美国领先企业联合成立了一个联盟，应对人工智能对技术岗位劳动力的影响由思科（Cisco）牵头，埃森哲（Accenture）、谷歌（Google）、国际商业机器公司（IBM）和微软（Microsoft）等主要行业参与者参与的人工智能 ICT 劳动力联盟（AI-Enabled ICT Workforce Consortium）AI-Enabled Information and Communication Technology (ICT) Workforce Consortium 旨在评估和减轻人工智能对技术工作的影响。该联盟旨在确定受人工智能进步影响的岗位所需的关键技能，为再培训和提高技能提供途径。该倡议借鉴了私营部门、顾问和政府的合作见解，为人工智能环境下的劳动力做好准备，强调了全球合作促进包容性技术未来的必要性。
人工智能 ICT 劳动力联盟致力于提供实际可行的洞见，发掘重新培训和提升技能的新机遇
思科牵头成立的AI赋能信息通信技术（ICT）工作力联盟，包括埃森哲、Eightfold、谷歌、IBM、Indeed、英特尔、微软和SAP等行业领导者的加入。该联盟将评估人工智能对科技岗位的影响，并为最可能受到AI影响的职业确定技能发展途径。 联盟的成立得到了美国-欧盟贸易与技术委员会人才成长工作组的推动，思科主席兼CEO Chuck Robbins在该工作组的参与，以及美国商务部的建议，起到了催化剂的作用。 顾问团包括美国劳工联盟-产业组织联合会、CHAIN5、美国通信工人联合会、DIGITALEUROPE、欧洲职业培训协会、可汗学院和SMEUnited等。
比利时鲁汶，2024年4月4日-- 思科（纳斯达克代码：CSCO）和另外八家行业领先公司包括埃森哲、Eightfold、谷歌、IBM、Indeed、英特尔、微软和SAP，以及六位顾问今天宣布，成立了致力于提升和重新培训最可能受到AI影响岗位的AI赋能ICT工作力联盟。该联盟受到美国-欧盟贸易与技术委员会人才成长工作组的启发，旨在探究AI对ICT岗位的影响，帮助工作者发现并参与相关培训计划，同时连接企业和具备相应技能、准备就绪的工作者。
作为私营部门的合作平台，联盟正评估AI如何改变工作岗位及所需技能，让工作者取得成功。首阶段工作成果将总结为一份提供给企业领导者和工作者实际建议的报告。未来几个月将公布更多详情。研究结果旨在为那些寻求为员工重新培训和提升技能的雇主提供实用的洞见和建议。
联盟成员涵盖了在AI前沿创新的企业，他们深知AI对劳动力市场的当前和未来影响。各成员企业已分别记录了AI带来的机遇与挑战。通过合作，这些组织能够汇聚见解，推荐行动计划，并在其广泛的影响领域内实施这些发现。
“人工智能正加速全球劳动力市场的变革，为私营部门提供了一个强大机会，帮助工作者重新培训和提升技能，以迎接未来，”思科执行副总裁兼首席人事、政策与目标官Francine Katsoudas表示。“我们新成立的AI赋能工作力联盟的任务是向组织提供关于AI对劳动力影响的知识，并装备工作者以相关技能。我们期待吸引更多利益相关方——包括政府、非政府组织和学术界——一同迈出确保AI革命惠及每个人的重要一步。”
联盟的工作受到了美国-欧盟贸易与技术委员会人才成长工作组的启发，思科主席兼CEO Chuck Robbins领导其技能培训工作流程的指导，以及美国商务部的建议。美国总统拜登、欧盟委员会主席冯德莱恩和欧洲理事会主席米歇尔于2021年6月成立了TTC，目的是通过合作和民主方法在贸易、技术和安全领域推进美国和欧盟的竞争力和繁荣。
“在美国商务部，我们致力于推动先进技术的发展，并深化与全球伙伴和盟友之间的贸易与投资关系。这项工作正帮助我们建立一个强大且具竞争力的经济体，由能够获得高质量、高薪、可维持家庭生活的未来工作的才华横溢的劳动力所推动。我们明白，经济安全与国家安全紧密相连。这就是我为何感到自豪地看到人才成长工作组的努力以及AI赋能ICT工作力联盟的成立，”美国商务部长Gina Raimondo表示。“我感激联盟成员加入这一努力，共同面对AI快速发展所带来的新型劳动力需求。这项工作将为这些工作的具体技能需求提供前所未有的见解。我希望这个联盟仅是一个开始，并且私营部门将其视为一个行动呼吁，确保我们的劳动力能够享受到AI带来的好处。”
AI赋能ICT工作力联盟的工作解决了对具备AI各方面技能训练的熟练劳动力的紧迫需求。联盟将利用其成员和顾问的力量，推荐和扩大包容性的重新培训和提升技能培训计划，以惠及多方利益相关者——学生、职业转换者、当前的IT工作者、雇主和教育者——大规模提升工作者以适应AI时代。
在其首阶段工作中，联盟将评估AI对56个ICT岗位角色的影响，并为受影响岗位提供培训建议。这些岗位角色根据Indeed Hiring Lab的数据，包括在2023年2月至2024年期间在美国和五个ICT劳动力最多的欧洲国家（法国、德国、意大利、西班牙和荷兰）获得最高岗位发布量的前45个ICT职位的80%。这些国家的ICT部门共计拥有1000万名ICT工作者，占据了行业的重要份额。
联盟成员普遍认识到，随着AI在商业的所有方面的加速融合，及时集结力量，建立一个包容性、能提供维持家庭生活机会的劳动力市场的重要性。联盟成员承诺，在将越来越多地整合人工智能技术的职业领域，开发工作者路径。为此，联盟成员设定了具有远见的目标，并通过技能发展和培训计划，在未来十年内对全球超过9500万人产生积极影响。联盟成员的目标包括：
思科承诺到2032年为2500万人提供网络安全和数字技能培训。
