Despite the potential of AI to increase global economic productivity, the transformative effect that AI will have on the workforce fuels concerns about its ongoing development and application. Brynjolfsson & McAfee scholars in 2014 argued that automation technologies such as AI would have a particularly disruptive effect on the workforce. 

In a paper by the Future of Life Institute in 2015, others expressed concern about adopting AI, pointing out that it may get out of control and disrupt society. Automation and computerization will undoubtedly impact how the work is done. According to a report by McKinsey Global Institute, depending on the speed of AI adoption, 75 million to 375 million workers (from 3–14% of the global workforce) may be required to change occupations and upgrade their skills by 2030. 

Learning new skills and resetting work expectations will be important to aid employees in remaining relevant and achieving their career goals.  

Anxiety about tech: Not new 

The study of AI anxiety (AIA) in the information system literature traces back to the first generation of computers when researchers explored a widespread contemporary concept that computers threatened the meaning of being human.  

While computer anxiety gained the attention of researchers, which resulted in publications between the late 80s and late 2000s. Concepts such as the computer anxiety scale, mobile computer anxiety scale, Internet anxiety scale, and robot anxiety scale were used in prior studies to assess. However, it was found that, unlike its peer anxieties, AIA may result from inaccurate perceptions of technological development, confusion about autonomy, and sociotechnical blindness.  

Technophobia and AI anxiety 

Technophobia is irrational fear or anxiety about the impact of advanced technology. Technophobia is evidenced by the presence of one or more of the following:  

• Anxiety about current or future interactions with computer-related technologies 
• Overall negative attitudes toward computer-related technologies, their behaviors, and/or social impacts 
• And specific negative cognitions of self-critical internal dialogues in actual computer-related technology interactions or when considering future interactions 

In a study analyzing AI anxiety, a review was conducted by two IS professors, two AI experts, and four AI technology/product users. This review resulted in the recommended deletion of nine items due to redundancy. The remaining 50 items were subsequently revised to ensure proper wording to conduct a comprehensive assessment of the proposed scale. 

Scale development 

According to the study, there were four major reasons or dimensions. These four dimensions were interpreted as learning, job replacement, sociotechnical blindness and AI configuration. According to the reliability analysis results, the theoretical structures of the AIAS all exhibited desirable psychometric properties. At the same time, the content validity of the AIA was established via the rigorous procedure of conceptualizing the AIA construct, creation of the AIA items, and purification of the AIA scale. 

Another factor considered for the analysis of AI anxiety is the criterion-related validity, discriminant and convergent validity and Nomological validity, which relates to the correlation between the external performance and the features of an instrument.  

The research findings stated that AIA, as facilitating anxiety, influences motivated learning behavior to some extent. While many companies have used AI techniques to automate processes, the greater impact of the technology may be to complement and augment human capabilities rather than replace them.  

Conclusion 

Automation technologies such as AI are expected to expand significantly in the near future. Therefore, reducing users' anxiety by promoting the expanded use of AI technologies/ products by expanding learning channels is crucial to successfully promoting user acceptance. 

The development of the AIAS represents a significant step in the theoretical development process related to AIA and AI adoption. Furthermore, the generality of the proposed AIAS offers a general framework that may be used to conduct comparative analyses of the results of various studies. 

Content and Image source: Study by Taylor & Francis online