TY  - JOUR
T1  - Analysis of Artificial Intelligence Readiness Performances of G7 Countries: An Application with LOPCOW-based MARCOS Method
TT  - G7 Ülkelerinin Yapay Zeka Performanslarının Analizi: LOPCOW tabanlı MARCOS Yöntemi ile Bir Uygulama
AU  - Altıntaş, Furkan Fahri
PY  - 2024
DA  - December
Y2  - 2024
DO  - 10.53070/bbd.1537792
JF  - Computer Science
JO  - JCS
PB  - Ali KARCI
WT  - DergiPark
SN  - 2548-1304
SP  - 99
EP  - 121
VL  - 9
IS  - Issue: 2
LA  - en
AB  - The artificial intelligence (AI) readiness performance of major economies can significantly impact the global economy. Therefore, analyzing the AI readiness performance of these economies is of great importance. In this study, the AI readiness performances of G7 countries were assessed using the most recent Government Artificial Intelligence Readiness Index (GAIRI) data for 2023. The analysis revealed that the importance of GAIRI components varies by country, with Data and Infrastructure generally being the most significant components. The countries were ranked according to their AI readiness performances using the LOPCOW-based MARCOS method as follows: USA, United Kingdom, Canada, France, Japan, Germany, and Italy. Notably, Italy's AI readiness performance was below the average, indicating the need for improvement to enhance its contribution to the global economy. The method applied proved to be sensitive in sensitivity analysis, credible and reliable in comparative analysis, and robust and stable in simulation analysis.
KW  - Artifical intelligence
KW  - artificial intelligence readiness performance
KW  - G7
KW  - LOPCOW
KW  - LOPCOW based MARCOS
N2  - Büyük ekonomilerin yapay zeka  hazırlık performansları, küresel ekonomi üzerinde önemli bir etkiye sahip olabilir. Bu nedenle, bu ekonomilerin yapay zeka hazırlık performanslarının analizi büyük önem taşımaktadır. Bu çalışmada, G7 ülkelerinin yapay zeka hazırlık performansları, 2023 yılına ait en güncel Hükümet Yapay Zeka Hazırlık Endeksi (YZHE) verileri kullanılarak değerlendirilmiştir. Analiz, GAIRI bileşenlerinin öneminin ülkelere göre farklılık gösterdiğini, Veri ve Altyapı bileşenlerinin genellikle en önemli bileşenler olduğunu ortaya koymuştur. Ülkeler, yapay zeka hazırlık performanslarına göre LOPCOW tabanlı MARCOS yöntemi kullanılarak şu şekilde sıralanmıştır: ABD, Birleşik Krallık, Kanada, Fransa, Japonya, Almanya ve İtalya. Özellikle İtalya'nın yapay zeka hazırlık performansının ortalamanın altında olduğu belirlenmiş olup, küresel ekonomiye katkısını artırmak için iyileştirilmesi gerektiğini göstermektedir. Uygulanan yöntem, duyarlılık analizinde hassas, karşılaştırmalı analizde güvenilir ve simülasyon analizinde sağlam ve istikrarlı olduğunu kanıtlamıştır.
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UR  - https://doi.org/10.53070/bbd.1537792
L1  - http://dergipark.org.tr/tr/download/article-file/4165337
ER  -