IBM将在2030年前为3000万人提供数字技能培训，包括200万人的AI技能。
英特尔计划到2030年为超过3000万人提供当前和未来工作的AI技能。
微软承诺到2025年为来自弱势社区的1000万人提供需求旺盛的数字技能培训和认证，为他们在数字经济中提供工作和生计机会。
SAP计划到2025年为全球200万人提供提升技能培训。
谷歌最近宣布投入2500万欧元，支持全欧洲人民的AI培训和技能提升。
埃森哲
“帮助组织识别技能差距并进行大规模快速培训是埃森哲的重点任务，这个联盟汇集了一系列致力于在我们社区中发展尖端技术、数据和AI技能的行业合作伙伴。在各个行业中，为与AI协同工作的人员进行重新培训至关重要。那些在技术投资中与学习投资同等重视的组织，不仅创造了职业发展路径，还能在市场中占据领先地位。” - 埃森哲首席领导力与人力资源官Ellyn Shook
Eightfold
“工作的动态和本质正在以前所未有的速度演变。Eightfold通过深入分析最受欢迎的职位，了解重新培训和提升技能的需求。通过其人才智能平台，我们为商业领袖提供了迅速适应不断变化的商业环境的能力。我们为能够为组织预备未来工作做出贡献而感到自豪。” - Eightfold AI首席执行官兼联合创始人Ashutosh Garg
谷歌
“谷歌坚信，技术创造的机遇应真正面向所有人。我们自豪地加入AI赋能工作力联盟，进一步推动我们使AI技能培训普及化的工作。我们致力于跨领域合作，确保不同背景的工作者都能有效利用AI，为面向未来的职位做好准备，获得新机会，在经济中茁壮成长。” - 谷歌成长计划创始人Lisa Gevelber
IBM
“IBM自豪地加入这个及时的企业主导倡议，通过汇集我们的共同专业知识和资源，为AI时代的劳动力做好准备。作为行业领袖，我们共同的责任是发展可信赖的技术，并为所有背景和经验水平的工作者提供学习新技能和提升现有技能的机会，以应对AI采纳改变工作方式并创造新职位的挑战。” - IBM欧洲中东非洲人力资源副总裁Gian Luigi Cattaneo
Indeed
“Indeed的使命是帮助人们找到工作。我们的研究表明，Indeed上今天发布的几乎每个职位，从卡车司机到医生到软件工程师，都将面临不同程度的受到基于GenAI的变革的影响。我们期待为工作力联盟的重要工作做出贡献。那些授权其员工学习新技能并获得与不断发展的AI工具的实践经验的公司，将加深他们的专业团队，提高员工留存率并扩大其合格候选人库。” - Indeed AI创新部门负责人Hannah Calhoon
英特尔
“作为全球AI创新的领导者，英特尔自豪地加入ICT工作力联盟，继续我们的努力，为所有人塑造一个包容和公平的技术未来。作为联盟的一员，我们将与行业领袖合作，分享最佳实践，创造可访问的学习机会，并与各方利益相关者协作，确保工作者掌握了迎接明天的技术技能。” - 微软人力资源法律副总裁兼副总法律顾问Amy Pannoni
SAP
“SAP自豪地加入这一努力，帮助为未来的工作准备我们的劳动力，并确保AI在企业和职位中的应用是相关的、可靠的、负责任的。面对我们不断变化的世界的复杂性，AI有潜力重塑行业、革新解决问题的方式，并释放前所未有的人类潜能，使我们能够构建一个更智能、更高效和更包容的劳动力。多年来，SAP支持了许多技能发展计划，我们期待作为联盟的一部分推动更多的学习机会、创新和积极变化。” - SAP副总裁兼全球开发学习负责人Nicole Helmer
关于思科
思科（纳斯达克代码：CSCO）是全球技术领袖，通过帮助我们的客户重新构想他们的应用、支持混合工作模式、保障企业安全、改造基础设施，并实现可持续发展目标，连接一切，让任何事情成为可能。在新闻室了解更多信息，并在X上关注我们@Cisco。
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来源：思科公司
LEUVEN, Belgium, April 4, 2024 - Cisco (NASDAQ: CSCO) and a group of eight leading companies including Accenture, Eightfold, Google, IBM, Indeed, Intel, Microsoft and SAP as well as six advisors today announced the launch of the AI-Enabled Information and Communication Technology (ICT) Workforce Consortium focused on upskilling and reskilling roles most likely to be impacted by AI. The Consortium is catalyzed by the work of the U.S.-EU Trade and Technology Council's (TTC) Talent for Growth Task Force, with the goal of exploring AI's impact on ICT job roles, enabling workers to find and access relevant training programs, and connecting businesses to skilled and job-ready workers.
