{"title":"Maine’s Workforce Challenges in an Age of Artificial Intelligence","authors":"J. McDonnell","doi":"10.53558/reua8661","DOIUrl":null,"url":null,"abstract":"Artificial intelligence will improve productivity, expand the economy, and significantly alter many jobs. To accommodate these changes, Maine will have to upgrade workforce skills in a rapidly changing economy. This article recommends policy proposals in response to the rise of artificial intelligence, including (1) training programs for current and displaced workers; (2) revamped postsecondary education programs to provide a wider group of students with the skills necessary in a postindustrial society; and (3) a much closer relationship between government, employers, and educational institutions to develop the future workforce for Maine. The paper also looks at the deliberations about workforce development in the early twentieth century as the United States transitioned from a largely agricultural economy to an industrial one for insights from the past in arriving at educational programs suitable for a postindustrial society. I her inaugural address, Governor Janet Mills pledged to develop a first-class workforce in Maine to address the frustration of employers who cannot find workers and the dissatisfaction of workers stuck in dead-end jobs without the skills for advancement. The governor recognized the complexity of this challenge by noting that technological innovation will radically alter the way Maine people live, learn, and work, which is why she announced the formation of an Office of Innovation and the Future (Mills 2019). Over the next decade, the acceleration of the adoption of automation, including artificial intelligence and robotics, will likely exacerbate the mismatch the governor identified between workers and employers. While new technologies will increase productivity and economic growth, they will inevitably result in many jobs requiring new skills and some workers requiring new occupations. This article explores the policy implications for Maine’s workforce from the rise of artificial intelligence and discusses (1) effective transition programs that train employed and displaced workers in new job skills; (2) postsecondary education programs that provide a wider group of students with skills necessary to work productively in a postindustrial society; and (3) a much closer relationship between government, employers, and educational institutions to develop Maine’ future workforce. The article also examines the deliberations over workforce development in the early twentieth century when US society transitioned from a largely agricultural economy to an industrial one, as a way to highlight what we can learn from that experience as we transition to a postindustrial society. THE SHIFTING NATURE OF WORK T globalization, digitization, and automation of the US economy has increased productivity, held down inflation, opened up new markets, created moreefficient supply chains, expanded the economy, and given consumers quality products at lower cost. But these advantages came at the expense of thousands of American jobs, particularly good manufacturing jobs. In the 1980s, manufacturing represented Maine’s largest employment sector, but the number of manufacturing jobs in Maine has been cut in half since that time (Maine DOL 2013). Over the last half century, the United States has shifted from an industrial manufacturing economy to a skilled service economy with an emphasis on finance, education, health care, and information technology. These service fields require higher skills than the jobs in the old industrial economy. Now, two out of three jobs require training beyond high school, often a twoor four-year degree (Carnevale 2016). Most of the job losses from trade took place in the first decade of this century; more-recent losses are coming from automation. Much of the political rhetoric during the 2016 presidential campaign focused on trade and immigration as the culprits upending industries and jobs. But job losses from trade have been eclipsed by the far MAINE’S WORKFORCE CHALLENGES MAINE POLICY REVIEW • Vol. 28, No. 1 • 2019 12 greater job losses from automation and artificial intelligence—impersonal forces that are harder to scapegoat, negotiate with, or turn back. A McKinsey study found that 45 percent of work activities could be automated with current technologies (Chui, Manyiku, and Mirenadi 2015). Increasingly, many routine jobs are becoming casualties of automation: robots have replaced factory workers, ATMs have eliminated bank tellers, and kiosks and scanners have jettisoned clerks. In the future, high-skilled