A Monitoring Framework for Progress in Artificial Intelligence Technology: A Research Based on Scientific and Technological Indicators

Öz

In the past century, the key technologies that shaped societal and economic transformation were mechanical, electrical, and automation technologies. In the current century, there are strong trends indicating the prominence of artificial intelligence technology. Therefore, artificial intelligence technology has become more important for all countries. The success of countries in artificial intelligence technology is only possible with well-designed artificial intelligence policy tools. It is important to measure the level of technological advancement for the formulation of policies. However, efforts to measure the scientific and technological advancement of artificial intelligence technology are insufficient. Therefore, this study aims to develop a framework to measure the scientific and technological progress of AI technology. The developed framework includes the number of publications and citations, the number of high-impact scientific journals, the number of patent applications, the number of universities ranked in the top thousand in the field of computer science, the number of international high-impact conferences, and the total number of researchers in higher education. Through these criteria, the level of scientific and technological progress of the countries has been analysed in detail. The findings clearly revealed the leading position of the USA in this field. China followed the USA. These two countries are clearly and positively differentiated from the other countries. Other countries with good performance are the UK, the Netherlands and Germany. JEL Classification : O31 , O32 , O33

Anahtar Kelimeler

• Artificial intelligence
• Technology management
• Scientific and technological progress
• Entropy
• Grey system theory

Kaynakça

1. Akçiğit, U., & Tok, E. Ö. (2020). Türkiye Bilim Raporu (No. TÜBA Raporları No:43). Türkiye Bilimler Akademisi Yayınları. google scholar
2. Aksens, D. W. (2003). A macro study of self-citation. Scientometrics, 56(2). https://doi. org/10.1023/A:1021919228368 google scholar
3. Aslan, F. (2023). Teknoloji geliştirme sürecinin değerlendirilmesi için olgunluk modeli önerisi: ARGE-500 firmalarının faaliyet ve yaklaşımlarına yönelik bir uygulama (Dissertation). Fırat Üniversitesi, Elazığ. google scholar
4. Baruffaldi, S., B., Beuzekom, B. van, Dernis, H., Harhoff, D., Rao, N., Rosenfeld, D., & Squicciarini, M. (2020). Identifying and measuring developments in artificial intelligence: Making the impossible possible (OECD Science, Technology and Industry Working Papers No. 2020/05). OECD. https:// doi.org/10.1787/5f65ff7e-en google scholar
5. Bernanke, B. S. (2011, May 16). Promoting research and development—The Government’s role. Presented at the New Building Blocks for Jobs and Economic Growth, Washington DC. Washington DC. google scholar
6. Betz, F. (2011). Managing technological innovation: Competitive advantage from change (3rd ed). Hoboken, N.J: Wiley. google scholar
7. Campbell, D., Roberge, G., Ventimiglia, A., Labrosse, I., Lefebvre, C., Picard-Aitken, M., ... Archambault, E. (2015). Analysis of bibliometric indicators for European policies 2010-2013. (Science Metrix., Ed.). Luxembourg: European Union. Retrieved from https://data.europa.eu/ doi/10.2777/194026 google scholar
8. Cesareo, S., & White, J. (2023). The Global AI Index. Tortoise. Retrieved from Tortoise website: https://www.tortoisemedia.com/intelligence/global-ai/ google scholar

