AI Safety
Also known as: AI Alignment, Safe AI, Beneficial AI
Research and practices aimed at ensuring AI systems behave as intended and don't cause unintended harm, from near-term risks to existential concerns.
AI safety encompasses efforts to ensure AI systems are beneficial, controllable, and aligned with human values—spanning immediate and long-term risks.
Risk Categories
Near-term:
- Bias and discrimination
- Misinformation at scale
- Job displacement
- Privacy violations
- Autonomous weapons
Long-term:
- Misaligned superintelligence
- Loss of human control
- Concentration of power
- Unintended optimization
Research Areas
- Alignment: Making AI pursue intended goals
- Interpretability: Understanding model decisions
- Robustness: Handling edge cases safely
- Governance: Institutional controls
- Evaluation: Measuring safety properties
Key Organizations
- Anthropic, OpenAI (safety teams)
- Center for AI Safety
- Machine Intelligence Research Institute (MIRI)
- Center for Human-Compatible AI (CHAI)
Debate
Disagreement exists on which risks matter most, whether existential risk is imminent, and how to balance safety with capability development.