Screentime Airtime Facetime: Practicing Hybridity in the Cultural Field is the final publication of Going Hybrid, an applied research program on the future of hybridity in the cultural field. How could Covid-triggered innovations in digital cultural programming be turned into durable ways of high-level, participatory livecasting? How do you report on hybrid events? And how do you collect the results in a living and accessible archive? This publication gathers the findings of two years of hands-on experiments, introduces the developed prototypes, and gives insight into the research process.Because we believe in critical making, this book is itself a hybrid entity. It was originally a live-streamed online event and later turned into a print and a digital publication – each version a little different than what you would expect of a livestream, website, or print book. We encourage you to playfully explore the various versions of Screentime Airtime Facetime and hope that you will gain joy and insight from the form of this book as much as from its contents.Going Hybrid (2021-2023) was a research project of the Institute of Network Cultures, in collaboration with Willem de Kooning Academy, MU Hybrid Art House, Framer Framed, IMPAKT, Hackers & Designers, The Hmm, Varia, Anna Maria Michael, Ania Molenda, and Maria van der Togt.
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This paper presents a comprehensive study on assisting new AI programmers in making responsible choices while programming. The research focused on developing a process model, incorporating design patterns, and utilizing an IDE-based extension to promote responsible Artificial Intelligence (AI) practices. The experiment evaluated the effectiveness of the process model and extension, specifically examining their impact on the ability to make responsible choices in AI programming. The results revealed that the use of the process model and extension significantly enhanced the programmers' understanding of Responsible AI principles and their ability to apply them in code development. These findings support existing literature highlighting the positive influence of process models and patterns on code development capabilities. The research further confirmed the importance of incorporating Responsible AI values, as asking relevant questions related to these values resulted in responsible AI practices. Furthermore, the study contributes to bridging the gap between theoretical knowledge and practical application by incorporating Responsible AI values into the centre stage of the process model. By doing so, the research not only addresses the existing literature gap, but also ensures the practical implementation of Responsible AI principles.
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In the coming decades, a substantial number of electric vehicle (EV) chargers need to be installed. The Dutch Climate Accord, accordingly, urges for preparation of regional-scale spatial programs with focus on transport infrastructure for three major metropolitan regions among them Amsterdam Metropolitan Area (AMA). Spatial allocation of EV chargers could be approached at two different spatial scales. At the metropolitan scale, given the inter-regional flow of cars, the EV chargers of one neighbourhood could serve visitors from other neighbourhoods during days. At the neighbourhood scale, EV chargers need to be allocated as close as possible to electricity substations, and within a walkable distance from the final destination of EV drivers during days and nights, i.e. amenities, jobs, and dwellings. This study aims to bridge the gap in the previous studies, that is dealing with only of the two scales, by conducting a two-phase study on EV infrastructure. At the first phase of the study, the necessary number of new EV chargers in 353 4-digit postcodes of AMA will be calculated. On the basis of the findings of the Phase 1, as a case study, EV chargers will be allocated at the candidate street parking locations in the Amsterdam West borough. The methods of the study are Mixed-integer nonlinear programming, accessibility and street pattern analysis. The study will be conducted on the basis of data of regional scale travel behaviour survey and the location of dwellings, existing chargers, jobs, amenities, and electricity substations.
