Competitive pressures in GPAI product release
In competitive situations, developers of general-purpose AI systems might cut corners on the safety evaluation of their GPAI model and instead spend more time and effort on the capabilities of those systems [183, 69]. This is especially dangerous if the capabilities of such AI systems are correlated with the risk they pose [162].
ENTITY
1 - Human
INTENT
1 - Intentional
TIMING
3 - Other
Risk ID
mit1168
Domain lineage
6. Socioeconomic and Environmental
6.4 > Competitive dynamics
Mitigation strategy
1. Enforce Proportional and Continuous Systemic Risk Management: Implement a comprehensive, lifecycle-wide risk assessment and mitigation framework, requiring continuous systemic risk evaluation and proportionate safety measures as outlined in regulatory guidance (e.g., EU AI Act obligations for General-Purpose AI with systemic risk). This ensures that safety is an integrated and non-optional part of development, resisting the pressure to cut corners. 2. Mandate Rigorous Independent External Evaluation: Require the use of state-of-the-art, independent model evaluations and adversarial testing (red-teaming) to rigorously assess systemic risks and high-impact capabilities before and after market placement, ensuring that the evaluation's depth is not compromised by competitive timelines. 3. Establish Independent Safety Governance and Accountability: Formalize governance structures with dedicated, independent oversight (separate from capability development teams) and establish clear accountability for defining and meeting safety and security metrics to embed a risk-aware culture that views governance as a strategic enabler rather than a bureaucratic obstacle.