When Full Employment Is No Longer Necessary

Hong-Ming Chen

No zpf5x_v1, SocArXiv from Center for Open Science

Abstract: Artificial intelligence may reduce the economic necessity of some forms of cognitive labour faster than employment and social institutions can reorganize the time, identity and roles that work currently structures. Rather than forecasting mass unemployment, we ask what should be tested if that transition arrives unevenly or abruptly: how people are received after occupational loss, how newly available time becomes genuinely self-directed, whether AI can make heterogeneous, voluntary arrangements administratively feasible without turning personalization into obligation, whether unmet human needs can support voluntary new roles, and what it costs to keep the human last mile human. Employment organizes more than income, so occupational displacement is an institutional problem as well as an economic one. We set out a sequence — receive, stabilize, recover, choose — in which recovery is a legitimate state rather than a delay before activation, and in which voluntary reconnection is one possible exit among many. The central proposition is offered as a hypothesis rather than a finding: full employment may have functioned partly as a technology of standardization, while AI could make heterogeneity administratively affordable. Because the same capacity could also produce a more efficient workfare machine, we propose personalization without compulsory optimization as a governing constraint. AI may make matching cheap without making human contact cheap.

Date: 2026-08-29
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:zpf5x_v1

DOI: 10.31235/osf.io/zpf5x_v1

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