根据利用股市波动来评估人工智能预期影响的经济学家分析，投资者似乎押注人工智能将大幅提升软件工程的生产力。
Investors appear to be betting that AI will deliver substantial gains in software engineering productivity, according to economists who used stock market movements to estimate the technology's expected impact.
来自加州大学伯克利分校（UCB）和伦敦政治经济学院（LSE）的经济学家表示，在2022年11月至2025年12月期间，“人工智能使市场对软件工程生产力的预期现值增加了相当于永久性32.6%的生产力增幅。”
Economists affiliated with the University of California, Berkeley (UCB) and the London School of Economics and Political Science (LSE) say that between November 2022 and December 2025, "AI increased the market's expected present value of software engineering productivity by the equivalent of a permanent 32.6 percent productivity increase."
亚历克斯·布卢门菲尔德（加州大学伯克利分校）、乔纳森·哈泽尔（伦敦政治经济学院）、陈廉（加州大学伯克利分校）和安德烈亚斯·沙布（加州大学伯克利分校）在国家经济研究局发表的一篇题为《人工智能的宏观经济效应：衡量软件工程渠道》的论文中描述了他们的研究结果。作者认为，自2022年11月ChatGPT问世以来，投资者已越来越多地将人工智能开发工具带来的预期收益计入公司估值中。
Alex Blumenfeld (UCB), Jonathon Hazell (LSE), Chen Lian (UCB), and Andreas Schaab (UCB) describe their findings in a National Bureau of Economics Research paper titled "The Macroeconomic Effect of AI: Sizing the Software Engineering Channel." The authors argue that investors have increasingly priced anticipated gains from AI development tools into company valuations since the introduction of ChatGPT in November 2022.
“我们通过实证研究来衡量，当人工智能股票指数上涨时，软件工程薪酬占比更高的公司是否会出现更大的股价涨幅，”加州大学伯克利分校金融学助理教授陈廉在给《The》的一封电子邮件中解释道。“然后，我们利用一个经济模型将这种关系转化为投资者预期的人工智能驱动的软件工程生产力收益。”
"We empirically measure whether firms with larger software engineering payroll shares experience larger stock-price increases when the AI stock index rises," explained Chen Lian, assistant professor of finance at UC Berkeley, in an email to The. "We then use an economic model to translate that relationship into the AI-driven software engineering productivity gains investors anticipate.
“对我们数据的初步观察表明，过去几年中，所覆盖公司的软件工程总就业人数有所增加。但我们的生产力估算完全不依赖于这一就业趋势。”
"A preliminary look at our data suggests that total software engineering employment among the firms covered has increased over the past few years.
研究人员并没有直接衡量开发人员的产出，而是研究了公司股票收益如何对人工智能相关新闻做出反应，以及这种反应是否会随着各公司软件工程薪酬占比的不同而变化。
But our productivity estimate does not depend on that employment trend at all."
“我们所说的‘人工智能相关新闻’，是指反映在股价中的新信息，”陈廉解释道。
Rather than measuring developers' output directly, the researchers examined how company stock returns respond to news about AI and whether that response varies with the proportion of each company's payroll devoted to software engineering.
如上所述，我们将实证测量与经济模型相结合，以推断人工智能如何改变了投资者对软件工程生产率的预期，以及由此隐含的国内生产总值（GDP）影响。连（Lian）承认，市场预期可能无法完全实现。“我们的估算捕捉了市场对当前和未来生产率提升的评估，而市场可能会过于乐观或悲观，”他表示。“其优势在于这是一种前瞻性指标，可实时获取，而此时人工智能的许多影响尚未显现。”
"By 'news about AI,' we mean new information reflected in stock prices," explained Lian. "As discussed above, we combine empirical measurements with an economic model to infer how AI has changed investors' expectations of software engineering productivity and the implied GDP impact." Lian acknowledges that market expectations may not fully materialize. "Our estimates capture the market’s assessment of current and future productivity gains, and markets can be overly optimistic or pessimistic," he said.
作者指出，市场隐含的32.6%的生产率提升，与其他研究人员报告的单项任务21%至56%的加速幅度在量级上相当。但他们同时指出，任务层面的提升可能会被限制生产率增长的瓶颈所抵消。在软件开发背景下，这可能表现为代码审查无法跟上激增的代码提交量。将估算的生产率提升纳入其经济模型，也产生了显著的隐含GDP效应。
"The advantage is a forward-looking measure, available in real time, when many of AI's effects have yet to play out." The market-implied productivity gain of 32.6 percent is comparable in magnitude to the 21-56 percent acceleration on individual tasks reported by other researchers, the authors say. They note however that task-level gains can be offset by bottlenecks that limit productivity gains. In the context of software development that might take the form of code reviews that can't keep pace with surging commit figures.
作者报告称：“从2022年11月到2025年12月的人工智能相关新闻，对应着现值GDP的增加，相当于永久性3.61%的水平提升。”至于在软件工程中观察到的生产率提升是否可推广到其他行业领域，连表示：“我们的方法可用于研究人工智能通过其他渠道产生的经济影响，我们计划在后续工作中对此进行探索。”®
Feeding the estimated productivity gain into their economic model also produces a sizeable implied effect on GDP. "News about AI from November 2022 to December 2025 corresponds to a present-value GDP increase equivalent to a permanent 3.61 percent level increase," the authors report. As to whether the productivity gains seen in software engineering are extensible to other industry sectors, Lian said: "Our methods can be used to study the economic impact of AI through other channels, which we plan to explore in follow-up work." ®