aiqbench analysis
This computational study reveals how AI governance responsibilities are increasingly embedded within hybrid privacy roles rather than existing solely in dedicated positions. By analyzing over 1,100 job postings, the research highlights a shift where technical skills and legal knowledge converge to manage emerging AI risks across compliance and security domains. This trend signals a structural evolution in the workforce necessary for scaling responsible AI deployment in enterprise environments.
Who Governs Data in the AI Era? A Computational Analysis of the U.S. Privacy Workforce in Job Postings
arXiv:2609.32030v1 Announce Type: cross Abstract: Privacy protection now spans legal, technical, and managerial duties, and demand for privacy professionals is growing across sectors. However, little is known about how employers define these roles. We analyze 1,143 U.S. privacy job postings from LinkedIn and Indeed. We examine job titles, salaries, competencies, certifications, education, experience, regulatory references, and AI-related language by using rule-based text mining. We also apply Topic Modeling (BERTopic) to the same postings and identify 18 latent themes which we grouped them into four categories. Our findings show that privacy roles are hybrid and they combine legal knowledge, technical skills, and interpersonal competence. Artificial intelligence appears in more than half of postings, with AI language spread across compliance, legal, governance and security themes. Our research indicates that AI governance responsibilities are often embedded within existing privacy roles, contributing to the rise of hybrid positions alongside dedicated AI governance roles.
Title:Who Governs Data in the AI Era? A Computational Analysis of the U.S. Privacy Workforce in Job Postings
Abstract:Privacy protection now spans legal, technical, and managerial duties, and demand for privacy professionals is growing across sectors. However, little is known about how employers define these roles. We analyze 1,143 U.S. privacy job postings from LinkedIn and Indeed. We examine job titles, salaries, competencies, certifications, education, experience, regulatory references, and AI-related language by using rule-based text mining. We also apply Topic Modeling (BERTopic) to the same postings and identify 18 latent themes which we grouped them into four categories. Our findings show that privacy roles are hybrid and they combine legal knowledge, technical skills, and interpersonal competence. Artificial intelligence appears in more than half of postings, with AI language spread across compliance, legal, governance and security themes. Our research indicates that AI governance responsibilities are often embedded within existing privacy roles, contributing to the rise of hybrid positions alongside dedicated AI governance roles.
Computers and Society (cs.CY); Computation and Language (cs.CL); Cryptography and Security (cs.CR)
arXiv:2609.32030 [cs.CY]
(or arXiv:2609.32030v1 [cs.CY] for this version)
https://doi.org/10.48550/arXiv.2609.32030 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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