents a novel test case at the intersection of scientific innovation and public engagement. Leveraging the power of real-time AI image generation, the project empowers festival participants to verbally describe their visions for a sustainable and regenerative future. These descriptions are instantly transformed into captivating imagery using SDXL Turbo, fostering collective engagement and tangible visualisation of abstract sustainability concepts. This unique interplay of speech recognition, AI, and projection technology breaks new ground in public engagement methods. The project offers valuable insights into public perceptions and aspirations for sustainability, as well as understanding the effectiveness of AI-powered visualisation and regenerative applications of AI. Ultimately, this will serve as a springboard for PhD research that will aim to understand How AI can serve as a vehicle for crafting regenerative futures? By employing real-time AI image generation, the project directly tests its effectiveness in fostering public engagement with sustainable futures. Analysing participant interaction and feedback sheds light on how AI-powered visualisation tools can enhance comprehension and engagement. Furthermore, the project fosters public understanding and appreciation of research. The interactive and accessible nature of "Speak the Future" demystifies the research process, showcasing its relevance and impact on everyday life. Moreover, by directly involving the public in co-creating visual representations of their aspirations, the project builds an emotional connection and sense of ownership, potentially leading to continued engagement and action beyond the festival setting. "Speak the Future" promises to be a groundbreaking initiative, bridging the gap between scientific innovation and public engagement in sustainability discourse. By harnessing the power of AI for collective visualisation, the project not only gathers valuable data for researchers but also empowers the public to envision and work towards a brighter, more sustainable future.
