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AI Public Policies in Latin America: Disruption or more of the same?

Published:12 January 2022Publication History

ABSTRACT

Artificial Intelligence (AI) resurgence has triggered a new wave of public policy development in over 60 countries worldwide. Given glaring inequalities and early deindustrialization in Latin America and the Caribbean, AI can provide new opportunities to change course if harnessed strategically with long-term goals on the horizon. Based on critical and descriptive research centered on document review, this paper examines AI public policy development from a public policy perspective. First, an analytical framework comprising AI policy inputs such as data, infrastructure, and human and institutional, and AI policy outputs targeting socio-economic, political, technical and governance is developed. Then, after reviewing existing literature and policy documents, three types of AI policies are identified globally. The framework and policy typology are then used to study AI policies in the region. While different development and maturity levels are identified in the region, national AI policies shy away from disrupting the current context and discussing issues related to data and technology sovereignty.

References

  1. K. Schwab, The fourth industrial revolution, First U.S. edition. New York: Crown Business, 2016.Google ScholarGoogle Scholar
  2. S. Milan and E. Treré, “Big Data from the South(s): Beyond Data Universalism:,” Television & New Media, Apr. 2019, doi: 10.1177/1527476419837739.Google ScholarGoogle Scholar
  3. K. Lee, F. Malerba, and A. Primi, “The fourth industrial revolution, changing global value chains and industrial upgrading in emerging economies,” Journal of Economic Policy Reform, vol. 0, no. 0, pp. 1–12, May 2020, doi: 10/gg88ht.Google ScholarGoogle Scholar
  4. M. L. Gray and S. Suri, Ghost work: how to stop Silicon Valley from building a new global underclass. Boston: Houghton Mifflin Harcourt, 2019.Google ScholarGoogle Scholar
  5. R. Calo, “Artificial Intelligence Policy: A Primer and Roadmap,” Social Science Research Network, Rochester, NY, SSRN Scholarly Paper ID 3015350, Aug. 2017. Accessed: Aug. 26, 2020. [Online]. Available: https://papers.ssrn.com/abstract=3015350Google ScholarGoogle Scholar
  6. A. Dafoe, “AI Governance: A Research Agenda,” Future of Humanity Institute, Oxford University, Aug. 2018.Google ScholarGoogle Scholar
  7. A. Goolsbee, “Public Policy in an AI Economy,” National Bureau of Economic Research, Working Paper 24653, May 2018. doi: 10.3386/w24653.Google ScholarGoogle ScholarCross RefCross Ref
  8. W. Naudé and N. Dimitri, “The race for an artificial general intelligence: implications for public policy,” AI & Soc, vol. 35, no. 2, pp. 367–379, Jun. 2020, doi: 10/gg6snv.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. B. Perry and R. Uuk, “AI Governance and the Policymaking Process: Key Considerations for Reducing AI Risk,” Big Data and Cognitive Computing, vol. 3, no. 2, Art. no. 2, Jun. 2019, doi: 10/gg9zkw.Google ScholarGoogle ScholarCross RefCross Ref
  10. M. Howlett, Designing public policies: principles and instruments, Second edition. London ; New York, NY: Routledge, Taylor & Francis Group, 2019.Google ScholarGoogle Scholar
  11. E. Brynjolfsson and A. McAfee, The second machine age: work, progress, and prosperity in a time of brilliant technologies. New York London: W.W. Norton & Company, 2016.Google ScholarGoogle Scholar
