Título:
Engineers' perspectives on the use of generative artificial intelligence tools in the workplace
Otros títulos:
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Director:
Compilador:
Autor:
Joskowicz, José
Slomovitz, Daniel
Slomovitz, Daniel
Tutor:
Tipo de documento:
Preprint
Editor:
Palabras clave:
Artificial intelligence
Surveys
Employment
Chatbots
Companies
Technological innovation
IEEE Regions
AI tools
Future impact
Generative
IEEE member
Surveys
Employment
Chatbots
Companies
Technological innovation
IEEE Regions
AI tools
Future impact
Generative
IEEE member
Descriptores:
Año de publicación:
2024
Contenido:
Resumen:
The integration of artificial intelligence (AI) into the workplace requires commitment not only from the leadership of company directors but, equally important, from the engineers responsible for its implementation. This article presents a survey on perceptions concerning the utilization of AI tools in engineering environments. It was focused on engineers and students in the areas of electricity, electronics, and computing. The questionnaire covered demographic information, AI knowledge level, preferred tools, primary applications, perceived impact, and attitudes toward labor substitution. With the endorsement of the IEEE Uruguay Section and IEEE Region 9, the survey was distributed via email to a diverse group of potential participants, in several countries, including all IEEE members in Region 9. There were 375 replies to the survey, from 20 different countries in the Americas.
Descripción:
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Citación:
Joskowicz, J. y Slomovitz, D. Engineers' perspectives on the use of generative artificial intelligence tools in the workplace [Preprint]. Publicado en: IEEE Engineering Management Review, 2024, vol. 52, no. 1, pp. 258-267. DOI: 10.1109/EMR.2023.3333794.
Citación:
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Otros identificadores:
Cobertura geográfica:
América.
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Departamento académico:
Grupo de investigación:
Licencia:
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
Colecciones:
| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| JS24a.pdf | Preprint | 641.24 KB | Adobe PDF |