The Politics of Intelligent Automation

The Politics of Intelligent Automation

Abstract Title: The Politics of Intelligent Automation

Labour Law and Economics/ Organization and Management

 

Author: 

Dr Matthew Cole 

Post-Doctoral Research Fellow

Work and Employment Relations Division

Leeds University Business School

 

Recently, there have been a wave of reports and academic publications heralding the “second machine age” (Brynjolfsson and McAfee, 2016), the “rise of the robots” (Ford, 2015), the “fourth industrial revolution” (Schwab, 2017) and other era-defining transformations of work in the digital age (Neufeind et al., 2018). Much of this research relies on a widely-cited study that claims up to 47% of US jobs are at risk of automation (Frey and Osborne, 2017), despite this methodology being widely and heavily criticised (Arntz et al., 2016). A common thread in these approaches is the claim that scale and scope of change will be unprecedented (Boyd and Holton, 2018; Wajcman, 2017). However, present data and historical comparisons to previous waves of automation indicate commonalities and limitations to technological transformation that must be carefully considered, particularly with regard to the political implications of technological substitution (Spencer, 2017).

 

This paper interrogates the idea that the introduction of intelligent machines in different industries represents a qualitative shift in human-machine relations. First, it argues that, based on the political economy of technological changes in production and their social effects, we are in the midst of an industrial revolution driven by intelligent automation or machines that adapt to augment or displace labour based on interactions with their environment. The accuracy level of the top-performing machine intelligences generally exceeds the average accuracy level expected of human intelligence performing the same task (Chui et al., 2018). Such machines facilitate the development of the so-called “intangible economy” (Haskel and Westlake, 2017), which is characterised by low marginal cost of reproduction and the capacity for exponential scaling through consumer connectivity creating low entry barriers for firms. Second, this paper argues that the existing macro-level studies (see Frey and Osborne, 2017) on the effects of intelligent automation fail to consider a number of material and social factors that highlight the political dimensions of intelligent automation. The global reach of digital products and perpetual updating of software catalyse the process of creative destruction, yet also provide for new opportunities for rent capture and exploitation (Soete, 2018). These factors pose a political challenge to the displacement paradigm through which the effects of technological change on labour have traditionally been understood (Acemoglu and Restrepo, 2018). To the extent that intelligent automation is used to capture surplus value (either through more efficiently exploiting workers’ productive labour power or through appropriating it from other productive sectors of the economy), it will lead to outcomes that are generally most favourable to the owners of capital and unfavourable to workers.



References

 

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