Application and Adoption of Emerging Technologies: From Artificial Intelligence to Metaverse

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    Sustainability for Artificial Intelligence Products and Services – Initial How-to for IT Practitioners
    (2023-01-03) Lammert, Dominic; Abdullai, Larry; Betz, Stefanie; Porras, Jari
    Year after year, software engineers celebrate new achievements in the field of AI. At the same time, the question about the impacts of AI on society remains insufficiently answered in terms of a comprehensive technology assessment. This article aims to provide software practitioners with a theoretically grounded and practically tested approach that enables an initial understanding of the potential multidimensional impacts. Subsequently, the results form the basis for discussions on AI software requirements. The approach is based on the Sustainability Awareness Framework (SusAF) and Participatory Design. We conducted three workshops on different AI topics: 1. Autonomous Driving, 2. Music Composition, and 3. Memory Avatars. Based on the results of the workshops we conclude that a two-level approach should be adopted: First, a broad one that includes a diverse selection of stakeholders and overall impact analysis. Then, in a second step, specific approaches narrowing down the stakeholders and focusing on one or few impact areas.
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    Is Artificial Intelligence Attractive? An Empirical Study on User’s Intention to Use AI-Enabled Applications
    (2023-01-03) Zhao, Yu (Gary); El-Gayar, Omar; Tu, Zhiling
    Artificial Intelligence (AI) technologies such as machine learning (ML), natural language processing (NLP), and image recognition, are being incorporated into a wide variety of applications. These AI-enabled applications (AIapps) promise to reshape people's lives. However, despite the proliferation of AI-related research, very little research has focused on how AIapps' unique characteristics affect an individual's adoption behavior. This study examines factors influencing an individual's intention to use AIapps with a proposed research model based on the Task-Technology Fit (TTF) as the underlying theoretical framework. The research model is empirically evaluated using the survey data and SEM method. Theoretically, this study focuses on how the unique characteristics of AIapps influence the task-technology fit and drive the intention of use. The findings are expected to help AIapp developers to evaluate the relative importance of AIapp features which can provide insights into the technology characteristics and identify priorities for further research and development.
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    Accept Me as I Am or See Me Go: A Qualitative Analysis of User Acceptance of Self-Sovereign Identity Applications
    (2023-01-03) Guggenberger, Tobias; Neubauer, Lena; Stramm, Jan; Völter, Fabiane; Zwede, Till
    Self-sovereign identity represents a novel phenomenon aiming to innovate how entities interact with, manage, and prove identity-related information. As with any emerging phenomenon, user acceptance represents a major challenge for the adoption of Self-sovereign identity. Since previous initiatives for digital identity management solutions have not been successfully adopted while at the same time their benefits are largely driven by network effects, user acceptance research is of particular importance for Self-sovereign identity. Therefore, we investigate the user acceptance of Self-sovereign identity by conducting a qualitative interview study. We contribute novel variables to existing theory and offer guidelines for building Self-sovereign identity systems.