Labor market
The labor market can face challenges from generative AI. As mentioned earlier, generative AI could be applied in a wide range of applications in many industries, such as education, healthcare, and advertising. In addition to increasing productivity, generative AI can create job displacement in the labor market (Zarifhonarvar, 2023). A new division of labor between humans and algorithms is likely to reshape the labor market in the coming years. Some jobs that are originally carried out by humans may become redundant, and hence, workers may lose their jobs and be replaced by algorithms (Pavlik, 2023). On the other hand, applying generative AI can create new jobs in various industries (Dwivedi et al., 2023). To stay competitive in the labor market, reskilling is needed to work with and collaborate with AI and develop irreplaceable advantages (Zarifhonarvar, 2023).
ENTITY
1 - Human
INTENT
1 - Intentional
TIMING
2 - Post-deployment
Risk ID
mit549
Domain lineage
6. Socioeconomic and Environmental
6.2 > Increased inequality and decline in employment quality
Mitigation strategy
1. Strategic Investment in Human-AI Complementarity Skills: Allocate substantial resources towards continuous education and training programs focused on cultivating skills that exhibit complementarity with generative AI, such as critical thinking, ethical reasoning, and high-level domain expertise, to facilitate worker adaptation and leverage AI for productivity gains. 2. Implementation of Proactive Labor Market Policy: Establish dedicated public funding mechanisms (e.g., an AI Worker Training Fund) and regulatory incentives to encourage firms to prioritize the reskilling of existing employees for augmented, AI-enabled roles over workforce reduction, thereby actively mitigating mass displacement. 3. Enhancement of Organizational Transparency and Worker Voice: Mandate clear, consistent corporate communication detailing the specific impact of generative AI adoption on job roles—delineating which tasks will be automated versus augmented—and formalize pathways for worker representation and input in the design and implementation of AI systems to address job security concerns.