Ajeya Cotra · Mar 26, 2023
Ajeya Cotra argues alignment is not the same as making AI good
Ajeya Cotra’s article, published March 26, 2023, argues that “alignment” should describe whether AI systems try to do what their designers want, not whether their actions are good for the world. She says this narrower framing could help researchers identify technical problems for experiments, code, and proofs to address, while leaving decisions about what counts as good to society and its institutions. Cotra’s examples distinguish alignment from broader risks: systems could faithfully serve harmful users, contribute to inequality, make high-stakes errors, or be affected by security failures. She also points to questions about who has authority to direct AI and how systems should handle conflicting preferences. In her view, alignment research may reduce some dangers, but it cannot resolve all the political, social, and moral questions involved in building a flourishing future. She expects different intellectual communities to address different parts of that work. The article’s examples describe possible outcomes, not reported events. It leaves open how researchers could develop and evaluate techniques that make powerful AI systems reliably try to follow their designers’ intent, and how society should decide whose intent those systems should serve.
Keep in view: Text as retrieved on October 29, 2026; originally published March 26, 2023. Cotra presents misuse, inequality, errors, and other harms as possible scenarios, not as events shown to have occurred. The article does not specify methods or evaluation results for determining whether powerful AI systems will follow their designers’ intent.
Original source · Added 2026-10-29T15:59:56.906Z