9. Costas, R., Van Leeuwen, T. N., & Bordons, M. (2010). Self-citations at the meso and individual levels: Effects of different calculation methods. Scientometrics, 82(3), 517-537. https://doi.org/10.1007/ s11192-010-0187-7 google scholar
10. Dwivedi, P. P., & Sharma, D. K. (2022). Application of Shannon entropy and CoCoSo methods in selection of the most appropriate engineering sustainability components. Cleaner Materials, 5, 100118. https://doi.org/10.1016/j.clema.2022.100118 google scholar
11. Eto, H. (2003). Interdisciplinary information input and output of a nano-technology project. Scientometrics, 58(1), 5-33. https://doi.org/10.1023/A:1025423406643 google scholar
12. Evans, K. M., Hazan, G., Kamepalli, S., & Matthews, K. R. W. (2021). U.S. Federal Scientific Research and Development: Budget Overview and Outlook. Rice University’s Baker Institute for Public Policy. Retrieved from Rice University’s Baker Institute for Public Policy website: https://www. bakerinstitute.org/research/us-federal-scientific-research-and-development-budget-overview-and-outlook/ google scholar
13. Everaers, P. (2022). Standards as the backbone for official statistics, how well do they fit within national and international systems?12 or Does the obsession with cross-national comparisons blind us to the weakly implemented standards behind them? Statistical Journal of the IAOS, 38(2), 675-680. https://doi.org/10.3233/SJI-220032 google scholar
14. Gonzâlez-Pereira, B., Guerrero-Bote, V. P., & Moya-Anegon, F. (2010). A new approach to the metric of journals’ scientific prestige: The SJR indicator. Journal of Informetrics, 4(3), 379-391. https:// doi.org/10.1016/j.joi.2010.03.002 google scholar
15. Guerrero-Bote, V. P., & Moya-Anegon, F. (2012). A further step forward in measuring journals’ scientific prestige: The SJR2 indicator. Journal of Informetrics, 6(4), 674-688. https://doi. org/10.1016/j.joi.2012.07.001 google scholar
16. Hellsten, I., Lambiotte, R., Scharnhorst, A., & Ausloos, M. (2007). Self-citations, co-authorships and keywords: A new approach to scientists’ field mobility? Scientometrics, 72(3), 469-486. https:// doi.org/10.1007/s11192-007-1680-5 google scholar
17. Hyland, K. (2003). Self-citation and self-reference: Credibility and promotion in academic publication. Journal of the American Society for Information Science and Technology, 54(3), 251259. https://doi.org/10.1002/asi.10204 google scholar
18. IBM Corporation. (2022). IBM Global AI Adoption Index 2022. Retrieved from https://www.ibm.com/ watson/resources/ai-adoption google scholar
19. Isaka, M. (2013). Intellectual Property Rights: The Role of Patents in Renewable Energy Technology Innovation (p. 34). Bonn, Germany: The International Renewable Energy Agency (IRENA). Retrieved from The International Renewable Energy Agency (IRENA) website: www.irena.org google scholar
20. Kaloudis, A., Aspelund, A., Koch, P. M., Lauvâs, T. A., Mathisen, M. T., Strand, 0., ... Aadland, T. (2019). How universities contribute to innovation: A literature review-based analysis. Norway: Norwegian Ministry of Education and Research. google scholar
21. Korinek, A., Schindler, M., & Stiglitz, J. E. (2021). Technological progress, artificial intelligence, and inclusive growth (Working Paper No. WP/21/166). International Monetary Fund. google scholar
22. Le, T., Pham, H., Mai, S., & Vu, N. (2022). Frontier academic research, industrial R&D and technological progress: The case of OECD countries. Technovation, 114, 102436. https://doi.org/10.1016/j. technovation.2021.102436 google scholar
23. Liu, H., Yang, G., Liu, X., & Song, Y. (2020). R&D performance assessment of industrial enterprises in China: A two-stage DEA approach. Socio-Economic Planning Sciences, 71, 100753. https://doi. org/10.1016/j.seps.2019.100753 google scholar
24. Mansfield, E. (1991). Academic research and industrial innovation. Research Policy, 20(1), 1-12. https://doi.org/10.1016/0048-7333(91)90080-A google scholar
25. Ministry Of Education, Culture, Sports, Science And Technology Japanese Government. (2005). Contributions of scientific and technological progress. Tokyo/Japan. Retrieved from https://www. mext.go.jp/en/publication/whitepaper/title03/detail03/1372835.htm google scholar
26. Moed, H. F. (2005). Citation Analysis in Research Evaluation (Vol. 9). Berlin/Heidelberg: Springer-Verlag. https://doi.org/10.1007/1-4020-3714-7 google scholar
27. Narin, F., Hamilton, K. S., & Olivastro, D. (1997). The increasing linkage between U.S. technology and public science. Research Policy, 26(3), 317-330. https://doi.org/10.1016/S0048-7333(97)00013-9 google scholar
28. National Research Council. (2007). A strategy for assessing science: Behavioral and social research on aging (I. Feller & P. C. Stern, Eds.). Washington, DC: National Academies Press. google scholar
