The Effects of Labor Relations Institutions and Generative AI on Job Attraction: An Inter-Industry Experiment
This study examines how job seekers respond to generative AI (GenAI) expectations communicated in job advertisements. Specifically, it asks whether organizational characteristics— such as union presence, labor-management partnerships and strong cultures of employee voice and fairness—make prospective hires more receptive to roles that require GenAI use. The project also investigates the mechanisms behind these reactions: do perceptions of voice, fairness, and job security explain how job seekers respond to GenAI expectations? And do these patterns shift across industries and roles that face different levels of automation risk? By clarifying how labor relations institutions shape attitudes toward emerging technology, the study aims to help organizations develop more effective recruitment strategies in an AI-driven labor market.
John McCarthy, Global Labor and Work, Cornell ILR
Michael Maffie, Cornell Peter and Stephanie Nolan, School of Hotel Administration
AI and Worker Voice Convening
The AI and Worker Voice Convening will bring together researchers, labor advocates, and practitioners in Fall 2026 to examine how artificial intelligence (AI) is reshaping work across sectors and to share the strategies that workers, unions, and advocates are using to assert worker voice in AI governance. While AI is often promoted as improving efficiency and decision-making, its impacts on job quality, worker voice, and employment conditions raise important concerns. This convening will foster cross-sector dialogue on organizing, bargaining, and policy strategies that protect workers’ interests, particularly in industries facing funding pressures and workforce shortages. By centering worker perspectives in conversations about AI governance, the convening aims to advance equitable, democratic, and worker-informed approaches to AI implementation.
Host: Zoë West, Worker Institute, Cornell ILR
Committee Members:
Virgina Doellgast, ILR School
Alexandra Mateescu, Data & Society
Joy Ming, SUNY Buffalo
Aiha Nguyen, Data & Society
Sanjay Pinto, Worker Institute fellow
The Role of Creativity Biases in Shaping Human-AI Collaboration and Creativity at Work
The Role of Creativity Biases in Shaping Human-AI Collaboration and Creativity at Work explores how artificial intelligence tools, such as ChatGPT, can transform creative work processes. While generative AI can enhance individual creativity, research suggests it may also reduce idea diversity across groups. This project investigates how well‑documented creativity and decision-making biases influence how workers engage with AI during idea generation. Through a series of experiments, we test whether these biases persist in AI‑assisted contexts and whether AI systems can be designed to mitigate them. By identifying how psychological biases shape human-AI collaboration, this research aims to inform the development of AI tools that promote both individual creativity and collective idea diversity in the workplace.
Brian Lucas, Organizational Behavior, Cornell ILR
Rene Kizilcec, Information Science, Cornell Bowers CIS
