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The Future of Work: Augmentation or Stunting?
Stockholms universitet, Samhällsvetenskapliga fakulteten, Statsvetenskapliga institutionen.ORCID-id: 0000-0002-2378-750x
2023 (engelsk)Inngår i: Philosophy & Technology, ISSN 2210-5433, E-ISSN 2210-5441, Vol. 36, nr 2, artikkel-id 36Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The last decade has seen significant improvements in artificial intelligence (AI) technologies, including robotics, machine vision, speech recognition, and text generation. Increasing automation will undoubtedly affect the future of work, and discussions on how the development of AI in the workplace will impact labor markets often include two scenarios: (1) labor replacement and (2) labor enabling. The former involves replacing workers with machines, while the latter assumes that human–machine cooperation can significantly improve worker productivity. In this context, it is often argued that (1) could lead to mass unemployment and that (2) therefore would be more desirable. We argue, however, that the labor-enabling scenario conflates two distinct possibilities. On the one hand, technology can increase productivity while also promoting “the goods of work,” such as the opportunity to pursue excellence, experience a sense of community, and contribute to society (human augmentation). On the other hand, higher productivity can also be achieved in a way that reduces opportunities for the “goods of work” and/or increases “the bads of work,” such as injury, reduced physical and mental health, reduction of autonomy, privacy, and human dignity (human stunting). We outline the differences of these outcomes and discuss the implications for the labor market in the context of contemporaneous discussions on the value of work and human wellbeing.

sted, utgiver, år, opplag, sider
2023. Vol. 36, nr 2, artikkel-id 36
Emneord [en]
The future of work, Automation, Human-AI cooperation, The goods of work, Work at Amazon, The ethics of work, The ethics of technology, Autonomy, Surveillance capitalism
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Identifikatorer
URN: urn:nbn:se:su:diva-233907DOI: 10.1007/s13347-023-00631-wScopus ID: 2-s2.0-85157961490OAI: oai:DiVA.org:su-233907DiVA, id: diva2:1902029
Tilgjengelig fra: 2024-10-01 Laget: 2024-10-01 Sist oppdatert: 2024-10-01bibliografisk kontrollert

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