The basic argument for supporting the acceleration of AI conceptual reasoning capabilities

Emery Cooper of Redwood Research wrote an article arguing that AI's conceptual reasoning capabilities should be accelerated differentially, that is, tasks that are similar to philosophy, difficult to verify directly, and advanced mainly through argumentation. The article holds that important work such as alignment cannot do without this kind of reasoning, whereas AI R&D and takeover depend on it far less, so accelerating it helps safety work more than it helps general capabilities. The author states that default training is dominated by easily verifiable tasks and companies lack commercial incentives, so conceptual reasoning is easily overlooked; their experiments show that few-shot prompting and small-scale training can improve models by three to twelve months on their conceptual argumentation benchmark LMCA. The author expects such work to spill over little into general capabilities; at present it mainly produces conceptual reasoning datasets and benchmarks, released through the Conceptual Reasoning Index website, with priority directions including technical AI safety, decision theory and safe Pareto improvements, and is recruiting researchers to participate.