We study how various types of machines, namely, information and communication technologies, software, and especially industrial robots, affect the demand for workers of different education, age, and gender. We do so by exploiting differences in the composition of workers across countries, industries and time. Our dataset comprises 10 high-income countries and 30 industries, which span roughly their entire economies, with annual observations over the period 1982–2005. The results suggest that software and robots reduced the demand for low and medium-skill workers, the young, and women — especially in manufacturing industries; but raised the demand for high-skill workers, older workers and men —especially in service industries. These findings are consistent with the hypothesis that automation technologies, contrary to other types of capital, replace humans performing routine tasks. We also find evidence for some types of workers, especially women, having shifted away from such tasks.

中文翻译：

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谁怕机器？

我们研究了各种类型的机器（即信息和通信技术，软件，尤其是工业机器人）如何影响对不同教育程度，年龄和性别的工人的需求。我们通过利用国家，行业和时间之间的工人组成差异来做到这一点。我们的数据集包括10个高收入国家和30个行业，大致涵盖了整个经济体，并在1982年至2005年期间进行了年度观测。结果表明，软件和机器人减少了对中低技能工人，年轻人和妇女的需求，特别是在制造业中；但是增加了对高技能工人，老年工人和男性的需求，尤其是在服务行业。这些发现与以下假设相符：自动化技术与其他类型的资本相反，代替执行常规任务的人员。我们还发现某些类型的工人，特别是女性，已经从此类工作转移了的证据。