2024年到底谁在使用人工智能?(英).pdf
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1、Policy Research Working Paper10870Who on Earth Is Using Generative AI?Yan LiuHe WangDigital Development Global PracticeAugust 2024 Public Disclosure AuthorizedPublic Disclosure AuthorizedPublic Disclosure AuthorizedPublic Disclosure AuthorizedProduced by the Research Support TeamAbstractThe Policy R
2、esearch Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues.An objective of the series is to get the findings out quickly,even if the presentations are less than fully polished.The papers carry the names of the authors and sh
3、ould be cited accordingly.The findings,interpretations,and conclusions expressed in this paper are entirely those of the authors.They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations,or those of the Execut
4、ive Directors of the World Bank or the governments they represent.Policy Research Working Paper 10870Leveraging unconventional data,including website traffic data and Google Trends,this paper unveils the real-time usage patterns of generative artificial intelligence tools by individuals across count
5、ries.The paper also examines coun-try-level factors driving the uptake and early impacts of generative artificial intelligence on online activities.As of March 2024,the top 40 generative artificial intelligence tools attract nearly 3 billion visits per month from hun-dreds of millions of users.ChatG
6、PT alone commanded 82.5 percent of the traffic,yet reaching only one-eightieth of Googles monthly visits.Generative artificial intelligence users skew young,highly educated,and male,particularly for video generation tools,with usage patterns strongly indicating productivity-related activities.Genera
7、tive arti-ficial intelligence has achieved unprecedentedly rapid global diffusion,reaching almost all economies worldwide within 16 months of ChatGPTs release.Middle-income econo-mies have disproportionately high adoption of generative artificial intelligence relative to their economic scale,now con
8、tribute more than 50 percent of global traffic,while low-income economies contribute less than 1 percent.Regression analysis reveals that income level,share of youth population,digital infrastructure,specialization in high-skill tradable services,English proficiency,and human capital are strongly co
9、rrelated with higher uptake of gen-erative artificial intelligence.The paper also documents disruptions in online traffic patterns and emphasizes the need for targeted investments in digital infrastructure and skills development to harness the full potential of artificial intelligence.This paper is
10、a product of the Digital Development Global Practice.It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world.Policy Research Working Papers are also posted on the Web at http:/www.worldbank.org/
11、prwp.The authors may be contacted at yanliuworldbank.org.Who on Earth Is Using Generative AI?Yan Liu*and He Wang*World BankJEL codes:O30,O31,O14Key words:Generative AI,Technology Adoption,Geographic Disparities,Digital DivideWe would like to thank Stephane Straub,Davide Strusani,and Estefania Vergar
12、a-Cobos for helpful commentsand suggestions.Email:yanliuworldbank.orgEmail:hwang21worldbank.org1IntroductionGenerative AI(GenAI)holds the potential to transform economies and societies.Taking traditionalAIs predictive power one step further,generative AI is capable of creating new content in all for
13、msof media-text,code,images,audio,video,and more.Generative AI tools like ChatGPT,Co-Pilot,and Midjourney are expected to revolutionize how certain tasks are performed,leading to significantefficiency gains and new opportunities for innovation(Eloundou,Manning,Mishkin,and Rock 2023;Humlum and Vester
14、gaard 2024).Since the debut of ChatGPT in November 2022,various types ofgenerative AI tools have proliferated and many have amassed a huge user base within record time.The widespread use of generative AI offers the possibility to transform economic development,socialstructures,and global competitive
15、ness.Despite extensive discussions about the applications andpotentials of generative AI on societies(Korinek 2023;Chui,Hazan,Roberts,Singla,and Smaje2023;Brynjolfsson,Li,and Raymond 2023;Jha,Qian,Weber,and Yang 2024;Kim,Muhn,andNikolaev 2024),research on the scale of generative AI usage is rare.Thi
16、s paper seeks to unveil thereal-time global scale of generative AI usage,including its demographic and country distribution,and to explore the barriers to and impacts of its adoption.As these technologies continue to evolve,understanding their adoption patterns,both in advanced and developing econom
17、ies,becomes crucialfor policymakers,businesses,and researchers.To measure AI adoption globally,several organizations have been publishing AI indexes andreports,tracking trends in AI development,and focusing on assessing countries readiness for AIintegration.Since 2017,Stanford University has been pu
18、blishing the AI Index Report(Maslej,Fattorini,Perrault,et al.2024)annually,providing a comprehensive overview of developmentsin AI research,investment,technology performance,education,and governance.Tortoise Mediaalso publishes the Global AI Index to benchmark 62 countries performance on AI innovati
19、on,investment,and implementation.The Government AI Readiness Index 2023 by Oxford Insightsranks countries on their readiness to integrate AI into government operations across 193 economies.The IMFs recent report emphasizes AIs transformative potential for labor markets and the needfor AI readiness,h
20、ighlighting the necessity of robust digital infrastructure and skilled workforces inadvanced economies,alongside the challenges faced by less developed countries(IMF 2024).Mostof these reports and indexes focus on the supply side of AI,offer limited coverage of developing2countries,and often lack sp
21、ecific emphasis on generative AI technologies.Tracking the usage of generative AI tools is a crucial first step in understanding their eco-nomic and social implications.Despite progress in connecting more people to the internet,themulti-faceted digital divide is widening both within and between econ
22、omies,amplifying disparitiesin productivity and consumer welfare(Sorbe,Gal,Nicoletti,and Timiliotis 2019).Applying in-novative data to summarize stylized facts is fundamental.This includes understanding the typesof users and economies that are leading in generative AI adoption,those that are lagging
23、,howpeople are using generative AI tools,and the underlying factors driving these trends.Such insightsare essential for policymakers,businesses,and researchers to make informed decisions and fosterequitable development in the AI landscape and the broader economy.However,there is a glaring data gap i
24、n monitoring the diffusion and adoption of generativeAI,especially in developing countries.Tracking AI adoption is challenging due to several factors.First,conducting comprehensive and representative surveys on AI usage is both time-consumingand expensive,often requiring extensive timelines to gathe
25、r and analyze data.Many surveys arealso one-off and not comparable over time or across countries.For instance,a survey conducted byHumlum and Vestergaard(2024)in Denmark reveals widespread usage,with half of the surveyedworkers reporting they use ChatGPT.This adoption has led to significant time sav
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