AI for a Generative Economy: The Role of Intelligent Systems in Sustaining Unalienated Labor, Environment, and Society

Abstract

Extractive economies pull value from a system without restoring it. Unsustainable extraction of ecological value includes over-fishing, clear-cut logging, etc. Extraction of labor value is similarly objectionable: assembly line jobs for example increase the likelihood of cardiovascular disease, depression, suicide and other problems. Extraction of social value--vacuuming up online personal information, commodification of the public sphere, and so on-- constitutes a third form. But all three domains--ecological value, labor value, and social value--can thrive in unalienated forms if we can create a future of work that replaces extraction with generative cycles. AI is a key technology in developing these alternative economic forms. This paper describes some initial experiments with African, African American, and Native American artisans who were willing to experiment with the introduction of computational enhancements to their work. Following our report on these initial results, we map out a vision for how AI could scale up labor that sustains “heritage algorithms”, ecologically situated value chains and other hybrid forms that prevent value alienation while flourishing from its robust circulation.NSF grant DRL-1640014NSF grant DGE-0947980Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/150647/1/FSS-19_paper_64.pdfDescription of FSS-19_paper_64.pdf : Preprint Versio

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