jobs will no longer be immune to automation as computer algorithms augment or even replace some professionals in law, medicine, and finance. Ironically, today’s workforce shortages may well accelerate the adoption of automation. Automation drives down labor costs and has been adopted in factories not only in high-cost regions like the United States, but also in lower-cost regions like China and Mexico, ensuring that the combination of automation and low-cost labor will make those regions competitive with any region with high labor costs. In many areas of the economy, employees of the future will be those who manage automated technology. Artificial intelligence has the power to change the nature of work for many people, but the pace of adoption and the extent of the disruption are still the subject of debate. A rapid adoption of autonomous self-driving vehicles, for instance, could dramatically displace millions of workers, but a more gradual and partial adoption, especially in a growing economy, will have far less impact on drivers. The Case for Significant Disruption As an extreme case, the historian Yuval Noah Harari offers a dystopian vision that imagines artificial intelligence doing to workers what the automobile did to the horse and buggy. In his analogy, many of today’s workers will likely be the horse that lost its job and never found another useful function in a motorized economy (Harari 2016). Harari reasons that the power of artificial intelligence is unlike past work-saving innovations that took over manual tasks and pushed human work up the conceptual ladder. Harari makes the case that innovations from artificial intelligence are radically different from past innovations. He argues that since humans can perform only manual and conceptual tasks, there is nowhere for us to go when artificial intelligence outperforms humans on both manual and conceptual tasks. The algorithms in artificial intelligence already dominate the stock market, social media, and search engines. Their capacity to take into account millions of variables when making split-second decisions will likely extend to the rest of the economy. Harari sees the possibility of artificial intelligence eventually taking over the work of millions of people, creating what he calls a “useless” class. What will societies such as Bangladesh do when we can produce products cheaper through automation than they can produce with their low-cost labor? People in Silicon Valley are already envisioning the need for basic universal income because many people will be unable to find employment in an economy dominated by artificial intelligence. Harari makes clear that he is not making a prediction or setting a timetable, rather he is dramatizing the power of artificial intelligence. The Case for More-Moderate Disruption More-moderate positions on the impact of artificial intelligence also predict dramatic change although without massive displacement of workers. A report by McKinsey Global Institute forecasts that 60 percent of current occupations could automate at least 30 percent of their work and as much as 33 percent of work activities could be displaced by 2030 (Manyika et al. 2017). The report predicts that up to 14 percent of workers will have to transition to new occupations. The timetable for these disruptions, however, will depend on the pace of adoption and whether multiple sectors in the economy adopt the technology simultaneously. But even with the adoption of artificial intelligence, the report paints a possible positive scenario of jobs growth if economies expand, incomes rise, use of health care increases with an aging society, and other economic stimuli (such as spending on infrastructure, energy, and climate change mitigation) take place. In contrast with Harari’s position, the argument for more-moderate disruption adopts the traditional view that while innovation disrupts the economy as some jobs and industries become obsolete, new technology ushers in new opportunities and jobs. Both cases, however, share the view that technology will disrupt the economy and that employers, employees, governments, and educational institutions will have to respond to the change. The McKinsey Global Institute projects continuing decline in jobs associated with physical and manual skills and basic cognitive functions and a shift toward higher cognitive and technological skills, as well as MAINE’S WORKFORCE CHALLENGES MAINE POLICY REVIEW • Vol. 28, No. 1 • 2019 13 increased importance in social and emotional intelligence (Manyika et al. 2017). Artificial intelligence will increase the importance of entrepreneurship and