29. National Research Council (NRCb). (1986). The Positive Sum Strategy: Harnessing Technology for Economic Growth (p. 612). Washington, D.C.: National Academies Press. https://doi. org/10.17226/612 google scholar
30. Nestor, M., Fattorini, L., Brynjolfsson, E., Etchemendy, J., Ligett, K., Lyons, T., ... Perrault, R. (2023). The AI Index 2023 Annual Report. Stanford, CA: AI Index Steering Committee, Institute for Human-Centered AI, Stanford University. Retrieved from AI Index Steering Committee, Institute for Human-Centered AI, Stanford University website: https://aiindex.stanford.edu/report/ google scholar
31. Ng, D. K. W. (1994). Grey system and grey relational model. ACM SIGICE Bulletin, 20(2). google scholar
32. OECD and SCImago Research Group. (2016). Compendium of bibliometric science indicators. Paris. Retrieved from http://oe.cd/scientometrics google scholar
33. OECDa. (1994). The Measurement of Scientific and Technical Activities: Standard Practice for Surveys of Research and Experimental Development - Frascati Manual 1993. OECD. https://doi. org/10.1787/9789264063525-en google scholar
34. OECDb. (1995). Measurement of Scientific and Technological Activities: Manual on the Measurement of Human Resources Devoted to S&T - Canberra Manual. Paris/France: OECD. https://doi. org/10.1787/9789264065581-en google scholar
35. OECDc. (2017). OECD Science, Technology and Industry Scoreboard 2017: The digital transformation. OECD. https://doi.org/10.1787/9789264268821-en google scholar
36. Oester, S., Cigliano, J. A., Hind-Ozan, E. J., & Parsons, E. C. M. (2017). Why Conferences Matter—An google scholar
37. Illustration from the International Marine Conservation Congress. Frontiers in Marine Science, 4, 257. https://doi.org/10.3389/fmars.2017.00257 google scholar
38. Okubo, Y. (1997). Bibliometric Indicators and Analysis of Research Systems: Methods and Examples (Working Papers No. 51765). Paris: OECD. https://doi.org/10.1787/208277770603 google scholar
39. Parsons, E. C. M. (2015). So you think you want to run an environmental conservation meeting? Advice on the slings and arrows of outrageous fortune that accompany academic conference planning. Journal of Environmental Studies and Sciences, 5(4), 735-744. https://doi.org/10.1007/ s13412-015-0327-8 google scholar
40. Pavel, A.-P. (2015). Global University Rankings—A Comparative Analysis. Procedia Economics and Finance, 26, 54-63. https://doi.org/10.1016/S2212-5671(15)00838-2 google scholar
41. Peng, X., Tang, X., Chen, Y., & Zhang, J. (2021). Ranking the Healthcare Resource Factors for Public Satisfaction with Health System in China—Based on the Grey Relational Analysis Models. International Journal of Environmental Research and Public Health, 18(3), 995. https://doi. org/10.3390/ijerph18030995 google scholar
42. Rogerson, A., Hankins, E., Nettel, P. F., & Rahim, S. (2022). Government AI readiness index. Oxford Insights. Retrieved from Oxford Insights website: https://www.oxfordinsights.com/government-ai-readiness-index2021 google scholar
43. Samuelson, S., & Sarrico, C. (2017). Benchmarking Higher Education System Performance: Conceptual Framework and Data. Organisation for Economic Co-operation and Development (No. EDU/ EDPC(2017)1). Organisation for Economic Co-operation and Development(OECD). google scholar
44. Schreiber, M. (2007). Self-citation corrections for the Hirsch index. Europhysics Letters (EPL), 78(3), 30002. https://doi.org/10.1209/0295-5075/78/30002 google scholar
45. Sobral, S. R. (2021). The Universities Ranking World Cup: A Global View by Continent and Country from the Computer Science Perspective. International Journal of Information and Education Technology, 11(6), 277-285. https://doi.org/10.18178/ijiet.2021.11.6.1523 google scholar
46. Tan, X.-R. (2005). Applications of gray relational analysis in gastroenterology. World Journal of Gastroenterology, 11(22), 3457. https://doi.org/10.3748/wjg.v11.i22.3457 google scholar
47. Times Higher Education. (2022). Times Higher Education World University Rankings. THE World Universities Insights Limited. https://doi.org/10.1201/9781315155890-8 google scholar
48. Tsinghua University. (2018). China AI development report. google scholar
49. Uludağ, A. S., & Doğan, H. (2021). Üretim yönetiminde çok kriterli karar verme yöntemleri: Lİteratür, teori ve uygulama (1st ed.). Ankara: Nobel Yayınevi. google scholar
50. WIPO. (2019). WIPO Technology Trends 2019: Artificial Intelligence. Geneva: World Intellectual Property Organization. google scholar
51. World Economic Forum. (2022). Empowering AI Leadership: AI C-Suite Toolkit. Switzerland: World Economic Forum. google scholar
52. Zhu, Y., Tian, D., & Yan, F. (2020). Effectiveness of Entropy Weight Method in Decision-Making. Mathematical Problems in Engineering, 2020, 1-5. https://doi.org/10.1155/2020/3564835 google scholar