OpenAI 最近发布了一份报告，清晰地指出了哪些职场技能在 AI 时代可能变得最有价值。
OpenAI recently published one of the clearest signals yet about which workplace skills may become most valuable in the AI era. In a report on how its researchers use AI, the company shared data showing which tasks are being absorbed by AI and which still rely on people. The biggest automation gains this year came in coding, technical support, monitoring computer runs, and analyzing results. By contrast, AI is still doing relatively little work deciding what projects to pursue, where to invest resources, or how to set priorities. This offers a glimpse of where the value of work may shift. Companies can measure whether code was written, products shipped, or bugs fixed, making those tasks easier to automate. Deciding what should be built in the first place is harder. It requires judgment, context, tradeoffs, and a willingness to take risks. As OpenAI put it: "People still set our research priorities, judge which ideas and results to pursue, and decide whether to scale, pause, or deploy systems." In other words, the future of human work may shift away from execution and toward making the right decisions. here. Reach out to me via email at abarr@businessinsider.com
该报告基于其研究人员如何使用 AI 的数据，展示了哪些任务正被 AI 接管，而哪些任务仍依赖人类。
OpenAI recently published one of the clearest signals yet about which workplace skills may become most valuable in the AI era. In a report on how its researchers use AI, the company shared data showing which tasks are being absorbed by AI and which still rely on people. The biggest automation gains this year came in coding, technical support, monitoring computer runs, and analyzing results. By contrast, AI is still doing relatively little work deciding what projects to pursue, where to invest resources, or how to set priorities. This offers a glimpse of where the value of work may shift. Companies can measure whether code was written, products shipped, or bugs fixed, making those tasks easier to automate. Deciding what should be built in the first place is harder. It requires judgment, context, tradeoffs, and a willingness to take risks. As OpenAI put it: "People still set our research priorities, judge which ideas and results to pursue, and decide whether to scale, pause, or deploy systems." In other words, the future of human work may shift away from execution and toward making the right decisions. here. Reach out to me via email at abarr@businessinsider.com
今年自动化程度提升最大的领域包括编程、技术支持、监控计算机运行以及分析结果。
OpenAI recently published one of the clearest signals yet about which workplace skills may become most valuable in the AI era. In a report on how its researchers use AI, the company shared data showing which tasks are being absorbed by AI and which still rely on people. The biggest automation gains this year came in coding, technical support, monitoring computer runs, and analyzing results. By contrast, AI is still doing relatively little work deciding what projects to pursue, where to invest resources, or how to set priorities. This offers a glimpse of where the value of work may shift. Companies can measure whether code was written, products shipped, or bugs fixed, making those tasks easier to automate. Deciding what should be built in the first place is harder. It requires judgment, context, tradeoffs, and a willingness to take risks. As OpenAI put it: "People still set our research priorities, judge which ideas and results to pursue, and decide whether to scale, pause, or deploy systems." In other words, the future of human work may shift away from execution and toward making the right decisions. here. Reach out to me via email at abarr@businessinsider.com
相比之下，AI 在决定追求哪些项目、资源投向何处或如何设定优先级方面所起的作用相对较小。这让我们得以窥见工作价值可能发生转移的方向。
OpenAI recently published one of the clearest signals yet about which workplace skills may become most valuable in the AI era. In a report on how its researchers use AI, the company shared data showing which tasks are being absorbed by AI and which still rely on people. The biggest automation gains this year came in coding, technical support, monitoring computer runs, and analyzing results. By contrast, AI is still doing relatively little work deciding what projects to pursue, where to invest resources, or how to set priorities. This offers a glimpse of where the value of work may shift. Companies can measure whether code was written, products shipped, or bugs fixed, making those tasks easier to automate. Deciding what should be built in the first place is harder. It requires judgment, context, tradeoffs, and a willingness to take risks. As OpenAI put it: "People still set our research priorities, judge which ideas and results to pursue, and decide whether to scale, pause, or deploy systems." In other words, the future of human work may shift away from execution and toward making the right decisions. here. Reach out to me via email at abarr@businessinsider.com
公司可以衡量代码是否已编写、产品是否已发布或错误是否已修复，这使得这些任务更容易实现自动化。
OpenAI recently published one of the clearest signals yet about which workplace skills may become most valuable in the AI era. In a report on how its researchers use AI, the company shared data showing which tasks are being absorbed by AI and which still rely on people. The biggest automation gains this year came in coding, technical support, monitoring computer runs, and analyzing results. By contrast, AI is still doing relatively little work deciding what projects to pursue, where to invest resources, or how to set priorities. This offers a glimpse of where the value of work may shift. Companies can measure whether code was written, products shipped, or bugs fixed, making those tasks easier to automate. Deciding what should be built in the first place is harder. It requires judgment, context, tradeoffs, and a willingness to take risks. As OpenAI put it: "People still set our research priorities, judge which ideas and results to pursue, and decide whether to scale, pause, or deploy systems." In other words, the future of human work may shift away from execution and toward making the right decisions. here. Reach out to me via email at abarr@businessinsider.com
而决定首先要构建什么则更为困难，这需要判断力、背景知识、权衡取舍以及承担风险的意愿。
OpenAI recently published one of the clearest signals yet about which workplace skills may become most valuable in the AI era. In a report on how its researchers use AI, the company shared data showing which tasks are being absorbed by AI and which still rely on people. The biggest automation gains this year came in coding, technical support, monitoring computer runs, and analyzing results. By contrast, AI is still doing relatively little work deciding what projects to pursue, where to invest resources, or how to set priorities. This offers a glimpse of where the value of work may shift. Companies can measure whether code was written, products shipped, or bugs fixed, making those tasks easier to automate. Deciding what should be built in the first place is harder. It requires judgment, context, tradeoffs, and a willingness to take risks. As OpenAI put it: "People still set our research priorities, judge which ideas and results to pursue, and decide whether to scale, pause, or deploy systems." In other words, the future of human work may shift away from execution and toward making the right decisions. here. Reach out to me via email at abarr@businessinsider.com
正如 OpenAI 所言：“人类仍然设定我们的研究优先级，判断要追求哪些想法和结果，并决定是扩大规模、暂停还是部署系统。”换言之，人类工作的未来可能会从执行层面转向做出正确的决策。
OpenAI recently published one of the clearest signals yet about which workplace skills may become most valuable in the AI era. In a report on how its researchers use AI, the company shared data showing which tasks are being absorbed by AI and which still rely on people. The biggest automation gains this year came in coding, technical support, monitoring computer runs, and analyzing results. By contrast, AI is still doing relatively little work deciding what projects to pursue, where to invest resources, or how to set priorities. This offers a glimpse of where the value of work may shift. Companies can measure whether code was written, products shipped, or bugs fixed, making those tasks easier to automate. Deciding what should be built in the first place is harder. It requires judgment, context, tradeoffs, and a willingness to take risks. As OpenAI put it: "People still set our research priorities, judge which ideas and results to pursue, and decide whether to scale, pause, or deploy systems." In other words, the future of human work may shift away from execution and toward making the right decisions. here. Reach out to me via email at abarr@businessinsider.com