problem solving in technologically rich environments (Bughin et al. 2018). The Brookings report on Automation and Artificial Intelligence forecasts 25 percent of US employment will face high exposure to automation over the next few decades and more than 70 percent of current tasks at risk of substitution. Another 36 percent of the workforce will experience moderate exposure, which means that more than six out of ten jobs will see some—or even all—tasks associated with that job taken over by automation. The lowest-skilled workers will be most vulnerable, but they will not be the only ones affected. New technologies will create an urgent need for educational programs that continually upgrade workers skills, or we risk having large portions of the population ill equipped for the work of the future (Muro, Maxim, and Whito","PeriodicalId":34576,"journal":{"name":"Maine Policy Review","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Maine Policy Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.53558/reua8661","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Artificial intelligence will improve productivity, expand the economy, and significantly alter many jobs. To accommodate these changes, Maine will have to upgrade workforce skills in a rapidly changing economy. This article recommends policy proposals in response to the rise of artificial intelligence, including (1) training programs for current and displaced workers; (2) revamped postsecondary education programs to provide a wider group of students with the skills necessary in a postindustrial society; and (3) a much closer relationship between government, employers, and educational institutions to develop the future workforce for Maine. The paper also looks at the deliberations about workforce development in the early twentieth century as the United States transitioned from a largely agricultural economy to an industrial one for insights from the past in arriving at educational programs suitable for a postindustrial society. I her inaugural address, Governor Janet Mills pledged to develop a first-class workforce in Maine to address the frustration of employers who cannot find workers and the dissatisfaction of workers stuck in dead-end jobs without the skills for advancement. The governor recognized the complexity of this challenge by noting that technological innovation will radically alter the way Maine people live, learn, and work, which is why she announced the formation of an Office of Innovation and the Future (Mills 2019). Over the next decade, the acceleration of the adoption of automation, including artificial intelligence and robotics, will likely exacerbate the mismatch the governor identified between workers and employers. While new technologies will increase productivity and economic growth, they will inevitably result in many jobs requiring new skills and some workers requiring new occupations. This article explores the policy implications for Maine’s workforce from the rise of artificial intelligence and discusses (1) effective transition programs that train employed and displaced workers in new job skills; (2) postsecondary education programs that provide a wider group of students with skills necessary to work productively in a postindustrial society; and (3) a much closer relationship between government, employers, and educational institutions to develop Maine’ future workforce. The article also examines the deliberations over workforce development in the early twentieth century when US society transitioned from a largely agricultural economy to an industrial one, as a way to highlight what we can learn from that experience as we transition to a postindustrial society. THE SHIFTING NATURE OF WORK T globalization, digitization, and automation of the US economy has increased productivity, held down inflation, opened up new markets, created moreefficient supply chains, expanded the economy, and given consumers quality products at lower cost. But these advantages came at the expense of thousands of American jobs, particularly good manufacturing jobs. In the 1980s, manufacturing represented Maine’s largest employment sector, but the number of manufacturing jobs in Maine has been cut in half since that time (Maine DOL 2013). Over the last half century, the United States has shifted from an industrial manufacturing economy to a skilled service economy with an emphasis on finance, education, health care, and information technology. These service fields require higher skills than the jobs in the old industrial economy. Now, two out of three jobs require training beyond high school, often a twoor four-year degree (Carnevale 2016). Most of the job losses from trade took place in the first decade of this century; more-recent losses are coming from automation. Much of the political rhetoric during the 2016 presidential campaign focused on trade and immigration as the culprits upending industries and jobs. But job losses from trade have been eclipsed by the far MAINE’S WORKFORCE CHALLENGES MAINE POLICY REVIEW • Vol. 28, No. 1 • 2019 12 greater job losses from automation and artificial intelligence—impersonal forces that are harder to scapegoat, negotiate with, or turn back. A McKinsey study found that 45 percent of work activities could be automated with current technologies (Chui, Manyiku, and Mirenadi 2015). Increasingly, many routine jobs are becoming casualties of automation: robots have replaced factory workers, ATMs have eliminated bank tellers, and kiosks and scanners have jettisoned clerks. In the future, high-skilled jobs will no longer be immune to automation as computer algorithms augment or even replace some professionals in law, medicine, and finance. Ironically, today’s workforce shortages may well accelerate the adoption of automation. Automation drives down labor costs and has been adopted in factories not only in high-cost regions like the United States, but also in lower-cost regions like China and Mexico, ensuring that the combination of automation and low-cost labor will make those regions competitive with any region with high labor costs. In many areas of the economy, employees of the future will be those who manage automated technology. Artificial intelligence has the power to change the nature of work for many people, but the pace of adoption and the extent of the disruption are still the subject of debate. A rapid adoption of autonomous self-driving vehicles, for instance, could dramatically displace millions of workers, but a more gradual and partial adoption, especially in a growing economy, will have far less impact on drivers. The Case for Significant Disruption As an extreme case, the historian Yuval Noah Harari offers a dystopian vision that imagines artificial intelligence doing to workers what the automobile did to the horse and buggy. In his analogy, many of today’s workers will likely be the horse that lost its job and never found another useful function in a motorized economy (Harari 2016). Harari reasons that the power of artificial intelligence is unlike past work-saving innovations that took over manual tasks and pushed human work up the conceptual ladder. Harari makes the case that innovations from artificial intelligence are radically different from past innovations. He argues that since humans can perform only manual and conceptual tasks, there is nowhere for us to go when artificial intelligence outperforms humans on both manual and conceptual tasks. The algorithms in artificial intelligence already dominate the stock market, social media, and search engines. Their capacity to take into account millions of variables when making split-second decisions will likely extend to the rest of the economy. Harari sees the possibility of artificial intelligence eventually taking over the work of millions of people, creating what he calls a “useless” class. What will societies such as Bangladesh do when we can produce products cheaper through automation than they can produce with their low-cost labor? People in Silicon Valley are already envisioning the need for basic universal income because many people will be unable to find employment in an economy dominated by artificial intelligence. Harari makes clear that he is not making a prediction or setting a timetable, rather he is dramatizing the power of artificial intelligence. The Case for More-Moderate Disruption More-moderate positions on the impact of artificial intelligence also predict dramatic change although without massive displacement of workers. A report by McKinsey Global Institute forecasts that 60 percent of current occupations could automate at least 30 percent of their work and as much as 33 percent of work activities could be displaced by 2030 (Manyika et al. 2017). The report predicts that up to 14 percent of workers will have to transition to new occupations. The timetable for these disruptions, however, will depend on the pace of adoption and whether multiple sectors in the economy adopt the technology simultaneously. But even with the adoption of artificial intelligence, the report paints a possible positive scenario of jobs growth if economies expand, incomes rise, use of health care increases with an aging society, and other economic stimuli (such as spending on infrastructure, energy, and climate