  12. M. Brundage and J. Bryson, “Smart Policies for Artificial Intelligence,” arXiv:1608.08196 [cs], Aug. 2016, Accessed: Sep. 10, 2020. [Online]. Available: http://arxiv.org/abs/1608.08196Google ScholarGoogle Scholar
  13. K. (et. al. ) Crawford, “AI Now 2019 Report,” NYU, 2020. Accessed: May 27, 2021. [Online]. Available: ​https://ainowinstitute.org/AI_Now_2019_Report.html​Google ScholarGoogle Scholar
  14. R. Ochigame, “The Invention of ‘Ethical AI’: How Big Tech Manipulates Academia to Avoid Regulation,” The Intercept, Dec. 20, 2019. https://theintercept.com/2019/12/20/mit-ethical-ai-artificial-intelligence/ (accessed Sep. 25, 2020).Google ScholarGoogle Scholar
  15. OECD, “Recommendation of the Council on Artificial Intelligence,” OECD, Paris, France, 2020. Accessed: Aug. 04, 2020. [Online]. Available: https://legalinstruments.oecd.org/en/instruments/OECD-LEGAL-0449Google ScholarGoogle Scholar
  16. M. Cabrol, N. González A., C. Pombo, and R. Sánchez A., “fAIr LAC: Adopción ética y responsable de la inteligencia artificial en América Latina y el Caribe,” Inter-American Development Bank, Jan. 2020. doi: 10.18235/0002169.Google ScholarGoogle ScholarCross RefCross Ref
  17. OECD, “OECD AI live repository of over 260 AI strategies & policies,” OECD AI live repository of over 260 AI strategies & policies, 2020. https://www.oecd.ai/dashboards (accessed Aug. 22, 2020).Google ScholarGoogle Scholar
  18. O. J. Grof, M. Nitzberg, and D. Zehr, “Comparison of National Strategies to Promote Artificial Intelligence, Part 1,” Konrad Adenauer Foundation, Nov. 2018. Accessed: Aug. 26, 2020. [Online]. Available: https://www.kas.de/en/single-title/-/content/vergleich-nationaler-strategien-zur-foerderung-von-kuenstlicher-intelligenzGoogle ScholarGoogle Scholar
  19. O. J. Grof, M. Nitzberg, and D. Zehr, “Comparison of National Strategies to Promote Artificial Intelligence, Part 2,” Konrad Adenauer Foundation, Berlin, Jan. 2019. Accessed: Aug. 26, 2020. [Online]. Available: https://www.kas.de/en/single-title/-/content/vergleich-nationaler-strategien-zur-forderung-von-kunstlicher-intellige-1Google ScholarGoogle Scholar
  20. S. Heumann and N. Zahn, “Benchmarking National AI Strategies: Why and How Indicators and Monitoring Can Support Agile Implementation,” SSRN Journal, 2018, doi: 10.2139/ssrn.3502283.Google ScholarGoogle Scholar
  21. D. Kim, “Artificial Intelligence Policies in East Asia: An Overview from the Canadian Perspective,” Asia Pacific Foundation of Canada, Jul. 25, 2019. https://www.asiapacific.ca/research-report/artificial-intelligence-policies-east-asia-overview-canadian (accessed Sep. 03, 2020).Google ScholarGoogle Scholar
  22. S. E. Mantilla, “Hacia una estrategia nacional de Inteligencia Artificial,” Instituto de Estrategia Internacional, Buenos Aires, Argentina, Oct. 2018.Google ScholarGoogle Scholar
  23. S. Saran, N. Natarajan, and M. Srikumar, “In pursuit of autonomy: AI and national strategies,” Observer Research Foundation, New Delhi, India, 2018. Accessed: Aug. 26, 2020. [Online]. Available: https://www.orfonline.org/research/in-pursuit-of-autonomy-ai-and-national-strategies/Google ScholarGoogle Scholar
  24. V. Amarante, Galván, Marco, and Mancero, Xavier, “Inequality in Latin America: A Global Measurement,” CEPAL Review, vol. 118, pp. 25–44, 2016.Google ScholarGoogle ScholarCross RefCross Ref
