Economic Calculation in Light of Advances in Big Data and Artificial Intelligence

Lambert, Karras; Fegley, Tate

doi:10.1016/j.jebo.2022.12.009

Cited by 9 publications

(13 citation statements)

References 19 publications

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“…This paper builds upon recent contributions by Phelan and Wenzel (2023) and Lambert and Fegley (2023) who argue that advances in computing technology including AI, big data, quantum computing, and the like will not resolve the economic problem as set out by Ludwig von Mises (1920 [1990], 1922 [1981]) and Friedrich Hayek (1935, 1940, 1945). Both sets of authors assert – correctly – that these advances in computing technology do not resolve the discovery problem at the heart of economic calculation.…”

Section: Introductionmentioning

confidence: 92%

“…The problem with that argument – although Phelan and Wenzel do not use this terminology – is that AI cannot ‘think’ outside the box; the AI is the box. Similarly, Lambert and Fegley (2023: 246) point out that all the data used to train AI, ‘are entirely that of the past’. AI that is trained on a sub-set of known information that can be easily communicated in machine readable form cannot ‘know’ enough to replicate the entrepreneurial function.…”

Section: The Knowledge Problem: Mises and Hayekmentioning

confidence: 99%

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The economic institutions of artificial intelligence

Davidson

2024

Journal of Institutional Economics

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This paper explores the role of artificial intelligence (AI) within economic institutions, focusing on bounded rationality as understood by Herbert Simon. Artificial Intelligence can do many things in the economy, such as increasing productivity, enhancing innovation, creating new sectors and jobs, and improving living standards. One of the ways that AI can disrupt the economy is by reducing the problem of bounded rationality. AI can help overcome this problem by processing large amounts of data, finding patterns and insights, and making predictions and recommendations. This insight raises the question: can AI overcome planning problems – could it be that central planning is now a viable option for economic organisation? This paper argues that AI does not make central planning viable at either the nation-state level or the firm level, simply because AI cannot resolve the knowledge problem as described by Ludwig von Mises and Friedrich Hayek.

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Section: Introductionmentioning

confidence: 92%

Section: The Knowledge Problem: Mises and Hayekmentioning

confidence: 99%

The economic institutions of artificial intelligence

Davidson

2024

Journal of Institutional Economics

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“…Sharing data come with its own risks including privacy and security. In addition, the process of data sharing between data providers and consumers has to be precisely defined, such that both providers and consumers work together for their mutual benefit [8,9]. Such a process must at a minimum include data discovery, data delivery, and incentive mechanisms [8,9].…”

Section: Introductionmentioning

confidence: 99%

“…In addition, the process of data sharing between data providers and consumers has to be precisely defined, such that both providers and consumers work together for their mutual benefit [8,9]. Such a process must at a minimum include data discovery, data delivery, and incentive mechanisms [8,9]. This is critical within any data sharing solution that must be designed and implemented properly to ensure extensibility and scalability.…”

Section: Introductionmentioning

confidence: 99%

“…This is critical within any data sharing solution that must be designed and implemented properly to ensure extensibility and scalability. For example, using a cooperative data delivery method with an improper incentive mechanism would ultimately fail the system because participants would leave since they are not compensated proportionally for the work they do [8,9]. Hence, the proper utilization of SNS depends on the use of appropriate data-sharing systems that deliver performance, scalability, privacy, and security [4,9].…”

Section: Introductionmentioning

confidence: 99%

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Extensible, Customizable and Trustworthy SocialNetwork Data Sharing Platform: IPFS Approach

Azzedin

2024

Preprint

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The proper utilization of the enormous data volume generated by IoT is predi-cated on the use of proper data sharing mechanisms that involve satisfying manycomplex requirements including scalability, performance, and security. Therefore,many blockchain-based data-sharing systems were proposed in the literature toaddress the problem of data sharing within different application domains thatsatisfy combinations of those requirements. However, these systems fully spec-ify how data is delivered between providers and consumers, which limits theircompatibility and customizability. Therefore, in this article, we address this issueby proposing a platform for traceable data sources where the delivery methodis user-definable. This allows existing data sources to be adapted by chainingthem to new data sources that deliver data in a way that satisfies consumerrequirements. This is in addition to enabling users to monetize their data sourcesand their delivery methods using different public blockchains. We evaluated theproposed platform by implementing two different use cases and the preliminaryresults show that the platform has great potential.

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An agent-based approach to the limits of economic planning

Martinelli

2024

AI & Soc

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Mises’ and Hayek’s arguments against central economic planning have long been taken as definitive proof that a centrally planned economy managed by the government would be impossible. Today, however, the exponential rise in the capacities of AI has opened up the possibility that supercomputers could have what it takes to plan the national economy. The ‘economic calculation debate’ has thus reignited. Arguably, this is because neither Mises nor Hayek have given a clear and conclusive argument why central planning of the economy is impossible in principle. The paper frames the problem of economic planning as an agent–environment interaction, offering a taxonomy of the different sets of agents at play a) in a market economy and b) in a centrally planned economy equipped with the most sophisticated AI technology. The argument is that public institutions as planning bodies cannot replace the market order, no matter the AI technology behind them, for the elimination of the market entails the elimination of crucial kinds of agents that cannot be recreated or emulated through AI or careful social planning: the proactive action of entrepreneurs driving market allocation.

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Economic Calculation in Light of Advances in Big Data and Artificial Intelligence

Cited by 9 publications

References 19 publications

The economic institutions of artificial intelligence

The economic institutions of artificial intelligence

Extensible, Customizable and Trustworthy SocialNetwork Data Sharing Platform: IPFS Approach

An agent-based approach to the limits of economic planning

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