Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Recent automation trends in Portugal: implications on industrial productivity and employment in automotive sector

Version 1 : Received: 8 July 2021 / Approved: 9 July 2021 / Online: 9 July 2021 (12:59:00 CEST)

How to cite: Boavida, N.; Candeias, M. Recent automation trends in Portugal: implications on industrial productivity and employment in automotive sector. Preprints 2021, 2021070219 (doi: 10.20944/preprints202107.0219.v1). Boavida, N.; Candeias, M. Recent automation trends in Portugal: implications on industrial productivity and employment in automotive sector. Preprints 2021, 2021070219 (doi: 10.20944/preprints202107.0219.v1).

Abstract

Artificial Intelligence (AI) is an automation mechanism that runs in a computer system performing tasks that normally require human intelligence, such as visual perception, speech recognition, decision making or translation [1]. Some authors argue that recent developments in AI are leading to a wave of innovation in organizational design and changes to institutionalized norms of the workplace [2]. Techno-optimists even named this present phase the ‘second machine age’, arguing that it now involves the substitution of the human brain (Brynjolfsson and McAfee 2014). Potentially, the ability to apply AI in a generalized way can produce significant technical, economic and social effects in firms. But how many of these AI applications are ready and how far can they be from reaching the manufacturing industry market? The paper will answer the question: what are the implications on industrial productivity and employment in the automotive sector with the recent automation trends in Portugal? We will focus on AI as the most relevant emergent technology to understand the development of automation in areas related to robotics, software, and data communications in Europe (Moniz 2018). R&D investments in industrial processes in general may reflect productivity improvements derived from the increased automation process. Our results will be based on case studies from the automotive and components sector combined with database search by keywords that signal intelligence automation developments and AI applications selected from national R&D projects (on robotics, machine learning, collaborative tools, human-machine interaction, autonomous systems, etc) supported by European structural funds. The implications on industrial productivity and employment will be discussed in relation to automation trends in the automotive sector.

Subject Areas

Artificial Intelligence; automation; productivity; employment; automotive industry

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