Researches and studies did not investigate in deep the importance to develop T-shaped skills and techniques for aligning human machine learning (Spohrer, Banavar, 2015) and to design more intuitive machine interfaces. Recently, in this direction, we can find some efforts with regards to the introduction of innovative approaches in education programs inspired by the T-Shaped Model (Barile and Saviano 2021; Saviano et al., 2017a; 2017b; Barile et al., 2015; 2015a). Thus, the aim of the paper is to explore the interpretative contribution of the VSA proposal of the T-Shaped Professional (T-SP) representation, to reconceive human-machine interaction in order to understand the characteristics that people must have to interact effectively (Barile et al., 2019; 2021; Bassano et al., 2020; 2021). Given our purpose, we refer to the trans-disciplinary approach based on Service Science (SS) and Viable Systems Approach (VSA) as methodological frameworks for highlighting the VSA contribution to frame the use of the revised T-Shaped Professionals (T-SP) Model – in which vertical expertise is combined with horizontal and cross-sectional knowledge (Maglio & Spohrer, 2008; Demirkan & Spohrer, 2015; Freund 2018; Moghaddam, Demirkan, and Spohrer 2018; Gardner & Maietta 2020) –, in the emerging context of the digital transformation where workforce’s personal and intellectual habits are challenged (Piciocchi et al., 2017; 2018; 2019). The paper could offer interesting insights for debating on the need for an actualized T-SP model that should be characterized by a proactive attitude, creativity and change management orientation. This assumption is coherent with the increasing demand for workers whose social emotional learning skills are crucial and not yet susceptible to computerization (Frey, C.B. and Osborne, 2017). This implies the need to understand why and how each person can access the rapidly growing digital workforce by reconfiguring own professional shape.

T-Shaped Professional (T-SP) Model to support Human-Machine Interaction

Paolo Barile;Clara Bassano
;
Paolo Piciocchi;Marialuisa Saviano;
2023-01-01

Abstract

Researches and studies did not investigate in deep the importance to develop T-shaped skills and techniques for aligning human machine learning (Spohrer, Banavar, 2015) and to design more intuitive machine interfaces. Recently, in this direction, we can find some efforts with regards to the introduction of innovative approaches in education programs inspired by the T-Shaped Model (Barile and Saviano 2021; Saviano et al., 2017a; 2017b; Barile et al., 2015; 2015a). Thus, the aim of the paper is to explore the interpretative contribution of the VSA proposal of the T-Shaped Professional (T-SP) representation, to reconceive human-machine interaction in order to understand the characteristics that people must have to interact effectively (Barile et al., 2019; 2021; Bassano et al., 2020; 2021). Given our purpose, we refer to the trans-disciplinary approach based on Service Science (SS) and Viable Systems Approach (VSA) as methodological frameworks for highlighting the VSA contribution to frame the use of the revised T-Shaped Professionals (T-SP) Model – in which vertical expertise is combined with horizontal and cross-sectional knowledge (Maglio & Spohrer, 2008; Demirkan & Spohrer, 2015; Freund 2018; Moghaddam, Demirkan, and Spohrer 2018; Gardner & Maietta 2020) –, in the emerging context of the digital transformation where workforce’s personal and intellectual habits are challenged (Piciocchi et al., 2017; 2018; 2019). The paper could offer interesting insights for debating on the need for an actualized T-SP model that should be characterized by a proactive attitude, creativity and change management orientation. This assumption is coherent with the increasing demand for workers whose social emotional learning skills are crucial and not yet susceptible to computerization (Frey, C.B. and Osborne, 2017). This implies the need to understand why and how each person can access the rapidly growing digital workforce by reconfiguring own professional shape.
2023
978-1-958651-84-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4837031
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