Artificial Intelligence in Cybersecurity: A Socio-Technical Framing

Rapid progress in Artificial Intelligence (AI) is presenting both opportunities and threats that promise to be transformative and disruptive to the field of cybersecurity. The current approaches to providing security and safety to users are limited. Online attacks (e.g., identity theft) and data breaches are causing real-world harms to individuals and communities, resulting in financial instability, loss of healthcare benefits, or even access to housing, among other undesirable outcomes. The resulting challenges are expected to be amplified, given the increased capabilities of AI and its deployment in professional, public, and private spheres. As such, there is a need for a new formulation of these challenges that considers the complex social, technical, and environmental dimensions and factors that shape both the opportunities and threats for AI in cybersecurity. Through an exploration and application of the socio-technical approach, which highlights the significance and value of participatory practices, we can generate new ways of conceptualising the challenges of AI in cybersecurity contexts. This paper will identify and elaborate on key issues, in the form of both gaps and opportunities, that need to be addressed by various stakeholders, while exploring substantive approaches to addressing the gaps and capitalizing on the opportunities at the micro/meso/macro levels, which in turn will inform decision-making processes. This paper offers approaches for responding to public interest security, safety, and privacy challenges arising from complex AI in cybersecurity issues in open socio-technical systems.

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Publication Details

Journal
IEEE Transactions on Technology and Society
Published
2024-10-07
DOI
https://doi.org/10.1109/tts.2024.3460740
Citations
6
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
3.16
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article

Artificial Intelligence in Cybersecurity: A Socio-Technical Framing

Kathleen M. Vogel, Katina Michael, Mariana Zafeirakopoulos, Jeremy Pitt
6 citations
IEEE Transactions on Technology and Society
Ethics and Social Impacts of AI
3.16
article

Artificial Intelligence in Cybersecurity: A Socio-Technical Framing

Kathleen M. Vogel, Katina Michael, Mariana Zafeirakopoulos, Jeremy Pitt
article en
6 citations

Abstract

Rapid progress in Artificial Intelligence (AI) is presenting both opportunities and threats that promise to be transformative and disruptive to the field of cybersecurity. The current approaches to providing security and safety to users are limited. Online attacks (e.g., identity theft) and data breaches are causing real-world harms to individuals and communities, resulting in financial instability, loss of healthcare benefits, or even access to housing, among other undesirable outcomes. The resulting challenges are expected to be amplified, given the increased capabilities of AI and its deployment in professional, public, and private spheres. As such, there is a need for a new formulation of these challenges that considers the complex social, technical, and environmental dimensions and factors that shape both the opportunities and threats for AI in cybersecurity. Through an exploration and application of the socio-technical approach, which highlights the significance and value of participatory practices, we can generate new ways of conceptualising the challenges of AI in cybersecurity contexts. This paper will identify and elaborate on key issues, in the form of both gaps and opportunities, that need to be addressed by various stakeholders, while exploring substantive approaches to addressing the gaps and capitalizing on the opportunities at the micro/meso/macro levels, which in turn will inform decision-making processes. This paper offers approaches for responding to public interest security, safety, and privacy challenges arising from complex AI in cybersecurity issues in open socio-technical systems.

IEEE Transactions on Technology and SocietyVol. 6(1)
The University of Sydney (AU), Institute for the Future (US), Imperial College London (GB), Arizona State University (US)
Openalex Percentile: Top 7%
Ethics and Social Impacts of AI
3.16
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