Changes in productivity and labour relations: AI in the automotive sector in Portugal

Citation:
Boavida, Nuno, António Brandão Moniz, and Marta Candeias. "Changes in productivity and labour relations: AI in the automotive sector in Portugal." In International Colloquium GERPISA - Le Réseau International de L’Automobile. online: ENS Paris-Saclay, 2021.

Date Presented:

18/6/2021

Abstract:

New technologies, sustainability policies, protectionism and consumers preferences are pushing for the reorganization of the automotive cluster. (ILO, 2020) Due to recent technological advances derived from the application of AI in the domains of autonomous driving, connectivity, automation, and robotics, the automotive sector is evolving from the traditional, linear, product-oriented value chain to a mobility, service oriented one including new players (ILO, 2020). In fact, in the last years, several digital competences centers are supplying the automotive sector and have been installed in Portugal. These changes are put in place to enhance the product quality, to control costs and to improve productivity. The product shift is done to respond to new regulations on environmental protection, and to enable the control of some emergent market niches.
The paper will contribute to answer the question: what are the expectable changes in productivity due to the introduction of AI in the automotive sector and at new players in the automotive value chain in Portugal? Do they have impacts in traditional labour relations in the sector? Did the COVID-19 had an effect in the acceleration of such changes? Does the employment in the automotive sector changed with the recent automation trends in Portugal? Are there signs of improvement in qualifications with increases in automation? Or can we observe a clear job precarity in the automotive labour market with increased application of cyber physical systems in this sector? We want to develop this framework of questions to collect new data and obtain results that will be based on case studies from the automotive cluster. We will use, as well, secondary statistical analysis. Finally, changes in the productivity and labour market will be discussed in relation to the employment volume and skills in the automotive sector.
In this recently approved national project, we will focus on AI (cyber-physical systems, intelligent automation, robotics, IoT) as the most relevant emergent technology to understand the development of automation in this manufacturing sector (Geels et al., 2012; Moniz 2018). R&D investments in industrial processes in general may reflect productivity improvements derived from the increased automation process, but that may not be the general trend. Our empirical data are based until now on initial case studies from the automotive and components sector combined with database search by keywords that sign intelligence automation developments and AI applications selected from national R&D projects on robotics, machine learning, collaborative tools, human-machine interaction and autonomous systems, supported by European structural funds. The implications on industrial productivity and employment will be discussed in relation to automation trends in the automotive sector.

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