Automation, skills use and training

By Ljubica Nedelkoska, G. Quintini. 2018

453 citations recorded by the source corpus.

Subfields: Demography, Economics and Econometrics, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/7b49d0d84af531e31c7b643c64426fcce4a608f2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Demography

1. José Hernandez-Orallo
2. Enrique Fernández-Macías
3. Iis P. Tussyadiah

In Economics and Econometrics

1. Silvia Massini
2. Annarosa Pesole
3. Songül Tolan
4. José Hernandez-Orallo
5. Fernando Martínez-Plumed
6. Enrique Fernández-Macías
7. Manuel Jesus Cobo
8. Mónica Santana

In Sociology and Political Science

1. Annarosa Pesole
2. Songül Tolan
3. José Hernandez-Orallo
4. Fernando Martínez-Plumed
5. Enrique Fernández-Macías
6. Manuel Jesus Cobo
7. Mónica Santana
8. Martin Kenney

Citations in the corpus

• Artificial Intelligence as Augmenting Automation: Implications for Employment (2020, background): “The argument is that by making routine tasks “general purpose”, information and communication technology allows better-skilled people to “make more creative and more productive use of it” (Nedelkoska and Quintini, 2018).”
• What is the future of work? A science mapping analysis (2020, background): “Indeed, variations in job composition within industries and differences in how tasks are organised within the same jobs will determine how a particular occupation is more susceptible to automation in some countries than in others (Gonzalez-Vazquez et al., 2019; Nedelkoska & Quintini, 2018).”
• Measuring the Occupational Impact of AI: Tasks, Cognitive Abilities and AI Benchmarks (2020, background): “This paper contributes to the literature on measuring the occupational impact of AI (Frey and Osborne, 2017; Arntz et al., 2016; Nedelkoska and Quintini, 2018), although we distinguish between technological feasibility of AI and the full automation (substitution through machines) of a task.”
• Digital technologies, innovation, and skills: emerging trajectories and challenges (2021, background): “…digital technologies will mainly improve existing jobs or create new ones (Arntz, Gregory, and Zierahn, 2017; Autor and Salomons, 2018; Felten, Raj, and Seamans, 2019); and still others take a more neutral stance, i.e., the effects will be mixed (Das et al., 2020; Nedelkoska and Quintini, 2018).”
• A review of research into automation in tourism: Launching the Annals of Tourism Research Curated Collection on Artificial Intelligence and Robotics in Tourism (2020, background): “…of intelligent automation also comes with risks, including loss of employment; loss of “low-tech” jobs; loss of control due to robot autonomy; and safety, security, and privacy challenges (Boyd & Holton, 2018; Huang & Rust, 2018; Jarrahi, 2018; Kopacek, 2012; Nedelkoska & Quintini, 2018).”