Artificial intelligence (AI) has captured the attention of various actors and is considered to be reshaping business, and being a critical strategic area for nation states. While AI is seen as transformative and disruptive, it has also led to concerns related to job loss, decision-making transparency, and surveillance. AI is, as such, contested, and a vast amount of actors contributes to legitimize and de-legitimize different meanings and implications of AI. The enthusiastic optimism and harsh skepticism of AI may be viewed as controversies over how to interpret AI, which may also continuously shape opportunities for action. Through this Bridging Project we explore how actors from different fields engage in legitimacy work and how it impacts the meanings of AI. Through a computational-driven discourse analysis where we scrape Twitter accounts, consultancy websites, think-tanks and government webpages and use topic modeling to reveal associations, we aim to reveal the multiple meanings of AI.
Our interdisciplinary approach, which combine “soft” competences from organizational analysis with “hard” competences in machine learning and computational text analysis (e.g. topic modelling) allow us to analyze a uniquely large dataset, and show how discourses about AI are being strategically leveraged by multiple actors, and how these actors enable and constrain the technology and each other. This kind of study is unprecedented within the social- and management sciences where the potentials of computational analysis and machine learning are only nascent but increasingly pointed out. Ultimately we expect the interdisciplinary collaboration to enable a novel approach, and important insights that allow us to cover a much larger dataset compared to prior more qualitative document analysis.
Participants:
Kasper Elmholdt, Christoffer Florczak, Jeppe Agger Nielsen (Department of Politics and Society), Roman Jurowetzki & Daniel Hein (AAU Business School), CLAAUDIA.