Confiança programável para a Ciência Aberta: alinhar agentes humanos e artificiais mediante incentivos económicos vetoriais
DOI:
https://doi.org/10.82524/recal.2026.179Palavras-chave:
Alinhamento da IA, Captura Escalar, Confiança Programável, Inteligência Artificial, Ciência Aberta e Descentralizada, Incentivos Económicos VetoriaisResumo
A governação da ciência opera dentro de uma arquitetura de incentivos económicos inteiramente denominados em dinheiro fiduciário (FIAT). Porque esta estrutura é, portanto, escalar, as decisões de alocação de recursos exigem que a qualidade científica multidimensional seja reduzida a proxies unidimensionais de desempenho (fator de impacto, índice h, métricas de citação), colapsando dimensões irredutíveis de valor científico num único número. Os agentes de Inteligência Artificial (IA), ao otimizarem computacionalmente os proxies que esta arquitetura recompensa, não corrigem a falha; amplificam-na. Este artigo argumenta que a resposta não reside na regulamentação a posteriori dos comportamentos da IA, mas na reconfiguração das infraestruturas de incentivos. Propõe o conceito de confiança programável, operacionalizado por meio de tecnologias de registo distribuído (DLT), como uma camada de governação na qual a reprodutibilidade, a integridade metodológica, a abertura dos dados e a relevância social operam como dimensões de valor autónomas. A análise de três implementações no domínio da ciência descentralizada (DeSci) revela um arco analítico: o sistema recapturado pela lógica escalar do dinheiro fiduciário (ResearchHub), a resistência arquitetural parcial (VitaDAO) e a infraestrutura de confiança programável não exposta a essa lógica (DeSci Labs/Codex). O artigo conclui que a Ciência Aberta precisa de programar a abertura na camada dos incentivos económicos que determinam a produção e validação do conhecimento, dotando-os de dimensões que o dinheiro fiduciário, enquanto grandeza escalar, não comporta.
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Os dados de análise que sustentam este artigo estão disponíveis em acesso aberto no Zenodo: https://doi.org/10.5281/zenodo.19323751
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Direitos de Autor (c) 2026 Dario Rodrigues (Autor)
Este trabalho encontra-se publicado com a Licença Internacional Creative Commons Atribuição 4.0.
