Artificial intelligence in the field of economics

Steve J Bickley,Ho Fai Chan,Benno Torgler

doi:10.1007/s11192-022-04294-w

Steve J Bickley, Ho Fai Chan + Show 1 more

Open Access

https://doi.org/10.1007/s11192-022-04294-w

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Abstract

The history of AI in economics is long and winding, much the same as the evolving field of AI itself. Economists have engaged with AI since its beginnings, albeit in varying degrees and with changing focus across time and places. In this study, we have explored the diffusion of AI and different AI methods (e.g., machine learning, deep learning, neural networks, expert systems, knowledge-based systems) through and within economic subfields, taking a scientometrics approach. In particular, we centre our accompanying discussion of AI in economics around the problems of economic calculation and social planning as proposed by Hayek. To map the history of AI within and between economic sub-fields, we construct two datasets containing bibliometrics information of economics papers based on search query results from the Scopus database and the EconPapers (and IDEAs/RePEc) repository. We present descriptive results that map the use and discussion of AI in economics over time, place, and subfield. In doing so, we also characterise the authors and affiliations of those engaging with AI in economics. Additionally, we find positive correlations between quality of institutional affiliation and engagement with or focus on AI in economics and negative correlations between the Human Development Index and share of learning-based AI papers.

Highlights

The quest for artificial intelligence1 (AI) has affected many fields and disciplines; economics is no exception
To gather the data needed to map this history of AI within and between economic subfields, we construct two datasets containing bibliometrics information of economics papers based on search query results from Scopus database and the EconPapers repository
We have explored the diffusion of AI and different AI methods (e.g., machine learning (ML), deep learning (DL), neural networks, expert systems, knowledgebased systems) through and within economic subfields, taking a Scientometrics approach

Summary

Introduction

The quest for artificial intelligence (AI) has affected many fields and disciplines; economics is no exception. It began with the dream of creating human- or animal-like machines and automata such as Leonardo da Vinci’s robot knight, walking lion, or Vaucanson’s duck.. Herb Simon, for example, shifted his interests and concerns around administration and economics towards human problem solving to discover the symbolic processes that people use in their thinking. The computer was used as a general processor for symbols. In other words, he found tools within computer languages that classical mathematical languages could not offer when exploring the processes of human thinking (Simon, 1991). The use of AI was closely linked to attaining more rigor in the fields of behavioral and social sciences

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