Inteligência Artificial generativa em portais de transparência pública: uma análise da expectativa de desempenho

Abstract

Generative Artificial Intelligence (AI) has brought advances regarding the possibilities of utilizing these technologies in public administration, potentially fostering transparency and social control through various techniques, such as natural language processing and conversational agents, among others. However, for the use of new technologies to be effective, prior studies demonstrating how the population will behave towards these novelties and whether they will effectively use them are recommended. Therefore, this study aims to analyze the main factors that influence the Performance Expectancy in the use of generative artificial intelligence tools in transparency portals. This will be achieved through an adaptation of the UTAUT Model (Unified Theory of Acceptance and Use of Technology), proposed by Venkatesh et al. (2003), by adding the constructs AI Literacy and Trust. The methodology will involve using surveys with a 7-point Likert scale and multiple regression analysis to assess the relationship of each independent variable with the dependent variable. The sampling method employed will be non-probabilistic convenience sampling. The study seeks to answer the research question: Which factors most significantly influence the Performance Expectancy of a Generative Artificial Intelligence tool applied to Transparency Portals?