【文章标题】：What will be left for us to work on 【文章标题】：未来还有什么留给我们去做
【文章正文】： 【文章正文】：
What will be left for us to work on? 未来还有什么留给我们去做？
Abstract 摘要
Given rapid advances in AI, how should researchers and developers shift how we allocate our time? What new skills should we build so that we’re not obsolete in the future? I argue that there will be plenty for us to work on, grounded in the “AI as normal technology” thesis, which holds that there are many bottlenecks between AI capability improvements and automation of tasks or jobs. 鉴于人工智能的快速发展，研究人员和开发者应如何调整我们的时间分配？我们应该培养哪些新技能，以免在未来被淘汰？我认为，基于“AI作为常规技术”的论点，未来仍有大量工作留给我们去做，该论点认为，在AI能力提升与任务或工作自动化之间存在着诸多瓶颈。
The evidence suggests that AI is better seen as an augmentation than an automation technology. The balance of human effort will shift towards tasks that are less verifiable — from developing models to scaffolds, and from building towards evaluation and monitoring. 现有证据表明，与其将AI视为自动化技术，不如将其看作增强技术。人类精力的重心将转向那些较难验证的任务——从开发模型转向搭建支撑框架，从构建系统转向评估与监控。
Over the long term, as purely technical skills are devalued, both researchers and developers will have to adapt. In research, human effort will migrate from problem solving to question asking and conceptual progress; in industry, relational skills, domain knowledge, aesthetic and normative judgment will gain in importance. 从长远来看，随着纯技术技能的贬值，研究人员和开发者都必须做出适应。在研究领域，人类的精力将从解决问题转向提出问题和推动概念性进展；在工业界，人际交往能力、领域知识、审美与规范性判断将变得愈发重要。