Anais
Resumo do trabalho
Estratégia em Organizações · Estratégia Corporativa e de Stakeholders
Título
THE EFFECT OF ARTIFICIAL INTELLIGENCE LITERACY ON STAKEHOLDER ENGAGEMENT
Palavras-chave
AI Literacy
Stakeholder Theory
Stakeholder Management
Agradecimento:
This work was supported by the FAPERGS - Fundação de Amparo à pesquisa do Estado do Rio Grande do Sul under Grant number 24/2551-0001443-8
Autores
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Greici SarturiUNIVERSIDADE FEDERAL DE SANTA MARIA (UFSM)
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Vanessa FaoroUNIVERSIDADE FEDERAL DE SANTA MARIA (UFSM)
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Keysa Manuela Cunha de MascenaUNIVERSIDADE DE FORTALEZA (UNIFOR)
Resumo
Introdução
The accelerated integration of Artificial Intelligence (AI) into organizational processes has fundamentally reshaped the nature of relationships between institutions and their stakeholders (Wang, Rau, & Yuan, 2023). In this context, AI literacy, understood as the ability to comprehend, critically evaluate, and effectively interact with AI systems (Long & Magerko, 2020), emerges as a core competency for fostering meaningful stakeholder engagement.
Problema de Pesquisa e Objetivo
Given the growing presence of AI in public organizations, this study investigates the following question: How do different dimensions of AI literacy influence stakeholder engagement? The aim is to examine the effects of awareness, usage, evaluation, and ethics on overall engagement and its subdimensions: affective commitment, positive affectivity, and empowerment.
Fundamentação Teórica
The theoretical framework is grounded in the concept of AI literacy, encompassing the dimensions of awareness, usage, evaluation, and ethics (Wang et al., 2023). It also draws on stakeholder engagement theory, with a particular focus on public engagement as proposed by Kang (2014), which includes the dimensions of affective commitment, positive affectivity, and empowerment. Based on this foundation, seven hypotheses were formulated linking the dimensions of AI literacy to organizational engagement.
Metodologia
The research was conducted with 61 stakeholders from public universities who attended a lecture on AI. The questionnaire employed adapted scales from Wang et al. (2022) to measure AI literacy and from Kang (2014) to assess engagement. The analysis used ordinary least squares (OLS) regression, with control variables for stakeholder group and length of relationship with the organization.
Análise dos Resultados
The models indicate that critical evaluation of AI is the only dimension with a positive and significant effect on engagement, positive affectivity, and empowerment. In contrast, the ethical dimension showed a negative relationship with affective commitment. Awareness and use did not demonstrate statistical significance in the estimated models.
Conclusão
The results of this study reinforce the centrality of critical evaluation as a key component of AI literacy aimed at public engagement. At the same time, they reveal the limitations of a purely functionalist approach to digital literacy and suggest that the ethical dimension should be addressed with greater sensitivity in civic education policies, given its potential both to empower and to alienate stakeholders from public institutions.
Contribuição / Impacto
The study advances the understanding of the factors that sustain engagement in the public sector. By highlighting the centrality of critical literacy, it contributes to public policies aimed at citizen empowerment, strengthening participatory, reflective, and socially responsible practices in the use of AI.
Referências Bibliográficas
Kang, M. (2014). Understanding public engagement: Conceptualizing and measuring its influence on supportive behavioral intentions. Journal of Public Relations Research, 26(5), 399-416.
Long, D., & Magerko, B. (2020, April). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI conference on human factors in computing systems (p. 1-16).
Wang, B., Rau, P. L. P., & Yuan, T. (2023). Measuring user competence in using artificial intelligence: validity and reliability of artificial intelligence literacy scale. Behaviour & information technology, 42(9), 1324-133.
Long, D., & Magerko, B. (2020, April). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI conference on human factors in computing systems (p. 1-16).
Wang, B., Rau, P. L. P., & Yuan, T. (2023). Measuring user competence in using artificial intelligence: validity and reliability of artificial intelligence literacy scale. Behaviour & information technology, 42(9), 1324-133.