The Syntax of Meaning and the Meaning of Syntax Minimal Computations and Maximal Derivations in a Label-/Phase-Driven Generative Grammar of Radical Minimalism
(2020) : Kosta, Peter
isbn: 978-3-653-06463-6
#division_of_labour #semantics #my_bibtex
Risk society
(1992) : Beck, Ulrich Lash, Scott Wynne...
isbn: 0-8039-8346-8
#division_of_labour #wealth #risk #risk_society #__important #wealth_distribution #modernity #labour #politics #knowledge #my_bibtex
Regulation of Division of Labor in Insect Societies
(1992) : Robinson, Gene E
DOI: https://doi.org/10.1146/annurev.en.37.010192.003225
#insect #entomology #division_of_labour #regulation #society #caste_system #my_bibtex
Risk society
(1992) : Beck, Ulrich Lash, Scott Wynne...
isbn: 0-8039-8346-8
#risk #labour #risk_society #politics #wealth #wealth_distribution #modernity #__important #knowledge #division_of_labour #my_bibtex
The Division of Labor, Coordination Costs, and Knowledge
(1992) : Becker, Gary S Murphy, Kevin M
DOI: https://doi.org/10.2307/2118383
#coordination #economics #organisation #division_of_labour #my_bibtex
Division of Labor, Coordination Costs, and Knowledge*

Abstract. This paper considers specialization and the division of labor. A more extensive division of labor raises productivity because returns to the time spen

OUP Academic
The Division of Labor, Coordination Costs, and Knowledge
(1992) : Becker, Gary S and Murphy, Kevin M
DOI: https://doi.org/10.2307/2118383
#coordination #division_of_labour #economics #organisation
#my_bibtex
Division of Labor, Coordination Costs, and Knowledge*

Abstract. This paper considers specialization and the division of labor. A more extensive division of labor raises productivity because returns to the time spen

OUP Academic
Automation, Ai & Work
(2022) : Laura D. Tyson and John Zysman
DOI: https://doi.org/10.1162/daed_a_01914
#ai #division_of_labour #employment #labour #philosophy #routine
#my_bibtex
Automation, AI & Work

Abstract. We characterize artificial intelligence as “routine-biased technological change on steroids,” adding intelligence to automation tools that substitute for humans in physical tasks and substituting for humans in routine and increasingly nonroutine cognitive tasks. We predict how AI will displace humans from existing tasks while increasing demand for humans in new tasks in both manufacturing and services. We also examine the effects of AI-enabled digital platforms on labor. Our conjecture is that AI will continue, even intensify, automation's adverse effects on labor, including the polarization of employment, stagnant wage growth for middle- and low-skill workers, growing inequality, and a lack of good jobs. Though there likely will be enough jobs to keep pace with the slow growth of the labor supply in the advanced economies, we are skeptical that AI and ongoing automation will support the creation of enough good jobs. We doubt that the anticipated productivity and growth benefits of AI will be widely shared, predicting instead that they will fuel more inequality. Yet we are optimistic that interventions can mitigate or offset AI's adverse effects on labor. Ultimately, how the benefits of intelligent automation tools are realized and shared depends not simply on their technological design but on the design of intelligent policies.

MIT Press