Artificial Intelligence, Historical Materialism, and close enough to a jobless society

Rogerio Silva Mattos ()
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Rogerio Silva Mattos: Universidade Federal de Juiz de Fora

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Abstract: Advancing artificial Intelligence draws most of its power from the artificial neural network, a software technique that has successfully replicated some information processing functions of the human brain and the unconscious mind. Jobs are at risk to disappear because even the tacit knowledge typically used by humans to perform complex tasks is now amenable to computerization. The paper discusses implications of this technology for capitalism and jobs, concluding that a very long run transition to a jobless economy should not be discarded. Rising business models and new collaborative schemes provide clues for how things may unfold. A scenario in which society is close enough to full unemployment is analyzed and strategic paths to tackle the challenges involved are discussed. The analysis follows an eclectic approach, based on the Marxist theory of historical materialism and the job task model created by mainstream economists.

Keywords: artificial intelligence; historical materialism; task model; neural networks; jobless society (search for similar items in EconPapers)
Date: 2019-01-01
New Economics Papers: this item is included in nep-big, nep-cmp, nep-hme and nep-pke
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Published in [Research Report] Universidade Federal de Juiz de Fora. 2019

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