AI, Organizing, and Management
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ItemOpening the Black Box of Music Royalties with the Help of Hybrid Intelligence( 2021-01-05)The ever-increasing complexity of the music industry and the intensified resentment of artists towards collecting societies call for a transformation and a change of behavior within the music ecosystem. This article introduces a hybrid intelligence system, that ameliorates the current situation by combining the intelligence of humans and machines. This study proposes design requirements for hybrid intelligence systems in the music industry. Using a design science research approach, we identify design requirements both inductively from expert interviews and deductively from theory and present a first prototypical instantiation of a respective hybrid intelligence system. Overall, this shall enrich the body of knowledge of hybrid intelligence research by transferring its concepts into a new context. Furthermore, the identified design requirements shall serve as a foundation for researchers and practitioners to further explore and design hybrid intelligence in the music industry, and beyond.
ItemIs AI ready to become a state servant? A case study of an intelligent chatbot implementation in a Scandinavian Public Service( 2021-01-05)Will AI shorten or increase the number of jobs? This question took one of the central places in the service literature debates. On the one hand side, the developers of the AI accentuate the potential of the application to completely imitate human behaviour and overtake all human responsibilities. On the other hand, service workers and researchers emphasize the importance and uniqueness of a “human touch” in service work. To see how AI can affect the jobs of the service workers, we conducted a case study of a public service entity that introduced an intelligent chatbot in its customer centre. Particularly, we looked into how the implementation affects job characteristics (skills variety, task significance, task identity, autonomy, and feedback) of the frontline service workers.
ItemInnovating with Artificial Intelligence: Capturing the Constructive Functional Capabilities of Deep Generative Learning( 2021-01-05)As an emerging species of artificial intelligence, deep generative learning models can generate an unprecedented variety of new outputs. Examples include the creation of music, text-to-image translation, or the imputation of missing data. Similar to other AI models that already evoke significant changes in society and economy, there is a need for structuring the constructive functional capabilities of DGL. To derive and discuss them, we conducted an extensive and structured literature review. Our results reveal a substantial scope of six constructive functional capabilities demonstrating that DGL is not exclusively used to generate unseen outputs. Our paper further guides companies in capturing and evaluating DGL’s potential for innovation. Besides, our paper fosters an understanding of DGL and provides a conceptual basis for further research.
ItemComputer, Whom Should I Hire? – Acceptance Criteria for Artificial Intelligence in the Recruitment Process( 2021-01-05)In the war for talents, the need for appropriate tools to fill open positions with the right talents is becoming increasingly important for employers. AI-based technologies simplify recruiters’ daily work and increase the efficiency of the recruitment process by replacing time-consuming approaches. However, little is known about the reactions of stakeholders to AI-based recruiting. Thus, this paper aims to identify personal and contextual factors that influence the acceptance of AI-based technologies in the recruitment process. Based on the interviews with recruiters, managers, and applicants involved in the recruitment process, we present that transparency, complementary features of the AI tools, and a sense of control play key roles in the acceptance of AI-based technology when used for recruiting. The findings contribute to research on the adoption of AI in the recruitment process and provide recommendations on the use of AI technologies when hiring talents.