{"title":"人工智能与就业:拐点到来了吗?来自在线劳动力平台的证据","authors":"Dandan Qiao, Huaxia Rui, Qian Xiong","doi":"arxiv-2312.04180","DOIUrl":null,"url":null,"abstract":"Artificial intelligence (AI) refers to the ability of machines or software to\nmimic or even surpass human intelligence in a given cognitive task. While\nhumans learn by both induction and deduction, the success of current AI is\nrooted in induction, relying on its ability to detect statistical regularities\nin task input -- an ability learnt from a vast amount of training data using\nenormous computation resources. We examine the performance of such a\nstatistical AI in a human task through the lens of four factors, including task\nlearnability, statistical resource, computation resource, and learning\ntechniques, and then propose a three-phase visual framework to understand the\nevolving relation between AI and jobs. Based on this conceptual framework, we\ndevelop a simple economic model of competition to show the existence of an\ninflection point for each occupation. Before AI performance crosses the\ninflection point, human workers always benefit from an improvement in AI\nperformance, but after the inflection point, human workers become worse off\nwhenever such an improvement occurs. To offer empirical evidence, we first\nargue that AI performance has passed the inflection point for the occupation of\ntranslation but not for the occupation of web development. We then study how\nthe launch of ChatGPT, which led to significant improvement of AI performance\non many tasks, has affected workers in these two occupations on a large online\nlabor platform. Consistent with the inflection point conjecture, we find that\ntranslators are negatively affected by the shock both in terms of the number of\naccepted jobs and the earnings from those jobs, while web developers are\npositively affected by the very same shock. Given the potentially large\ndisruption of AI on employment, more studies on more occupations using data\nfrom different platforms are urgently needed.","PeriodicalId":501487,"journal":{"name":"arXiv - QuantFin - Economics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AI and Jobs: Has the Inflection Point Arrived? Evidence from an Online Labor Platform\",\"authors\":\"Dandan Qiao, Huaxia Rui, Qian Xiong\",\"doi\":\"arxiv-2312.04180\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Artificial intelligence (AI) refers to the ability of machines or software to\\nmimic or even surpass human intelligence in a given cognitive task. While\\nhumans learn by both induction and deduction, the success of current AI is\\nrooted in induction, relying on its ability to detect statistical regularities\\nin task input -- an ability learnt from a vast amount of training data using\\nenormous computation resources. We examine the performance of such a\\nstatistical AI in a human task through the lens of four factors, including task\\nlearnability, statistical resource, computation resource, and learning\\ntechniques, and then propose a three-phase visual framework to understand the\\nevolving relation between AI and jobs. Based on this conceptual framework, we\\ndevelop a simple economic model of competition to show the existence of an\\ninflection point for each occupation. Before AI performance crosses the\\ninflection point, human workers always benefit from an improvement in AI\\nperformance, but after the inflection point, human workers become worse off\\nwhenever such an improvement occurs. To offer empirical evidence, we first\\nargue that AI performance has passed the inflection point for the occupation of\\ntranslation but not for the occupation of web development. We then study how\\nthe launch of ChatGPT, which led to significant improvement of AI performance\\non many tasks, has affected workers in these two occupations on a large online\\nlabor platform. Consistent with the inflection point conjecture, we find that\\ntranslators are negatively affected by the shock both in terms of the number of\\naccepted jobs and the earnings from those jobs, while web developers are\\npositively affected by the very same shock. Given the potentially large\\ndisruption of AI on employment, more studies on more occupations using data\\nfrom different platforms are urgently needed.\",\"PeriodicalId\":501487,\"journal\":{\"name\":\"arXiv - QuantFin - Economics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuantFin - Economics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2312.04180\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2312.04180","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
AI and Jobs: Has the Inflection Point Arrived? Evidence from an Online Labor Platform
Artificial intelligence (AI) refers to the ability of machines or software to
mimic or even surpass human intelligence in a given cognitive task. While
humans learn by both induction and deduction, the success of current AI is
rooted in induction, relying on its ability to detect statistical regularities
in task input -- an ability learnt from a vast amount of training data using
enormous computation resources. We examine the performance of such a
statistical AI in a human task through the lens of four factors, including task
learnability, statistical resource, computation resource, and learning
techniques, and then propose a three-phase visual framework to understand the
evolving relation between AI and jobs. Based on this conceptual framework, we
develop a simple economic model of competition to show the existence of an
inflection point for each occupation. Before AI performance crosses the
inflection point, human workers always benefit from an improvement in AI
performance, but after the inflection point, human workers become worse off
whenever such an improvement occurs. To offer empirical evidence, we first
argue that AI performance has passed the inflection point for the occupation of
translation but not for the occupation of web development. We then study how
the launch of ChatGPT, which led to significant improvement of AI performance
on many tasks, has affected workers in these two occupations on a large online
labor platform. Consistent with the inflection point conjecture, we find that
translators are negatively affected by the shock both in terms of the number of
accepted jobs and the earnings from those jobs, while web developers are
positively affected by the very same shock. Given the potentially large
disruption of AI on employment, more studies on more occupations using data
from different platforms are urgently needed.