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CAIL - Critical AI Literacy

    Stefan Strauss

ITA Projektbericht, pp. , 2024/11/25


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doi:10.1553/ITA-pb


Abstract

Artificial intelligence (AI) has become a strong driver behind digitalization in recent years. Prominent and intensively promoted generative AI-tools have been reinforcing the ongoing hype also in the general public. The hype obscures the fact that not everything now called AI is new and that a broad range of different applications already exist. There are continuing debates on the impact of AI-based technologies on labour and the economy and a growing number of companies already apply these technologies in various areas. This technological change affects more and more professions that were previously not involved. On the longer run, many employees have to encounter significant changes in their daily work life.
The specific novelty of AI-based technologies is not the wide range of applications, but basically the new forms of automation that their use entails. The associated change increasingly affects knowledge work, though, yet widely uncertain to what extent. The CAIL research project, funded by the Digitalization Fund of the Viennese Chamber of Labour, thus investigated how practices of knowledge work alter through the use of AI-based technologies and the related new forms of automation and what challenges result from this development. Based on this, approaches for establishing Critical AI Literacy (CAIL) – i.e. critical competence in dealing with AI-based technologies – were developed. This report summarizes the key findings of the research project and particularly addresses the following questions:
‒ What do companies expect from the use of AI?
‒ What are peculiarities of AI-based automation?
‒ How does the use of AI affect practices of knowledge work?
‒ What are corresponding main challenges and problems and how do they relate to the risk of (deep) automation bias?
‒ What are main influencing factors for the constructive use of AI in companies?
‒ What are basic skills of a Critical AI Literacy and what approaches can be used to impart the corresponding knowledge?
Following this introduction, section 1 briefly discusses key expectations, narratives and current usage figures of AI in Austria. The significance and functionality of AI is explained in section 2. Section 3 deals with the question how knowledge work is changing and – based on selected fields of application – utlines
what impact on working practices is already observable. Section 4 explores crucial peculiarities of AI-based automation and explains why (deep) automation bias represents a meta-risk of AI usage. Section 5 identifies and discusses key challenges and problem areas, section 6 addresses the essential aspect of agency, explains the importance of CAIL and outlines – based on the elaborated CAIL framework – how critical AI literacy can be communicated within companies. The subsequent recommendations can support decision-makers in the planning and deployment of AI-based technologies (section 6.2). Section 7 briefly summarizes the key results.