AI Risk Signals and Their Implications for Employment and Shared Prosperity

As artificial intelligence (AI) technology continues to evolve, its impact on employment and economic equity remains a pressing concern. The AI and Shared Prosperity Initiative has identified several "Risk Signals" (RS) that highlight how AI systems could negatively affect workers and shared prosperity if not carefully managed. These risk signals fall into three main categories: task-related, market-related, and sourcing-related risks.

Task-Related Risks

RS1: Elimination of Core Job Tasks AI systems can automate tasks that were previously performed by humans. This development can be beneficial, particularly when automating tasks that pose risks to workers’ physical or mental health. However, if AI is primarily used to eliminate core paid tasks without creating new roles or enhancing job quality, it could lead to reduced employment and lower wages. The AI and Shared Prosperity Initiative considers eliminating more than 10% of a job’s core tasks a significant concern.

RS2: Reallocation to Lower-Paid or Precarious Jobs AI can shift tasks from full-time jobs to precarious or informal work arrangements. This trend, often referred to as "gig-ification," separates “time on task” from “idle time,” leading to unpredictable wages and undermining minimum wage protections. In some cases, paid tasks are converted into unpaid roles, such as customers handling self-checkout or automated support.

RS3: Reallocation to Jobs with Different Skill Requirements AI can shift tasks to jobs requiring higher or lower specialized skills. While this can create opportunities, affected workers may lack the skills needed for new roles. Conversely, lowering skill requirements may reduce entry barriers but can also decrease wages and limit career growth.

Market-Related Risks

RS4: Geographic Relocation of Jobs AI can move jobs away from regions with few alternatives, leading to social and economic challenges. Areas that lose stable jobs often experience increased mental health issues, addiction, and economic decline. Displacement can also occur indirectly when technology developed in one region spreads globally.

RS5: Increased Market Concentration AI can increase market concentration, reducing competition and leading to job losses. In monopolistic markets, benefits from AI are often concentrated among a few firms, while workers and consumers see little advantage. This concentration can also affect upstream and downstream industries.

Sourcing-Related Risks

RS6: Reliance on Poorly Treated Outsourced Labor AI development often depends on data enrichment professionals who handle tasks like annotation and classification. These workers often face low pay, inconsistent compensation, long hours, and limited recourse for grievances. A lack of transparency in sourcing practices worsens these conditions.

RS7: Use of Unconsented Training Data Some AI systems are trained on data collected without consent or compensation, exploiting economically valuable know-how. This practice can reduce demand for the original labor, such as artists’ works or drivers’ actions used to train generative and autonomous AI systems.

Conclusion The AI and Shared Prosperity Initiative stresses the importance of proactive measures to mitigate these risks. This includes conducting job impact assessments, retraining programs, and ensuring transparency in AI development. By addressing these concerns, AI can be a force for shared prosperity rather than economic disparity.

source- Guidelines for AI and Shared Prosperity - Partnership on AI

disclaimer- This is non-financial/medical advice and made using AI so could be wrong.