![]() Employment-related variables and characteristics that affect networking competence are analyzed in depth, as is the impact of networking competence on career success and employability-thus laying a foundation for transformation in network organization management, employee relations, and individual career development. ![]() Much attention is put on differentiating it from other types of competence and other network objects, and identifying its behavioral manifestations, as the frequency of such behaviors can be used as a measure of an individual’s networking competence level. Workers’ networking competence is the main theme of this book. The book addresses the vital issue of changes occurring in management and employment, with the growing career individualization, focus on future professional challenges, importance of knowledge workers, and possibilities of functioning in social and organizational networks. Human capital is both a source of competitive advantage and a value that allows individual employees to develop their careers and find satisfaction in their employment. Networks and networking are essential concepts that transform organizational, economic, and social practices. CONTEMPORARY CHALLENGES IN MANAGEMENT AND EMPLOYMENT ORGANIZATIONAL NETWORKS AND NETWORKING COMPETENCE. We conclude by looking forward and setting up several avenues for future research. We discuss how a social network approach allows to capture professional interactions in a more straightforward, visual and fine-grained way and how it can simultaneously capture professional interactions at different levels of analysis (e.g., individuals, teams, units, organizations). Building on exemplary findings of recent studies, it shows that the pattern and quality of social relationships among professionals may significantly enhance our understanding of the ways in which interaction takes place and contributes to learning and development. We reflect on the added value of a social network perspective to workplace learning research. The chapter stresses that how individuals learn and develop in and around the workplace is significantly affected by the way they are tied into a larger web of social connections. In this chapter, we set forward a social network perspective on professional learning and development. Our work contributes to the discourse of Human-Centered XAI by expanding the design space of XAI. ![]() The framework showcases how ST can potentially calibrate trust in AI, improve decision-making, facilitate organizational collective actions, and cultivate holistic explainability. We suggested constitutive design elements of ST and developed a conceptual framework to unpack ST's effect and implications at the technical, decision-making, and organizational level. To explore ST conceptually, we conducted interviews with 29 AI users and practitioners grounded in a speculative design scenario. We take a developmental step towards socially-situated XAI by introducing and exploring Social Transparency (ST), a sociotechnically informed perspective that incorporates the socio-organizational context into explaining AI-mediated decision-making. However, Explainable AI (XAI) approaches have been predominantly algorithm-centered. AI systems are often socio-organizationally embedded. Explanations in human-human interactions are socially-situated. As AI-powered systems increasingly mediate consequential decision-making, their explainability is critical for end-users to take informed and accountable actions.
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