Year: 2019
Type: preprint
Abstract: We report on experiences with implementing conversational agents in the recruitment domain based on a machine learning (ML) system. Recruitment chatbots mediate communication between job-seekers and recruiters by exposing ML data to recruiter teams. Errors are difficult to understand, communicate, and resolve because they may span and combine UX, ML, and software issues. In an effort to improve organizational and technical transparency, we came to rely on a key contact role. Though effective for design and development, the centralization of this role poses challenges for transparency in sustained maintenance of this kind of ML-based mediating system.
Source: arXiv (Cornell University)
Authors: Kuksenok, Kit, Praß, Nina
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2943986526