Direct competition with humans
One or more artificial agent(s) could have the capacity to directly outcompete humans, for example through capacity to perform work faster, better adaptation to change, vaster knowledge base to draw from, etc. This may result in human labor becoming more expensive or less effective than artificial labor, leading to redundancies or extinction of the human labor force.
ENTITY
2 - AI
INTENT
1 - Intentional
TIMING
2 - Post-deployment
Risk ID
mit116
Domain lineage
6. Socioeconomic and Environmental
6.2 > Increased inequality and decline in employment quality
Mitigation strategy
1. Implement and enforce regulatory constraints on the total compute used for training and the operational inference speed (FLOP/s) of frontier AI models. These technical capability caps serve as a verifiable, hard backstop to limit the speed and scale of AGI deployment, thereby preventing an autonomous system from achieving the capacity to rapidly and fully displace human labor across multiple sectors before societal and economic adaptations can occur. 2. Establish insulated permeable sandbox architectures for deploying agentic AGI systems, mandating human-in-the-loop (HITL) verification for all high-consequence external outputs, such as financial transactions, code execution, and communications affecting critical infrastructure. This mechanism prevents unchecked autonomous economic action and provides a "Circuit Breaker" to manage the speed and scope of competitive displacement. 3. Develop and implement robust alignment and governance frameworks that legally and technically define the roles, obligations, and access controls of deployed AGI agents. These frameworks must be designed to prevent the emergence of misaligned objectives, such as seeking power or resources, which would aggressively drive outperformance and economic competition against human workers, thereby ensuring AGI functions as an augmentation tool.