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PRWP

Reproducibility package for Beyond The AI Divide: A Simple Approach To Identifying Global And Local Overperformers In AI Preparedness

2025
Get Reproducibility Package
Reference ID
RR_WLD_2025_284
DOI
https://doi.org/10.60572/rpkc-nf68
Author(s)
Pierre Mandon
Collections
World Bank Policy Research Working Papers
Metadata
JSON
Created on
Mar 12, 2025
Last modified
Mar 24, 2025
  • Project Description
  • Downloads
  • Overview
  • Reproducibility Package
  • Description
  • Scope and coverage
  • Disclaimer
  • Access and rights
  • Contacts
  • Information on metadata
  • Citation
  • Overview

    Abstract

    This paper examines global disparities in artificial intelligence preparedness, using the 2023 Artificial Intelligence Preparedness Index developed by the International Monetary Fund alongside the multidimensional Economic Complexity Index. The proposed methodology identifies both global and local overperformers by comparing actual artificial intelligence readiness scores to predictions based on economic complexity, offering a comprehensive assessment of national artificial intelligence capabilities. The findings highlight the varying significance of regulation and ethics frameworks, digital infrastructure, as well as human capital and labor market development in driving artificial intelligence overperformance across different income levels. Through case studies, including Singapore, Northern Europe, Malaysia, Kazakhstan, Ghana, Rwanda, and emerging demographic giants like China and India, the analysis illustrates how even resource-constrained nations can achieve substantial artificial intelligence advancements through strategic investments and coherent policies. The study underscores the need for offering actionable insights to foster peer learning and knowledge-sharing among countries. It concludes with recommendations for improving artificial intelligence preparedness metrics and calls for future research to incorporate cognitive and cultural dimensions into readiness frameworks.

    Reproducibility Package

    Scripts
    Readme Get Reproducibility Package
    Link: https://reproducibility.worldbank.org/index.php/catalog/251/download/735/README.pdf
    Reproducibility package for Beyond The AI Divide: A Simple Approach To Identifying Global And Local Overperformers In AI Preparedness
    Title
    Reproducibility package for Beyond The AI Divide: A Simple Approach To Identifying Global And Local Overperformers In AI Preparedness
    Date
    2025-03
    Dependencies
    Stata dependencies are listed in the ado folder. R dependencies are saved in the renv folder.
    Instructions
    See README in reproducibility package.
    Notes
    Computational reproducibility verified by Development Impact (DIME) Analytics team, World Bank.
    Source code repository
    Repository name URI
    Reproducible Research Repository (World Bank) https://reproducibility.worldbank.org
    Software
    R
    Name
    R
    Version
    4.4.0
    Stata
    Name
    Stata
    Version
    Version 18 MP

    Reproducibility

    Technology environment

    – OS: Windows 10 Enterprise
    – Processor: Intel(R) Xeon(R) Gold 6132 CPU @ 2.60GHz (2 processors)
    – Memory available: 32 GB
    – Software version: Stata 18.0 MP, R 4.4.

    Technology requirements

    The code takes approximately 15 minutes to run.

    Reproduction instructions

    To run the package:

    • Open the do-file "Do_AiPI_PCA_ECI" file, change directory paths and run the script
    • Open the do-file "Do_AIPI_&_BMA" file, change the directory paths, and run the script
    • Open the code.Rproj file
    • Open the script.R file and run the script

