Centro de Documentação da PJ
Analítico de Periódico
CD 341
Bridging knowledge gap [Recurso eletrónico] : the contribution of employees’ awareness of AI cyber risks comprehensive program to reducing emerging AI digital threats / Amir Schreiber, Ilan Schreiber
Information and Computer Security, Vol. 32, n. 5 (2024), p. 613-635
Ficheiro de 1,8 MB em formato PDF.
INTELIGÊNCIA ARTIFICIAL, TECNOLOGIA, SEGURANÇA INFORMÁTICA, EMPRESA
Purpose – In the modern digital realm, while artificial intelligence (AI) technologies pave the way for unprecedented opportunities, they also give rise to intricate cybersecurity issues, including threats like deepfakes and unanticipated AI-induced risks. This study aims to address the insufficient exploration of AI cybersecurity awareness in the current literature. Design/methodology/approach – Using in-depth surveys across varied sectors (N ¼ 150), the authors analyzed the correlation between the absence of AI risk content in organizational cybersecurity awareness programs and its impact on employee awareness. Findings – A significant AI-risk knowledge void was observed among users: despite frequent interaction with AI tools, a majority remain unaware of specialized AI threats. A pronounced knowledge difference existed between those that are trained in AI risks and those who are not, more apparent among non-technical personnel and sectors managing sensitive information. Research limitations/implications – This study paves the way for thorough research, allowing for refinement of awareness initiatives tailored to distinct industries. Practical implications – It is imperative for organizations to emphasize AI risk training, especially among non-technical staff. Industries handling sensitive data should be at the forefront. Social implications – Ensuring employees are aware of AI-related threats can lead to a safer digital environment for both organizations and society at large, given the pervasive nature of AI in everyday life. Originality/value – Unlike most of the papers about AI risks, the authors do not trust subjective data from second hand papers, but use objective authentic data from the authors’ own up-to-date anonymous survey.