  25. L. Tornarolli, M. Ciaschi, and L. Galeano, “Income Distribution in Latin America The Evolution in the Last 20 Years: A Global Approach,” Centro de Estudios Distributivos, Laborales y Sociales Universidad Nacional de La Plata, La Plata, 2018.Google ScholarGoogle Scholar
  26. CEPAL, “Universalizar el acceso a las tecnologías digitales para enfrentar los efectos del COVID-19,” CEPAL, Aug. 2020. Accessed: Sep. 08, 2020. [Online]. Available: https://www.cepal.org/es/publicaciones/45938-universalizar-acceso-tecnologias-digitales-enfrentar-efectos-covid-19Google ScholarGoogle Scholar
  27. OECD and IDB, “Política de Banda Ancha para América Latina y el Caribe: Un manual para la economía digital,” 2016.Google ScholarGoogle ScholarCross RefCross Ref
  28. UNESCO, “Sociedad digital: brechas y retos para la inclusión digital en América Latina y el Caribe,” 2017.Google ScholarGoogle Scholar
  29. C. Aguerre, “Estrategias nacionales de IA y gobernanza de datos en la región En C. Aguerre, (Ed.). Inteligencia Artificial en América Latina y el Caribe. Ética, Gobernanza y Políticas. Buenos Aires: CETyS Universidad de San Andrés.,” vol. En C. Aguerre, (Ed.). Inteligencia Artificial en América Latina y el Caribe. Ética, Gobernanza y Políticas. Buenos Aires: CETyS Universidad de San Andrés., Buenos Aires, Argentina, 2020.Google ScholarGoogle Scholar
  30. C. Gómez Mont, C. M. Del Pozo, C. Martínez Pinto, and A. V. Martín del Campo Alcocer, “La inteligencia artificial al servicio del bien social en América Latina y el Caribe: Panorámica regional e instantáneas de doce países,” Inter-American Development Bank, May 2020. Accessed: Aug. 26, 2020. [Online]. Available: https://publications.iadb.org/es/node/28187Google ScholarGoogle Scholar
  31. Departamento Nacional de Planeación, “Plan Nacional de Desarrollo 2018-2022. Pacto por Colombia. Pacto por la Equidad. Ley 1955 de 2019.,” 2018.Google ScholarGoogle Scholar
  32. Departamento Nacional de Planeación , CONPES 3920. 2018, p. 116.Google ScholarGoogle Scholar
  33. Consejería Presidencial para Asuntos Económicos y Transformación Digital and Armando, “Consulta marco ético Inteligencia Artificial en Colombia. Documento para discusión.,” Bogotá, 2020.Google ScholarGoogle Scholar
  34. Departamento Nacional de Planeación , CONPES 3995. 2020, p. 51.Google ScholarGoogle Scholar
  35. AGESIC, Presidencia de la República, “Agenda Uruguay Digital. Transformación con equidad 2020.,” 2019.Google ScholarGoogle Scholar
  36. AGESIC, Presidencia de la República, “Uruguay: Gobierno Digital y D9,” 2019. https://www.gub.uy/agencia-gobierno-electronico-sociedad-informacion-conocimiento/uruguay-gobierno-digital-d9Google ScholarGoogle Scholar
  37. Presidencia de la República Argentina, “Agenda Digital Argentina 2030.” 2018.Google ScholarGoogle Scholar
  38. Presidencia de la República Argentina, “ArgenIA. Plan Nacional de Inteligencia Artificial,” 2018. https://ia-latam.com/portfolio/plan-nacional-de-ia-gobierno-de-argentina/Google ScholarGoogle Scholar
  39. UNESCO, “Estratégia Brasileira para a Inteligência Artificial,” 2018.Google ScholarGoogle Scholar
  40. Ministry of Science, Technology and Innovation, “Estrátegia Brasileira da Inteligencia Artificial e seus eixos Temáticos,” Jul. 2021. Accessed: Aug. 28, 2021. [Online]. Available: https://www.gov.br/mcti/pt-br/acompanhe-o-mcti/transformacaodigital/arquivosinteligenciaartificial/ia_estrategia_portaria_mcti_4-979_2021_anexo1.pdfGoogle ScholarGoogle Scholar
