Pablo Dorta-González , Alexis Jorge López-Puig , María Isabel Dorta-González , Sara M. González-Betancor
{"title":"研究人员在工作中使用生成式人工智能:性别、职业阶段、工作场所类型和感知障碍的影响","authors":"Pablo Dorta-González , Alexis Jorge López-Puig , María Isabel Dorta-González , Sara M. González-Betancor","doi":"10.1016/j.tele.2024.102187","DOIUrl":null,"url":null,"abstract":"<div><p>The integration of generative artificial intelligence technology into research environments has become increasingly common in recent years, representing a significant shift in the way researchers approach their work. This paper seeks to explore the factors underlying the frequency of use of generative AI amongst researchers in their professional environments. As survey data may be influenced by a bias towards scientists interested in AI, potentially skewing the results towards the perspectives of these researchers, this study uses a regression model to isolate the impact of specific factors such as gender, career stage, type of workplace, and perceived barriers to using AI technology on the frequency of use of generative AI. It also controls for other relevant variables such as direct involvement in AI research or development, collaboration with AI companies, geographic location, and scientific discipline. Our results show that researchers who face barriers to AI adoption experience an 11 % increase in tool use, while those who cite insufficient training resources experience an 8 % decrease. Female researchers experience a 7 % decrease in AI tool usage compared to men, while advanced career researchers experience a significant 19 % decrease. Researchers associated with government advisory groups are 45 % more likely to use AI tools frequently than those in government roles. Researchers in for-profit companies show an increase of 19 %, while those in medical research institutions and hospitals show an increase of 16 % and 15 %, respectively. This paper contributes to a deeper understanding of the mechanisms driving the use of generative AI tools amongst researchers, with valuable implications for both academia and industry.</p></div>","PeriodicalId":48257,"journal":{"name":"Telematics and Informatics","volume":"94 ","pages":"Article 102187"},"PeriodicalIF":7.6000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0736585324000911/pdfft?md5=d90070ae12caa2325005060f62c919ba&pid=1-s2.0-S0736585324000911-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Generative artificial intelligence usage by researchers at work: Effects of gender, career stage, type of workplace, and perceived barriers\",\"authors\":\"Pablo Dorta-González , Alexis Jorge López-Puig , María Isabel Dorta-González , Sara M. González-Betancor\",\"doi\":\"10.1016/j.tele.2024.102187\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The integration of generative artificial intelligence technology into research environments has become increasingly common in recent years, representing a significant shift in the way researchers approach their work. This paper seeks to explore the factors underlying the frequency of use of generative AI amongst researchers in their professional environments. As survey data may be influenced by a bias towards scientists interested in AI, potentially skewing the results towards the perspectives of these researchers, this study uses a regression model to isolate the impact of specific factors such as gender, career stage, type of workplace, and perceived barriers to using AI technology on the frequency of use of generative AI. It also controls for other relevant variables such as direct involvement in AI research or development, collaboration with AI companies, geographic location, and scientific discipline. Our results show that researchers who face barriers to AI adoption experience an 11 % increase in tool use, while those who cite insufficient training resources experience an 8 % decrease. Female researchers experience a 7 % decrease in AI tool usage compared to men, while advanced career researchers experience a significant 19 % decrease. Researchers associated with government advisory groups are 45 % more likely to use AI tools frequently than those in government roles. Researchers in for-profit companies show an increase of 19 %, while those in medical research institutions and hospitals show an increase of 16 % and 15 %, respectively. This paper contributes to a deeper understanding of the mechanisms driving the use of generative AI tools amongst researchers, with valuable implications for both academia and industry.</p></div>\",\"PeriodicalId\":48257,\"journal\":{\"name\":\"Telematics and Informatics\",\"volume\":\"94 \",\"pages\":\"Article 102187\"},\"PeriodicalIF\":7.6000,\"publicationDate\":\"2024-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0736585324000911/pdfft?md5=d90070ae12caa2325005060f62c919ba&pid=1-s2.0-S0736585324000911-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Telematics and Informatics\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0736585324000911\",\"RegionNum\":2,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Telematics and Informatics","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0736585324000911","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
Generative artificial intelligence usage by researchers at work: Effects of gender, career stage, type of workplace, and perceived barriers
The integration of generative artificial intelligence technology into research environments has become increasingly common in recent years, representing a significant shift in the way researchers approach their work. This paper seeks to explore the factors underlying the frequency of use of generative AI amongst researchers in their professional environments. As survey data may be influenced by a bias towards scientists interested in AI, potentially skewing the results towards the perspectives of these researchers, this study uses a regression model to isolate the impact of specific factors such as gender, career stage, type of workplace, and perceived barriers to using AI technology on the frequency of use of generative AI. It also controls for other relevant variables such as direct involvement in AI research or development, collaboration with AI companies, geographic location, and scientific discipline. Our results show that researchers who face barriers to AI adoption experience an 11 % increase in tool use, while those who cite insufficient training resources experience an 8 % decrease. Female researchers experience a 7 % decrease in AI tool usage compared to men, while advanced career researchers experience a significant 19 % decrease. Researchers associated with government advisory groups are 45 % more likely to use AI tools frequently than those in government roles. Researchers in for-profit companies show an increase of 19 %, while those in medical research institutions and hospitals show an increase of 16 % and 15 %, respectively. This paper contributes to a deeper understanding of the mechanisms driving the use of generative AI tools amongst researchers, with valuable implications for both academia and industry.
期刊介绍:
Telematics and Informatics is an interdisciplinary journal that publishes cutting-edge theoretical and methodological research exploring the social, economic, geographic, political, and cultural impacts of digital technologies. It covers various application areas, such as smart cities, sensors, information fusion, digital society, IoT, cyber-physical technologies, privacy, knowledge management, distributed work, emergency response, mobile communications, health informatics, social media's psychosocial effects, ICT for sustainable development, blockchain, e-commerce, and e-government.