Huiling Ding
Publications
- Theorizing knowledgescape as a transnational mediating force: Artificial intelligence and global flows , GLOBAL MEDIA AND COMMUNICATION (2024)
- Tools, Potential, and Pitfalls of Social Media Screening: Social Profiling in the Era of AI-Assisted Recruiting , JOURNAL OF BUSINESS AND TECHNICAL COMMUNICATION (2023)
- A network analysis of cross-occupational skill transferability for the hospitality industry , International Journal of Contemporary Hospitality Management (2021)
- Boundary of Content Ecology: Chatbots, User Experience, Heuristics, and Pedagogy , SIGDOC'19: PROCEEDINGS OF THE 37TH ACM INTERNATIONAL CONFERENCE ON THE DESIGN OF COMMUNICATION (2019)
- Development of Technical Communication in China: Program Building and Field Convergence , TECHNICAL COMMUNICATION QUARTERLY (2019)
- Constructing HIV/AIDS on the internet: A comparative rhetorical analysis of online narratives in the United States and in China , International Journal of Communication (2014)
- Intercultural Rhetoric and Professional Communication: Technological Advances and Organizational Behavior , Technical Communication Quarterly (2014)
- Rhetoric of global epidemic: Transcultural communication about SARS , (2014)
- Transnational Quarantine Rhetorics: Public Mobilization in SARS and in H1N1 Flu , Journal of Medical Humanities (2014)
- 360-Degree Rhetorical Analysis of Job Hunting: A Four-Part, Multimodal Project , BUSINESS AND PROFESSIONAL COMMUNICATION QUARTERLY (2013)
Grants
The overall goal of this Phase 1 Convergence Accelerator (C-Accel) proposal is to develop what we know to be the first public-facing AI platform that assists individual workers and small employers with upskilling and career changes in a labor market increasingly characterized by automation, technological disruption, and AI recruiting. It will address key challenges faced by employees and employers in occupations most impacted by AI with labor market research, credential gap diagnostics, and support for job search and retraining in AI recruiting. Focusing on manufacturing in Phase I, we will develop and build support for an occupation predicted to lose about 20% jobs to automation by 2026, namely, machine operation hiring mostly male non-college workers. Exploring retraining resources, job search strategies in AI recruiting, and reemployment opportunities in related occupations requiring complementary skills, we aim to assist manufacturing workers with upskilling and retraining while developing educational materials to help prepare young generations for future jobs. Our innovative solution will be scaled up to a wide range of occupations and retraining programs in Phase II.