20260314|经济学人|外刊精读:市场总是难以给技术革命定价

双语正文

⭕️Markets always struggle to price technological revolutions

⭕️市场总是难以给技术革命定价

【1】Stockmarkets are, in a literal sense, fortune-tellers: their job is to foresee which businesses will make money in the future and which won’t. When things are not changing much, this is a matter of simple extrapolation. When change happens, it gets harder. This is obviously true in times of acute change, such as the fog of war currently enveloping the world. Yet it is also true of slower-moving but more profound disruption, like that being wrought by artificial intelligence.
从字面意义上讲，股市就是算命先生：它们的职责是预见哪些企业未来能盈利，哪些则不能。当环境变化不大时，这不过是简单的外推预测。而当变革发生时，难度就会陡增。在剧烈变革时期，比如当下笼罩世界的“战争迷雾”，这一点体现得尤为明显。但对于人工智能这类进展缓慢却影响更为深远的颠覆性变革，市场同样难以定价。

【2】Confusion over AI is everywhere. Goldman Sachs has created a share-price index of firms at most risk of disruption. Over the past year this has fallen by more than 20%. The bank’s mirror index of “long-term AI beneficiaries”, whose earnings stand to get the biggest boost from higher AI-fuelled productivity, is down by about 5%, even though many stockmarkets are near record highs. Often investors cannot even decide whether a firm is an AI winner or loser. From May 2024 to May 2025 the share price of Duolingo, a language-educator, doubled. Since then it has fallen by 80%. Not long ago Google was apparently toast because of AI. In the past year the share price of its parent company, Alphabet, has risen by 85%.
对人工智能的困惑无处不在。高盛集团编制了一个受颠覆性冲击风险最高企业的股价指数。过去一年，该指数跌幅超过20%。而该行对应的“长期人工智能受益者”指数——这类企业的盈利将因人工智能驱动的生产力提升而获得最大提振——尽管许多股市逼近历史高点，却仍下跌了约5%。投资者往往甚至无法判断一家企业是人工智能的赢家还是输家。2024年5月至2025年5月，语言学习平台多邻国的股价翻倍。但此后又暴跌80%。不久前，谷歌还因人工智能而看似前途尽毁。过去一年，其母公司字母表的股价却上涨了85%。

【3】Bond traders, for their part, think it is all much ado about nothing. In a world of higher AI-fuelled economic growth real interest rates should rise. But at 4.9%, yields on 30-year Treasury bonds are little different to where they were at the start of the year. When Isaiah Andrews and Maryam Farboodi of the Massachusetts Institute of Technology analysed bond-market moves around big AI model releases, they found that long-term yields fell.
债券交易员则认为这一切都是小题大做。在人工智能推动经济高速增长的世界里，实际利率本应上升。但30年期美国国债收益率为4.9%，与年初相比几乎没有变化。麻省理工学院的以赛亚·安德鲁斯和玛丽亚姆·法布迪分析了大型人工智能模型发布前后的债券市场走势，发现长期收益率有所下降。

【4】Depending on where you look, then, AI is both everything and nothing: an existential risk for firms and a rounding error for the economy. This exasperates market-watchers. It is also, when you look to history, par for the course. For if stockmarkets are bad at pricing conflict, they may be worse at pricing technological revolutions.
因此，从不同视角来看，人工智能既是“一切”也是“无关紧要”：对企业而言是生存威胁，对整体经济而言却只是微小误差。这让市场观察人士倍感沮丧。但从历史角度看，这实属常态。如果说股市不擅长为冲突定价，那它在为技术革命定价时可能表现得更糟。

【5】For every Blockbuster, which the stockmarket started marking down two years before the video-rental darling’s revenues peaked in 2004, there is a BlackBerry or a Kodak, where investors failed to detect trouble until the business was on its last legs. Like economists and recessions, markets often anticipate a technological disruption that never happens. When Thomas Edison’s electric-lighting revolution began in the 1870s, it was the ChatGPT of its day. Smart money of the era piled into the new technology, backed by John Pierpont Morgan among other financiers, and out of gas companies, until then the providers of most artificial illumination. But gas did not become irrelevant. Investors realised that electric light would remain dearer than gas for years. Even as electric light fell in price in the following decades, gas firms found larger markets to pursue. In London, the Gas Light and Coke Company noted that in 1892 only 2% of its customers had gas cookers. By 1911 more than two-thirds did.
就像百视达（Blockbuster）这家视频租赁巨头在2004年营收见顶前两年，股市就开始下调其股价；而黑莓（BlackBerry）或柯达（Kodak）则恰恰相反，投资者直到企业濒临绝境才察觉危机。和经济学家预测衰退一样，市场常常预判到一场永远不会发生的技术颠覆。19世纪70年代托马斯·爱迪生的电灯革命兴起时，它就如同当时的ChatGPT。彼时的精明资本在摩根大通等金融家的支持下，大举涌入这项新技术，同时撤出煤气公司——此前煤气公司是人工照明的主要供应商。但煤气并未被淘汰。投资者意识到，电灯在未来多年里仍会比煤气更昂贵。即便在随后几十年电灯价格持续下跌，煤气公司也找到了更广阔的市场。在伦敦，煤气灯与焦炭公司（Gas Light and Coke Company）记录显示，1892年仅有2%的客户使用煤气灶，到1911年这一比例已超过三分之二。