  41. Comisión Desafíos del Futuro, Ciencia, Tecnología e Innovación, “Inteligencia Artificial para Chile. Urgencia de desarrollar una estrategia.,” Senado de la República, 2019.Google ScholarGoogle Scholar
  42. Gobierno de Chile, “Política Nacional de Inteligencia Artificial,” Política Nacional de Inteligencia Artificial, 2021. http://www.minciencia.gob.cl/politica-nacional-de-inteligencia-artificial/ (accessed May 27, 2021).Google ScholarGoogle Scholar
  43. Gobierno digital Chile, “La futura Política Nacional de Inteligencia Artificial,” 2020. https://digital.gob.cl/noticias/la-futura-politica-nacional-de-inteligencia-artificial (accessed Oct. 05, 2020).Google ScholarGoogle Scholar
  44. Gobierno de la República de México, “Estrategia Nacional Digital.” 2013.Google ScholarGoogle Scholar
  45. E. Martinho-Truswell, H. Miller, I. N. Asare, A. Petheram, R. Stirling, and C. Martínez, “Toward an AI Strategy in Mexico: Harnessing the AI Revolution,” 2018.Google ScholarGoogle Scholar
  46. Coalición IAMX2030, “Agenda Nacional Mexicana de Inteligencia Artificial,” 2020.Google ScholarGoogle Scholar
  47. Ministerio de Ciencia, Tecnología y Telecomunicaciones, “Estrategia de Transformación Digital hacia la Costa Rica del Bicentenario 4.0,” 2018.Google ScholarGoogle Scholar
  48. Ministerio de Tecnologías de la Información y Comunicación, “Agenda Digital Paraguay,” 2018. https://www.mitic.gov.py/agenda-digital/agenda-digital/que-es-la-agenda-digital (accessed Sep. 01, 2020).Google ScholarGoogle Scholar
  49. Oficina de Planeamiento y Presupuesto, “Hacia una Estrategia Nacional de Desarrollo, Uruguay 2050 Volumen II - Automatización y empleo en Uruguay - Una mirada en perspectiva y en prospectiva,” 2019. [Online]. Available: https://www.opp.gub.uy/sites/default/files/documentos/2018-06/2256_Publicacion_Automatizacion_y_empleo_en_Uruguay.pdfGoogle ScholarGoogle Scholar
  50. Gabinete Ministerial de Transformación Productiva y Competitividad uruguayo, “Hoja de Ruta Ciencia de Datos y Aprendizaje Automático,” 2019. [Online]. Available: (https://www.transformauruguay.gub.uy/es/documentos/tic.pdf).Google ScholarGoogle Scholar
  51. Departmento Nacional de Planeación , CONPES 3975. 2019, p. 63.Google ScholarGoogle Scholar
  52. K. Crawford, Atlas of AI: power, politics, and the planetary costs of artificial intelligence. New Haven: Yale University Press, 2021.Google ScholarGoogle ScholarCross RefCross Ref
  53. E. D. Dussel, Ética de la liberación en la edad de la globalización y la exclusión. Madrid: Trotta, 2009.Google ScholarGoogle Scholar
  54. A. Andreoni and F. Tregenna, “Escaping the middle-income technology trap: A comparative analysis of industrial policies in China, Brazil and South Africa,” Structural Change and Economic Dynamics, vol. 54, pp. 324–340, Sep. 2020, doi: 10/gg96qr.Google ScholarGoogle ScholarCross RefCross Ref
  55. H.-J. Chang and A. Andreoni, “Industrial Policy in the 21st Century,” Development and Change, vol. 51, no. 2, pp. 324–351, 2020, doi: 10/ghbg8k.Google ScholarGoogle ScholarCross RefCross Ref

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        • Published in

          cover image ACM Other conferences
          ICEGOV '21: Proceedings of the 14th International Conference on Theory and Practice of Electronic Governance
          October 2021
          557 pages
          ISBN:9781450390118
          DOI:10.1145/3494193

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          Publication History

          • Published: 12 January 2022

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