change mitigation) take place. In contrast with Harari’s position, the argument for more-moderate disruption adopts the traditional view that while innovation disrupts the economy as some jobs and industries become obsolete, new technology ushers in new opportunities and jobs. Both cases, however, share the view that technology will disrupt the economy and that employers, employees, governments, and educational institutions will have to respond to the change. The McKinsey Global Institute projects continuing decline in jobs associated with physical and manual skills and basic cognitive functions and a shift toward higher cognitive and technological skills, as well as MAINE’S WORKFORCE CHALLENGES MAINE POLICY REVIEW • Vol. 28, No. 1 • 2019 13 increased importance in social and emotional intelligence (Manyika et al. 2017). Artificial intelligence will increase the importance of entrepreneurship and problem solving in technologically rich environments (Bughin et al. 2018). The Brookings report on Automation and Artificial Intelligence forecasts 25 percent of US employment will face high exposure to automation over the next few decades and more than 70 percent of current tasks at risk of substitution. Another 36 percent of the workforce will experience moderate exposure, which means that more than six out of ten jobs will see some—or even all—tasks associated with that job taken over by automation. The lowest-skilled workers will be most vulnerable, but they will not be the only ones affected. New technologies will create an urgent need for educational programs that continually upgrade workers skills, or we risk having large portions of the population ill equipped for the work of the future (Muro, Maxim, and Whito
人工智能将提高生产力,扩大经济,并显著改变许多工作岗位。为了适应这些变化,缅因州将不得不在快速变化的经济中提升劳动力技能。本文提出了应对人工智能兴起的政策建议,包括:(1)现有和失业工人的培训计划;(2)改进高等教育课程,为更广泛的学生群体提供后工业社会所需的技能;(3)政府、雇主和教育机构之间建立更紧密的关系,为缅因州培养未来的劳动力。本文还考察了20世纪初美国从农业经济向工业经济过渡时对劳动力发展的思考,以期从过去获得适合后工业社会的教育计划的见解。在她的就职演说中,州长珍妮特·米尔斯承诺要在缅因州发展一流的劳动力队伍,以解决雇主找不到工人的沮丧情绪,以及那些被困在没有晋升技能的没有出路的工作中的工人的不满情绪。州长认识到这一挑战的复杂性,她指出,技术创新将从根本上改变缅因州人的生活、学习和工作方式,这就是为什么她宣布成立创新与未来办公室(Mills 2019)。在接下来的十年里,包括人工智能和机器人在内的自动化的加速采用,可能会加剧州长所指出的工人和雇主之间的不匹配。虽然新技术将提高生产力和经济增长,但它们将不可避免地导致许多工作需要新技能,一些工人需要新的职业。本文探讨了人工智能的兴起对缅因州劳动力的政策影响,并讨论了:(1)有效的过渡计划,培训在职和失业工人的新工作技能;(2)为更广泛的学生群体提供在后工业社会中有效工作所需技能的高等教育项目;(3)政府、雇主和教育机构之间建立更密切的关系,以培养缅因州未来的劳动力。本文还考察了20世纪初美国社会从农业经济向工业经济过渡时对劳动力发展的思考,以强调我们在向后工业社会过渡的过程中可以从这一经验中学到什么。美国经济的全球化、数字化和自动化提高了生产率,抑制了通货膨胀,开辟了新市场,创造了更高效的供应链,扩大了经济,并以更低的成本为消费者提供了高质量的产品。但这些优势是以牺牲美国成千上万的工作岗位为代价的,尤其是制造业的好工作岗位。在20世纪80年代,制造业是缅因州最大的就业部门,但从那时起,缅因州的制造业工作岗位减少了一半(缅因州劳工部2013)。在过去的半个世纪里,美国已经从一个工业制造业经济转变为一个以金融、教育、医疗保健和信息技术为重点的技术服务业经济。这些服务领域比旧工业经济中的工作需要更高的技能。现在,三分之二的工作需要高中以上的培训,通常是两年制或四年制学位(Carnevale 2016)。贸易造成的大部分失业发生在本世纪头十年;最近的损失来自自动化。2016年总统竞选期间的许多政治言论都集中在贸易和移民问题上,称其是颠覆行业和就业的罪魁祸首。但贸易造成的就业损失被远远超过了缅因州的劳动力挑战缅因州政策评论·第28卷,第1期·2019年自动化和人工智能造成的更多就业损失-这些非个人力量更难成为替罪羊,谈判或扭转。麦肯锡的一项研究发现,45%的工作活动可以通过现有技术实现自动化(Chui, Manyiku, and Mirenadi 2015)。越来越多的常规工作正成为自动化的牺牲品:机器人取代了工厂工人,自动柜员机淘汰了银行柜员,售货亭和扫描仪淘汰了职员。在未来,随着计算机算法增强甚至取代法律、医学和金融领域的一些专业人士,高技能工作将不再幸免于自动化。具有讽刺意味的是,今天的劳动力短缺很可能加速自动化的采用。 自动化降低了劳动力成本,不仅在美国这样的高成本地区,而且在中国和墨西哥这样的低成本地区,工厂都采用了自动化,确保了自动化和低成本劳动力的结合,将使这些地区与任何高劳动力成本地区相比都具有竞争力。在经济的许多领域,未来的雇员将是那些管理自动化技术的人。人工智能有能力改变许多人的工作性质,但采用的速度和破坏的程度仍然是争论的主题。例如,自动驾驶汽车的迅速普及可能会大大取代数百万工人,但更渐进和部分的普及,尤其是在一个不断增长的经济体中,对司机的影响要小得多。作为一个极端的例子,历史学家尤瓦尔·诺亚·哈拉里(Yuval Noah Harari)提出了一个反乌托邦的愿景,想象人工智能对工人的影响,就像汽车对马和马车的影响一样。在他的类比中,今天的许多工人可能会成为失去工作的马,在机动化经济中再也找不到其他有用的功能(Harari 2016)。赫拉利的理由是,人工智能的力量不同于过去节省工作的创新,后者取代了手工任务,将人类工作推向了概念阶梯。赫拉利认为,人工智能带来的创新与过去的创新截然不同。他认为,由于人类只能执行手动和概念性任务,当人工智能在手动和概念性任务上都超过人类时,我们将无处可去。人工智能中的算法已经主导了股票市场、社交媒体和搜索引擎。他们在做出瞬间决定时考虑数以百万计变量的能力,可能会扩展到经济的其他领域。赫拉利认为,人工智能最终有可能接管数百万人的工作,创造出他所谓的“无用”阶层。当我们通过自动化生产的产品比他们用低成本劳动力生产的产品更便宜时,像孟加拉国这样的社会会怎么做?硅谷的人已经在设想基本全民收入的必要性,因为在一个由人工智能主导的经济中,许多人将无法找到工作。赫拉利明确表示,他不是在做预测或设定时间表,而是在戏剧性地展示人工智能的力量。关于人工智能影响的更温和的观点也预测了巨大的变化,尽管没有大规模的工人被取代。麦肯锡全球研究所(McKinsey Global Institute)的一份报告预测,到2030年,60%的当前职业至少有30%的工作可能被自动化取代,多达33%的工作活动可能被取代(Manyika et al. 2017)。该报告预测,高达14%的工人将不得不过渡到新的职业。然而,这些中断的时间表将取决于采用的速度以及经济中的多个部门是否同时采用该技术。但即使采用了人工智能,该报告也描绘了一种可能的积极情景,即如果经济扩张、收入增加、医疗保健的使用随着老龄化社会的增加而增加,以及其他经济刺激措施(如基础设施、能源和减缓气候变化的支出)到位,就业机会可能会增长。与赫拉利的观点相反,支持更适度颠覆的观点采用了传统观点,即虽然创新会破坏经济,导致一些工作和行业过时,但新技术带来了新的机会和就业机会。然而,这两种情况都认为,技术将扰乱经济,雇主、雇员、政府和教育机构将不得不对这种变化做出反应。麦肯锡全球研究所预测,与体力和体力技能以及基本认知功能相关的工作岗位将继续下降,并向更高的认知和技术技能转变,以及缅因州的劳动力挑战缅因州政策评论•第28卷,第1期•2019。13 .社交和情商的重要性增加(Manyika et al. 2017)。人工智能将在技术丰富的环境中增加创业和解决问题的重要性(Bughin et al. 2018)。布鲁金斯学会关于自动化和人工智能的报告预测,在未来几十年里,美国25%的就业岗位将面临自动化的高度影响,超过70%的当前工作将面临被替代的风险。另外36%的劳动力将经历适度的暴露,这意味着超过六成的工作岗位将看到与该工作相关的部分甚至全部任务被自动化取代。 技能最低的工人将是最脆弱的,但他们不会是唯一受到影响的人。新技术将迫切需要不断提高工人技能的教育项目,否则我们将面临很大一部分人口无法胜任未来工作的风险(穆罗、马克西姆和惠托)