Intelligent technologies and productivity spillovers: Evidence from the Fourth Industrial Revolution

Venturini, Francesco

doi:10.1016/j.jebo.2021.12.018

Cited by 39 publications

(7 citation statements)

References 51 publications

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“…Research specifically for the United States seems to suggest, however, that effects of AI are particularly strong in large firms that patent significantly (Alderucci et al, 2020 ). Looking at productivity spillovers, on the other hand, Venturini ( 2022 ) suggests that at least during the early periods of the transition toward automation based on AI and robotics, significant spillovers might have contributed to the observed productivity increases. In other words, despite increases in productivity at both the firm and the sectoral level that were driven by AI and robotization, aggregate apparent labor productivity growth decelerated, suggesting that other factors must have been holding back the possible positive contribution of AI on growth.…”

Section: Understanding the Mechanisms Of The Trilemmamentioning

confidence: 99%

The AI trilemma: Saving the planet without ruining our jobs

Ernst

2022

Front. Artif. Intell.

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Digitalization and artificial intelligence increasingly affect the world of work. Rising risk of massive job losses have sparked technological fears. Limited income and productivity gains concentrated among a few tech companies are fueling inequalities. In addition, the increasing ecological footprint of digital technologies has become the focus of much discussion. This creates a trilemma of rising inequality, low productivity growth and high ecological costs brought by technological progress. How can this trilemma be resolved? Which digital applications should be promoted specifically? And what should policymakers do to address this trilemma? This contribution shows that policymakers should create suitable conditions to fully exploit the potential in the area of network applications (transport, information exchange, supply, provisioning) in order to reap maximum societal benefits that can be widely shared. This requires shifting incentives away from current uses toward those that can, at least partially, address the trilemma. The contribution analyses the scope and limits of current policy instruments in this regard and discusses alternative approaches that are more aligned with the properties of the emerging technological paradigm underlying the digital economy. In particular, it discusses the possibility of institutional innovations required to address the socio-economic challenges resulting from the technological innovations brought about by artificial intelligence.

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Section: Understanding the Mechanisms Of The Trilemmamentioning

confidence: 99%

The AI trilemma: Saving the planet without ruining our jobs

Ernst

2022

Front. Artif. Intell.

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“…As the number of digital natives increases and the range of digital design tools/media expands, the groundwork for a fully digital industrial design process is being laid ( Pauliuk et al, 2022 ; Urgo et al, 2022 ). Using only the perceptual thinking and creativity of industrial designers, or exaggerating the role of quantitative data in the field of emotional cognition, on the other hand ( Venturini, 2022 ), is a more one-sided approach to industrial design ( Xiao and Cheng, 2020 ). Through emotional interaction with the target user, an industrial design service platform can effectively bridge this contradiction ( Schneorson et al, 2019 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Investigate the Influencing Factors of Industrial Design Platform Demand: From the Perspective of Emotional Interaction

Zhang¹,

Yang²,

Tong³

et al. 2022

Front. Psychol.

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With the deep integration of industries brought about by big data technology, users’ design needs are diversifying and individuating. Thanks to big data technology, users’ diverse design needs can be precisely met. Meanwhile, big data can be used to realize emotional interaction for personalized design needs of users, resulting in a better user experience. Using grounded theory to mine user demand text data, this paper investigates the influencing factors of emotional interaction and dynamic resource allocation in the digital design supply chain. The results show that government-driven factors have a direct impact on the demand for industrial design in user emotional interactions. Market factors are the most fundamental in the development of an industrial design service platform, and universities play an important role in this. Furthermore, a lack of market sensitivity stems from a lack of emotional interaction with users, resulting in a schism between industry, university, and research, which has become a major impediment to the development of China’s industrial design industry. This study not only lays the theoretical groundwork for understanding the mechanisms of user emotional interaction on IDSPs, but it also points the way forward for future industrial design service platform development.

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“…Some studies have investigated the impact of technological innovation on TFP from the perspectives of Internet technology, information and communications technology (ICT), and industrial robots (Brynjolfsson & Hitt, 1996;Cette et al, 2021;Kallal et al, 2021) but their conclusions are not uniform. Some scholars believe that technological innovation has improved TFP (Venturini, 2022), while others have concluded the opposite (Jorgenson et al, 2008). With the advent of Industry 4.0, intelligent manufacturing continues to penetrate all aspects of production, and intelligence is bound to have a huge impact on production practices.…”

Section: Introductionmentioning

confidence: 99%

Does Intelligence Improve the Total Factor Productivity of China’s Manufacturing Industry?

Qin

2023

Asian Economics Letters

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This paper empirically tests the impact of intelligence on the total factor productivity of China’s manufacturing industry through a double fixed-effect model. The results show that the current process of intelligentization can significantly improve total factor productivity in China’s manufacturing industry. Specifically, intelligence significantly promotes total factor productivity in the eastern region, but does not significantly impact total factor productivity in central and western regions.

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Intelligent technologies and productivity spillovers: Evidence from the Fourth Industrial Revolution

Cited by 39 publications

References 51 publications

The AI trilemma: Saving the planet without ruining our jobs

The AI trilemma: Saving the planet without ruining our jobs

Investigate the Influencing Factors of Industrial Design Platform Demand: From the Perspective of Emotional Interaction

Does Intelligence Improve the Total Factor Productivity of China’s Manufacturing Industry?

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