【6】To complement anecdote, The Economist examined American and European equities from 2005 to 2026 and found around 80 instances where an entire industry, from luxury goods to telecoms and media, entered a sectoral bear market, with share-price drops of at least 20 percentage points over three months relative to the broader index. (We excluded the energy industry, which rises and fall with the price of fossil fuels.) When this happens, we assume that the market worries that some structural change will hurt that industry. This could be a new technology or institutional arrangement (such as globalisation).
为了佐证这些案例，《经济学人》分析了2005年至2026年的欧美股市，发现约80个案例中，从奢侈品到电信、媒体的整个行业会进入板块熊市——股价在三个月内相对大盘指数至少下跌20个百分点。（我们排除了随化石燃料价格波动的能源行业。）当这种情况发生时，我们认为市场在担忧某些结构性变化会损害该行业，这可能是新技术或制度安排（如全球化）带来的冲击。

【7】Following such a sectoral bear market, the share price stays down half the time. In those cases, investors had correctly priced a long-term change in an industry’s circumstances. When competition from Chinese rivals permanently destroyed much of the European solar industry in the 2010s, investors priced this early. They also foresaw that telecoms firms would suffer as the internet took off .

在这类板块熊市之后，股价有一半概率会持续低迷。在这些案例中，投资者准确为行业长期环境变化定价。2010年代，中国竞争对手的竞争永久摧毁了欧洲大部分光伏产业，投资者提前对此做出了定价。他们也预见到互联网普及会让电信企业遭受冲击。

【8】In the other half of bear markets, the share price rises back above the overall market within a few years, suggesting that the early bets soured. Tobacco firms in America and Europe are a good example. Several times their share prices nosedived relative to the market, as investors worried about the effect of innovations in e-cigarettes and vaping. Time and again, tobacco stocks rose from the ashtray.

在另一半熊市案例中，股价会在几年内回升至大盘之上，说明早期的看空押注是错误的。欧美烟草公司就是典型例子。由于投资者担忧电子烟和蒸汽烟创新的冲击，它们的股价曾多次相对大盘暴跌。但烟草股总能一次次“死灰复燃”，从低谷中反弹。

【9】Our results suggest the stockmarket struggles to capture structural economic changes. This chimes with the work of Song Ma of Yale University. Even when companies’ technological base is becoming obsolete (measured by how cutting-edge their patents are), analysts tend to overestimate future profitability, Mr Ma finds. This props up the share prices of obsolete firms.
我们的研究结果表明，股市难以捕捉结构性经济变化。这与耶鲁大学宋马的研究结论不谋而合。他发现，即便企业的技术基础正在过时（以专利的前沿程度衡量），分析师也往往会高估其未来盈利能力，这支撑了落后企业的股价。

【10】It would not be a surprise if today’s investors, following Mr Ma’s results, were overestimating the AI threat to some firms but underestimating the danger to others. There is, after all, even more uncertainty about the AI transition than there was about previous technological shifts. Two reasons stand out. The first concerns the technology itself. AI capabilities have improved rapidly in certain domains, notably coding. But progress is uneven across tasks. Performance on open-ended writing and idea generation is not noticeably better than it was a few months ago.

如果遵循宋马的研究结论，如今的投资者很可能高估了人工智能对部分企业的威胁，却低估了对另一些企业的风险。毕竟，人工智能转型的不确定性比以往任何技术变革都要大。主要有两个原因：首先是技术本身。人工智能在某些领域（尤其是编程）的能力提升迅速，但在不同任务上进展不均。开放式写作和创意生成的表现，相比几个月前并无明显改善。

【11】The second source of uncertainty concerns the economics of a superintelligent AI. No one knows to whom the profits of such “artificial general intelligence” would accrue. If AI reduces barriers to entry, companies’ profit margins may decline. Leading AI labs report rapid revenue growth but also enormous costs of computing power. Lots of academic research suggests that new technologies cause market bubbles as investors get excited about the future. But some, such as by Jeremy Greenwood of the University of Pennsylvania and Boyan Jovanovic of New York University, suggests that the stockmarket can actually fall because investors expect new, as yet unlisted, firms to gobble up the profits. That is certainly what many backers of OpenAI and Anthropic, two warring AI labs, are hoping.
第二个不确定性来源是超级人工智能的经济学问题。没人知道这类“通用人工智能”的利润最终会流向谁。如果人工智能降低了行业准入门槛，企业利润率可能会下降。头部人工智能实验室虽报告营收快速增长，但也面临着极高的算力成本。大量学术研究表明，新技术会因投资者对未来的乐观预期催生市场泡沫。但宾夕法尼亚大学的杰里米·格林伍德和纽约大学的博扬·约万诺维奇等人的研究指出，股市反而可能下跌——因为投资者预期尚未上市的新企业会攫取大部分利润。这正是OpenAI和Anthropic这两家竞争激烈的人工智能实验室的众多支持者所期望的。

