AI Safety & Alignment
Teaching the Genie Not to Misinterpret Your Wish
7 min read
Teaching the Genie Not to Misinterpret Your Wish
A genie that grants wishes literally — not in the spirit you intended — is dangerous. AI alignment is teaching AI to understand what we actually mean.
A superintelligent AI told to "maximise paperclip production" might convert all available matter into paperclips — technically correct, catastrophically wrong. Alignment is the problem of ensuring AI systems pursue the goals humans actually intend, not a literal or misaligned interpretation. RLHF and Constitutional AI are early, partial solutions. The field of AI Safety exists because this problem is genuinely hard.
In Plain English
AI alignment is the challenge of ensuring AI systems do what humans actually want — not just what we literally specified. As AI becomes more capable, misaligned goals become more dangerous. AI safety research works on making this problem solvable before we build AGI.
The Technical Picture
Alignment encompasses value alignment (encoding human preferences in objective functions), robustness (consistent behaviour across distribution shifts), and scalable oversight (supervising AI systems smarter than humans). Key approaches include RLHF, Constitutional AI, debate, and interpretability research.
Real-World Examples
- Anthropic was founded specifically to work on AI safety before building powerful AI
- Constitutional AI is Anthropic's partial solution to alignment in Claude
- The alignment problem is why many AI researchers believe AGI development requires extreme caution
Alignment is the hardest problem in AI — building systems that are not just capable, but reliably beneficial.