Exportar Publicação

A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Anabela da Conceição Pereira (2025). Governing AI in an Age of Global Challenges: A Sociotechnical Reflection of the Ethics of Sensitive Data. Technology in the Face of Global Challenges. ESA RN24/SSTNET Midterm Conference – Faculty of Arts and Humanities, University of Porto, November 26-27, 2025, Porto, Portugal.
Exportar Referência (IEEE) 
A. D. Pereira,  "Governing AI in an Age of Global Challenges: A Sociotechnical Reflection of the Ethics of Sensitive Data", in Technology in the Face of Global Challenges. ESA RN24/SSTNET Midterm Conf. – Faculty of Arts and Humanities, University of Porto, November 26-27, 2025, Porto, Portugal, Porto, 2025
Exportar BibTeX 
@misc{pereira2025_1769201042201,
	author = "Anabela da Conceição Pereira",
	title = "Governing AI in an Age of Global Challenges: A Sociotechnical Reflection of the Ethics of Sensitive Data",
	year = "2025",
	howpublished = "Ambos (impresso e digital)"
}
Exportar RIS 
TY  - CPAPER
TI  - Governing AI in an Age of Global Challenges: A Sociotechnical Reflection of the Ethics of Sensitive Data
T2  - Technology in the Face of Global Challenges. ESA RN24/SSTNET Midterm Conference – Faculty of Arts and Humanities, University of Porto, November 26-27, 2025, Porto, Portugal
AU  - Anabela da Conceição Pereira
PY  - 2025
CY  - Porto
AB  - The rapid adoption of AI technologies, accelerated by world crises such as the COVID-19 pandemic and war(s), has revealed tensions between technological innovation and social ethics. This paper critically examines the use of biometric, personal, and sensitive data in AI systems, with a focus on vulnerabilities related to privacy and consent. We reflect on the role of governance frameworks, including the European Union’s Artificial Intelligence Act, as a regulatory response, and assess their role in mitigating risks associated with current AI systems. Our contribution is the proposal of a model for shared governance that integrates regulation, digital literacy, and corporate and individual responsibility, aiming for more equitable technological innovation. By situating data governance within the sociology of science and technology, this proposition provides a foundational conceptualization of how societies can shape the development of AI to address global challenges in an ethical and just manner.
ER  -