【12】In a world where fundamental views of AI switch quickly, today’s losers could end up as tomorrow’s winners. Much will depend on how well firms deploy AI to improve their offering to clients. Innovating your way out of supposed technological threats is a common theme in business history. Western Union, the leading telegraphy firm of its day, foolishly snubbed Alexander Graham Bell’s offer to sell it the patent for the telephone. But as phone networks grew, Western Union carved out a niche in money transfers which faced no immediate technological competition. American Express, now synonymous with credit cards, started out as a freight-forwarder. Samsung, a global technology giant, sold dried fish. Some of the software businesses being hammered today may likewise reinvent themselves.
在对人工智能的核心认知快速切换的世界里，今天的输家可能成为明天的赢家。这很大程度上取决于企业能否很好地运用人工智能来优化客户服务。通过创新摆脱所谓技术威胁，是商业史上的常见主题。当年领先的电报公司西联汇款，曾愚蠢地拒绝了亚历山大·格雷厄姆·贝尔出售电话专利的提议。但随着电话网络普及，西联汇款在即时转账领域开辟了一片不受技术冲击的细分市场。如今以信用卡闻名的美国运通，最初是货运代理公司；全球科技巨头三星，早年还卖过鱼干。如今正遭受重创的部分软件企业，或许也能像它们一样完成自我革新。

【13】Fans of efficient markets may be maddened by this inability to peer accurately into the future. But markets reflect only the collective wisdom of today’s investors. For as long as conversations between two Silicon Valley technologists produce three answers about AI’s impact on the world, no one will be the wiser.

有效市场理论的支持者可能会对这种无法准确预判未来的现象感到恼火。但市场只反映了当下投资者的集体智慧。只要两位硅谷技术专家谈论人工智能对世界的影响时，都能得出三种不同结论，就没人能真正看透未来。

生词短语

1. technomyopia /ˌteknəʊˈmaɪəpiə/ n. 技术短视

2. price /praɪs/ v. 给……定价

3. technological /ˌteknəˈlɒdʒɪkl/ adj. 技术的

4. revolution /ˌrevəˈluːʃn/ n. 革命

5. literal /ˈlɪtərəl/ adj. 字面的

6. extrapolation /ɪkˌstræpəˈleɪʃn/ n. 外推法；推断

7. acute /əˈkjuːt/ adj. 剧烈的；尖锐的

8. disruption /dɪsˈrʌpʃn/ n. 颠覆性变革

9. beneficiary /ˌbenɪˈfɪʃəri/ n. 受益者

10. productivity /ˌprɒdʌkˈtɪvəti/ n. 生产力

11. yield /jiːld/ n. 收益率 v. 产出

12. existential /ˌeɡzɪˈstenʃl/ adj. 存在的；生存的

13. exasperate /ɪɡˈzæspəreɪt/ v. 使恼怒；使沮丧

14. peak /piːk/ v. 达到峰值 n. 顶点

15. anticipate /ænˈtɪsɪpeɪt/ v. 预期；预判

16. financier /faɪˈnænsɪə/ n. 金融家

17. illumination /ɪˌluːmɪˈneɪʃn/ n. 照明

18. irrelevant /ɪˈreləvənt/ adj. 无关紧要的

19. complement /ˈkɒmplɪment/ v. 补充 /ˈkɒmplɪmənt/ n. 补充物

20. equity /ˈekwəti/ n. (pl. equities) 股票；普通股

21. sectoral /ˈsektərəl/ adj. 行业的；部门的

22. structural /ˈstrʌktʃərəl/ adj. 结构的

23. institutional /ˌɪnstɪˈtjuːʃənl/ adj. 制度的；机构的

24. permanently /ˈpɜːmənəntli/ adv. 永久地

25. nosedive /ˈnəʊzdaɪv/ v. 暴跌；急降

26. obsolete /ˈɒbsəliːt/ adj. 过时的；废弃的

27. cutting-edge /ˌkʌtɪŋ ˈedʒ/ adj. 前沿的；尖端的

28. patent /ˈpeɪtnt/ n. 专利

29. overestimate /ˌəʊvərˈestɪmeɪt/ v. 高估

30. profitability /ˌprɒfɪtəˈbɪləti/ n. 盈利能力

31. underestimate /ˌʌndərˈestɪmeɪt/ v. 低估

32. transition /trænˈzɪʃn/ n. 转型；过渡

33. uneven /ʌnˈiːvn/ adj. 不均衡的

34. superintelligent /ˌsuːpərɪnˈtelɪdʒənt/ adj. 超级智能的

35. accrue /əˈkruː/ v. 积累；归属

36. margin /ˈmɑːdʒɪn/ n. 利润率；边缘

37. bubble /ˈbʌbl/ n. 泡沫

38. synonymous /sɪˈnɒnɪməs/ adj. 同义的

39. reinvent /ˌriːɪnˈvent/ v. 重塑；革新

40. collective /kəˈlektɪv/ adj. 集体的

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