Samothrakis, Spyridon (2024) Artificial intelligence and modern planned economies: a discussion on methods and institutions. AI and Society. DOI https://doi.org/10.1007/s00146-023-01826-7
Samothrakis, Spyridon (2024) Artificial intelligence and modern planned economies: a discussion on methods and institutions. AI and Society. DOI https://doi.org/10.1007/s00146-023-01826-7
Samothrakis, Spyridon (2024) Artificial intelligence and modern planned economies: a discussion on methods and institutions. AI and Society. DOI https://doi.org/10.1007/s00146-023-01826-7
Abstract
Interest in computerised central economic planning (CCEP) has seen a resurgence, as there is strong demand for an alternative vision to modern free (or not so free) market liberal capitalism. Given the close links of CCEP with what we would now broadly call artificial intelligence (AI)—e.g. optimisation, game theory, function approximation, machine learning, automated reasoning—it is reasonable to draw direct analogues and perform an analysis that would help identify what commodities and institutions we should see for a CCEP programme to become successful. Following this analysis, we conclude that a CCEP economy would need to have a very different outlook from current market practices, with a focus on producing basic “interlinking” commodities (e.g. tools, processed materials, instruction videos) that consumers can use as a form of collective R &D. On an institutional level, CCEP should strive for the release of basic commodities that empower consumers by having as many alternative uses as possible, but also making sure that a baseline of basic necessities is widely available.
Item Type: | Article |
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Uncontrolled Keywords: | Artificial intelligence; Planning; Reinforcement learning; Adaptive systems |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 12 Apr 2024 11:43 |
Last Modified: | 30 Oct 2024 21:16 |
URI: | http://repository.essex.ac.uk/id/eprint/38192 |
Available files
Filename: s00146-023-01826-7.pdf
Licence: Creative Commons: Attribution 4.0