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In my lectures on AI for future MBAs, Executives and Managers at the Frankfurt School, I regularly discuss the expected impact of AI on the economy and on society. This article [1] explores different viewpoints on automation through AI and the potential loss of jobs.
The integration of AI into various sectors of the economy is changing the world of work and sparking a major debate about its consequences. As a mathematician and economist, I approach this topic from two angles: the technical details on the one hand, and the economic impact on employment on the other. The general debate assumes that AI will lead to significant job losses, with discussions now focusing on whether new jobs and demographic changes can compensate for these losses, or whether measures such as an unconditional basic income will be needed. This analysis aims to examine the underlying assumption of inevitable job losses due to AI, using economic research and data to understand the actual impact of AI on employment. This is because, despite some arguments suggesting that AI will lead to significant unemployment due to increased productivity, empirical data since the 1970s shows a steady decline in productivity growth rates, which contradicts these arguments.
The article “How Will AI Change Work? Here Are 5 Schools of Thought”2] examines different perspectives on the future impact of artificial intelligence (AI) on the world of work. The report is divided into five different schools of thought on the role of AI in the change of jobs, productivity and economic growth:
– Erik Brynjolfsson and Andrew McAfee are technology optimists who believe that AI can help economic growth and improve living standards.
– Martin Ford takes a dystopian view, warning of widespread unemployment due to AI.
– David Autor offers a more nuanced view, suggesting that automation will create new job opportunities.
– Carl Benedikt Frey and Michael A. Osborne believe that a significant proportion of jobs will be automated, but also see the possibility of new job opportunities.
– Daron Acemoglu and Pascual Restrepo argue that automation can have both positive and negative effects, depending on adjustments in the economy and society.
Writers such as Nick Srnicek and Alex Williams, Aaron Benanav, Aaron Bastani and Peter Frase offer critical perspectives that challenge the capitalist framework within which automation is unfolding and advocate radical alternatives to the current socio-economic model.
– Srnicek and Williams are in favour of a post-work society, supported by automation and a universal basic income.
– For Benanav, the stagnation in job growth has more to do with a global decline in economic growth than with technological progress.
– Bastani dreams of a “fully automated luxury communism” in which technology creates abundance for all.
– Frase speculates on four possible futures, ranging from dystopian to utopian, depending on how society and politics react to automation.
The empirical data since the Second World War shows a complex relationship between technological progress and productivity growth. After an initial boom in the post-war period, there has been a slowdown in productivity growth since the 1970s, despite the introduction of computers and the digital revolution. This phenomenon, often referred to as the “productivity paradox”, raises questions about the direct impact of technology on economic performance.
While some are optimistic about the transformative power of AI on work and the economy, empirical data urges caution. The slowdown in productivity growth observed since the 1970s suggests that technological innovation alone will not be enough to reverse long-term economic trends. The future of work and the impact of automation remain open questions that are influenced by a variety of factors, including technological developments, economic structures and political decisions. An informed debate requires a deep understanding of the complex relationships between technology, economic policy and the employment market. In this rapidly changing landscape, it is essential to consider empirical data while at the same time being open to the opportunities that technological innovation can offer. The challenge is to find a path that promotes both economic growth and social justice by sharing the benefits of automation and AI broadly across society.
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