Influence of artificial intelligence on public employment and its impact on politics: A systematic literature review

Goal:Public administration is constantly changing in response to new challenges, including the implementation of new technologies such as robotics and artificial intelligence (AI). This new dynamic has caught the attention of political leaders who are finding ways to restrain or regulate AI in public services, but also of scholars who are raising legitimate concerns about its impacts on public employment. In light of the above, the aim of this research is to analyze the influence of AI on public employment and the ways politics are reacting. Design / Methodology / Approach: We have performed a systematic literature review to disclose the state-of-the-art and to find new avenues for future research. Results: The results indicate that public services require four kinds of intelligence – mechanical, analytical, intuitive, and empathetic – albeit, with much less expression than in private services. Limitations of the investigation: This systematic review provides a snapshot of the influence of AI on public employment. Thus, our research does not cover the whole body of knowledge, but it presents a holistic understanding of the phenomenon. Practical implications: As private companies are typically more advanced in the implementation of AI technologies, the for-profit sector may provide significant contributions in the way states can leverage public services through the deployment of AI technologies. Originality / Value: This article highlights the need for states to create the necessary conditions to legislate and regulate key technological advances, which, in our opinion, has been done, but at a very slow pace.info:eu-repo/semantics/publishedVersio

More than programming? The impact of AI on work and skills

This chapter explores the ways in which organisational readiness and scientific advances in Artificial Intelligence have been affecting the demand for skills and their training in Australia and other nations leading in the promotion, use or development of AI. The consensus appears that having adequate numbers of qualified data scientists and machine learning experts is critical for meeting the challenges ahead. The chapter asks what this may mean for Australia's education and training system, what needs to be taught and learned, and whether technical skills are all that matter.Comment: Chapter 9 in The Future of Work: Global Trends, Challenges and Policies with an Australian Perspective. Editor: Andreas Cebulla, Routledge. 202

Technol Mind Behav

Although advanced technologies (i.e., artificial intelligence (AI), robots) are often discussed as drivers of societal inequality, our research examines whether people living in more unequal societies tend to view technology as a greater threat to jobs in general. Building from research that societal inequality heightens concerns about status hierarchies and future resource attainment, we anticipated that workers in more unequal societies would tend to view AI/robots as greater threats (e.g., AI/robots as job destroyers). Utilizing the Eurobarometer 87.1 dataset, we found that country inequality, as operationalized via the Gini Index, was positively associated with perceptions that AI/robots pose threats of general job loss. These relationships occurred when controlling for people's perceptions of technological threat to their own personal job, technology skills and interests, and demographics. Moreover, these findings are robust across alternative operationalizations of inequality including the Human Inequality Index and people's subjective perceptions of current and future inequality in their country. These findings advance theory on inequality and suggest that the broader context-both objective and perceived-may play a role in how people view disruption associated with AI/robots at work.T42 OH008438/OH/NIOSH CDC HHSUnited States/T42OH008438/ACL/ACL HHSUnited States