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AI-Driven Justice: Investigating the adoption of AI tools in supporting the justice system

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Detalhes bibliográficos
Resumo:With the rapid development of artificial intelligence (AI) systems, their implementation in judicial processes is becoming a reality, offering automation in data collection, case analysis and prediction, despite lacking emotional and empathetic capabilities. To address the lack of holistic studies on public and professional perspectives regarding ‘smart courts’, this study explores the factors driving AI adoption in the justice system and its broader outcomes, addressing both technical and humanistic constructs. Drawing on a quantitative approach, the study employs partial least squares structural equation modeling (PLS-SEM) to evaluate both measurement and structural components of the proposed model. The results show that perceived usefulness, ease of use, trust and job threat significantly influence public attitudes, while ethics-related concerns unexpectedly emerge as non-relevant. The findings aim to provide actionable insights for policymakers to ethically integrate AI into legal systems while safeguarding fairness, trust, and public confidence.
Autores principais:Carmo, Joana Margarida Farinha
Assunto:Artificial Intelligence Justice System Ethics Structural Equation Modeling Technology Adoption Modeling SDG 9 - Industry, innovation and infrastructure SDG 10 - Reduced inequalities SDG 16 - Peace, justice and strong institutions
Ano:2025
País:Portugal
Tipo de documento:dissertação de mestrado
Tipo de acesso:acesso embargado
Instituição associada:Universidade Nova de Lisboa
Idioma:inglês
Origem:Repositório Institucional da UNL
Descrição
Resumo:With the rapid development of artificial intelligence (AI) systems, their implementation in judicial processes is becoming a reality, offering automation in data collection, case analysis and prediction, despite lacking emotional and empathetic capabilities. To address the lack of holistic studies on public and professional perspectives regarding ‘smart courts’, this study explores the factors driving AI adoption in the justice system and its broader outcomes, addressing both technical and humanistic constructs. Drawing on a quantitative approach, the study employs partial least squares structural equation modeling (PLS-SEM) to evaluate both measurement and structural components of the proposed model. The results show that perceived usefulness, ease of use, trust and job threat significantly influence public attitudes, while ethics-related concerns unexpectedly emerge as non-relevant. The findings aim to provide actionable insights for policymakers to ethically integrate AI into legal systems while safeguarding fairness, trust, and public confidence.