Organizations’ hiring processes are increasingly shaped by various digital tools and e-recruitment systems. However, there is little understanding of the recruiters’ needs for and expectations towards new systems. This paper investigates recruitment chatbots as an emergent form of e-recruitment, offering a low-threshold channel for recruiter-applicant interaction. The rapid spread of chatbots and the casual nature of their user interfaces raise questions about the perceived benefits, risks, and suitable roles in this sensitive application area. To this end, we conducted 13 semi-structured interviews, including 11 interviews with people who are utilizing recruitment chatbots and two people from companies that are developing recruitment chatbots. The findings provide a qualitative account of their expectations and motivations, early experiences, and perceived opportunities regarding the current and future use of chatbots in recruitment. While chatbots answer the need for attracting new candidates, they have also introduced new challenges and work tasks for the recruiters. The paper offers considerations that can help to redesign recruitment bots from the recruiter’s viewpoint.
Artificial intelligence (AI) is embedded in a wide variety of Smart City applications and infrastructures, often without the citizens being aware of the nature of their “intelligence”. AI can affect citizens’ lives concretely, and thus, there may be uncertainty, concerns, or even fears related to AI. To build acceptable futures of Smart Cities with AI-enabled functionalities, the Human-Centered AI (HCAI) approach offers a relevant framework for understanding citizen perceptions. However, only a few studies have focused on clarifying the citizen perceptions of AI in the context of smart city research. To address this gap, we conducted a two-phased study. In the pre-study, we explored citizen perceptions and experiences of AI with a short survey (N = 91). Second, scenario-based interviews (N = 7) were utilized to gain in-depth insights of citizen perceptions of AI in the Smart City context. Five central themes were recognized: (1) I don’t like them monitoring me, (2) I want maximum gain for minimum effort, (3) I don’t want AI to mimic people, (4) I’ll avoid using AI if I consider the risk too high, and (5) I don’t need to be concerned about AI. These offer an idea of human-centered requirements worth considering while designing AI applications for future Smart Cities.
The practices of organizational talent acquisition are rapidly transforming as a result of the proliferation of information systems that support decision-making, ranging from applicant tracking systems to recruitment chatbots. As part of human resource management (HRM), talent acquisition covers recruitment and team-assembly activities and is allegedly in dire need for digital aid. We analyze the pitfalls and tensions of digitalization in this area through a lens that builds on the interdisciplinary literature related to digital ethics. Using three relevant landmark papers, we analyzed qualitative data from 47 interviews of HRM professionals in Finland, including team-assembly facilitators and recruitment experts. The analysis highlights 14 potential tensions and pitfalls, such as the tension between requesting detailed data versus respecting privacy and the pitfall of unequal treatment across application channels. We identify that the values of autonomy, fairness and utility are often especially at risk of being compromised. We discuss the tendency of the binary considerations related to human and automated decision making, and the reasons for the incompatibility between current digital systems and organizations’ needs for talent acquisition.
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