AI Safety Atlas Ch.2 — Introduction
Source: Risks — Introduction | ai-safety-atlas.com/chapters/v1/risks/introduction/
The chapter introduction establishes the framework for understanding AI risks: capability advancement creates larger-scale risks, and a systematic categorization is needed to analyze them. The chapter argues “isolated safety measures often prove insufficient” — risks combine across categories and severity levels.
Two-Dimensional Framework
By Cause (see risk-decomposition)
- Misuse risks — humans deliberately use AI for harmful purposes (bioweapons, cyber attacks, autonomous weapons)
- Misalignment risks — AI systems pursuing objectives conflicting with human intentions (specification gaming, deceptive alignment)
- Systemic risks — emergent harms from AI integration into broader systems (power concentration, mass unemployment, epistemic degradation, value lock-in)
By Severity
- Individual harms — specific people affected
- Catastrophic — large populations affected, recovery possible
- Existential — human extinction or permanent civilizational collapse
Risk Amplifiers
The introduction lists factors that increase both likelihood and severity of all risk categories — the building blocks of the risk-amplifiers concept page:
- Competitive race dynamics pressuring unsafe deployment
- Accidents from complex system interactions
- Corporate prioritization of profits over safety
- Coordination failures preventing collective action
- Unpredictable capability emergence outpacing safety measures
Connection to Wiki
This intro connects directly to the wiki’s existing risk-landscape pages:
- ai-takeover-scenarios — pathways for misalignment risks reaching existential severity
- ai-population-explosion — Karnofsky’s systemic-risk framing prefigures the Atlas’s systemic category
- near-term-harms-vs-x-risk — the severity dimension exactly parallels this debate
- 2501.04064v1 — Swoboda et al.’s rebuttal of the “Distraction” / “Human Frailty” / “Checkpoints” arguments operates within this same frame