    Data

    Datasets
    Artificial Intelligence Preparedness Index (AIPI) database
    Name
    Artificial Intelligence Preparedness Index (AIPI) database
    Note
    Source: IMF AI Preparedness Index (AIPI). Date Accessed: November 2024 . Datasets: imf-dm-export-*.xls (5)
    Access policy
    Data is publicly available and included in the reproducibility package.
    License URL
    https://www.imf.org/en/About/copyright-and-terms#data
    Data URL
    https://www.imf.org/external/datamapper/datasets/AIPI#:~:text=AI%20Preparedness%20Index%20(AIPI)%20assesses,integration%2C%20and%20regulation%20and%20ethics
    Economic Complexity Indexes, for Trade, Technology and Research
    Name
    Economic Complexity Indexes, for Trade, Technology and Research
    Note
    Source: The Observatory of Economic Complexity. Date Accessed: December 2024. Datasets: Data-ECI-*.csv (3). Instructions: Download and place in the rawData folder
    Access policy
    Data is publicly available but does not allow redistribution.
    License URL
    https://oec.world/en/resources/terms
    Data URL
    https://oec.world/en/rankings/eci/hs6/hs96
    Database from Sala-i-Martin et al. (2004) "Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach"
    Name
    Database from Sala-i-Martin et al. (2004) "Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach"
    Note
    Source: Sala-I-Martin, Xavier, Doppelhofer, Gernot, and Miller, Ronald I. Replication data for: Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach. Nashville, TN: American Economic Association [publisher], 2004. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-12-06. https://doi.org/10.3886/E116024V1. Date Accessed: December 2024. Datasets: BACE_data.xls
    Access policy
    Data is publicly available and included in the reproducibility package.
    License URL
    https://www.openicpsr.org/openicpsr/project/116024/version/V1/view?path=/openicpsr/116024/fcr:versions/V1/LICENSE.txt&type=file
    Data URL
    https://www.openicpsr.org/openicpsr/project/116024/version/V1/view
    World Bank Official Boundaries
    Name
    World Bank Official Boundaries
    Note
    Source: World Bank Development Data Hub. Date Accessed: December 2024. Datasets: wb_countries_admin0_10m.shp, wb_countries_admin0_10m.dbf.
    Access policy
    Data is publicly available and included in the reproducibility package.
    License
    Creative Commons Attribution 4.0
    License URL
    https://creativecommons.org/licenses/by/4.0/
    Data URL
    https://datacatalog.worldbank.org/search/dataset/0038272/World-Bank-Official-Boundaries
    World Development Indicators
    Name
    World Development Indicators
    Note
    Data Accessed: December 2024. Indicator: Total population. Instructions: Downloadable directly from Stata through the command "wbopendata, indicator(SP.POP.TOTL) clear" included in the Do_AiPI_PCA_ECI.do script.
    Access policy
    Data is publicly available and included in the reproducibility package.
    Data statement

    All data sources are publicly available but not all are included in the reproducibility package. (Accessible Data)

    Description

    Output
    Beyond The AI Divide: A Simple Approach To Identifying Global And Local Overperformers In AI Preparedness
    Type
    Working Paper
    Title
    Beyond The AI Divide: A Simple Approach To Identifying Global And Local Overperformers In AI Preparedness
    Description
    Policy Research Working Papers (PRWP) WPS11073
    URL
    http://documents.worldbank.org/curated/en/099517502242572646
    DOI
    https://doi.org/10.1596/1813-9450-11073
    Authors
    Author Affiliation Email
    Pierre Mandon World Bank pmandon@worldbank.org
    Date of production

    2025-03-11

    Scope and coverage

    Geographic locations
    Location Code
    World WLD
    Keywords
    Ai Preparedness Economic Complexity Peer Learning Policy Overperformance
    Topics
    ID Topic Parent topic ID Vocabulary Vocabulary URI
    F63 Economic Development F6 Journal of Economic Literature (JEL)
    H11 Structure, Scope, and Performance of Government H1 Journal of Economic Literature (JEL)
    O33 Technological Change: Choices and Consequences • Diffusion Processes O3 Journal of Economic Literature (JEL)
    O38 Government Policy O3 Journal of Economic Literature (JEL)

    Disclaimer

    Disclaimer

    The materials in the reproducibility packages are distributed as they were prepared by the staff of the International Bank for Reconstruction and Development/The World Bank. The findings, interpretations, and conclusions expressed in this event do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. The World Bank does not guarantee the accuracy of the materials included in the reproducibility package.

    Access and rights

    License
    Name URI
    Modified BSD3 https://opensource.org/license/bsd-3-clause/

    Contacts

    Contacts
    Name Affiliation Email
    Pierre Mandon World Bank pmandon@worldbank.org
    Reproducibility WBG World Bank reproducibility@worldbank.org

    Information on metadata

    Producers
    Name Abbreviation Affiliation Role
    Reproducibility WBG DIME World Bank - Development Impact Department Verification and preparation of metadata
    Date of Production

    2025-03-11

    Document version

    1

    Citation

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