Working as a private sector collaborative, the Consortium is evaluating how AI is changing the jobs and skills workers need to be successful. The first phase of work will culminate in a report with actionable insights for business leaders and workers. Further details will be shared in the coming months. Findings will be intended to offer practical insights and recommendations to employers that seek ways to reskill and upskill their workers in preparation for AI-enabled environments.
Consortium members represent a cross section of companies innovating on the cutting edge of AI that also understand the current and impending impact of AI on the workforce. Individually, Consortium members have documented opportunities and challenges presented by AI. The collaborative effort enables their organizations to coalesce insights, recommend action plans, and activate findings within their respective broad spheres of influence.
"AI is accelerating the pace of change for the global workforce, presenting a powerful opportunity for the private sector to help upskill and reskill workers for the future," said Francine Katsoudas, Executive Vice President and Chief People, Policy & Purpose Officer, Cisco. "The mission of our newly unveiled AI-Enabled Workforce Consortium is to provide organizations with knowledge about the impact of AI on the workforce and equip workers with relevant skills. We look forward to engaging other stakeholders—including governments, NGOs, and the academic community—as we take this important first step toward ensuring that the AI revolution leaves no one behind."
The Consortium's work is inspired by the TTC's Talent for Growth Task Force and Cisco Chair and CEO Chuck Robbins' leadership of its skills training workstream, and input from the U.S. Department of Commerce. The TTC was established in June 2021 by U.S. President Biden, European Commission President von der Leyen, and European Council President Michel to promote U.S. and EU competitiveness and prosperity through cooperation and democratic approaches to trade, technology, and security.
"At the U.S. Department of Commerce, we're focused on fueling advanced technology and deepening trade and investment relationships with partners and allies around the world. This work is helping us build a strong and competitive economy, propelled by a talented workforce that's enabling workers to get into the good quality, high-paying, family-sustaining jobs of the future. We recognize that economic security and national security are inextricably linked. That's why I'm proud to see the efforts of the Talent for Growth Task Force continue with the creation of the AI-Enabled ICT Workforce Consortium," said U.S. Secretary of Commerce Gina Raimondo. "I am grateful to the consortium members for joining in this effort to confront the new workforce needs that are arising in the wake of AI's rapid development. This work will help provide unprecedented insight on the specific skill needs for these jobs. I hope that this Consortium is just the beginning, and that the private sector sees this as a call to action to ensure our workforces can reap the benefits of AI."
The AI-Enabled ICT Workforce Consortium's efforts address a business critical and growing need for a proficient workforce that is trained in various aspects of AI, including the skills to implement AI applications across business processes. The Consortium will leverage its members and advisors to recommend and amplify reskilling and upskilling training programs that are inclusive and can benefit multiple stakeholders – students, career changers, current IT workers, employers, and educators – in order to skill workers at scale to engage in the AI era.
In its first phase of work, the Consortium will evaluate the impact of AI on 56 ICT job roles and provide training recommendations for impacted jobs. These job roles include 80% of the top 45 ICT job titles garnering the highest volume of job postings for the period February 2023-2024 in the United States and five of the largest European countries by ICT workforce numbers (France, Germany, Italy, Spain, and the Netherlands) according to Indeed Hiring Lab. Collectively, these countries account for a significant segment of the ICT sector, with a combined total of 10 million ICT workers.
Consortium members universally recognize the urgency and importance of their combined efforts with the acceleration of AI in all facets of business and the need to build an inclusive workforce with family-sustaining opportunities. Consortium members commit to developing worker pathways particularly in job sectors that will increasingly integrate artificial intelligence technology. To that end, Consortium members have established forward thinking goals with skills development and training programs to positively impact over 95 million individuals around the world over the next 10 years. Consortium member goals include:
Cisco to train 25 million people with cybersecurity and digital skills by 2032.
IBM to skill 30 million individuals by 2030 in digital skills, including 2 million in AI.
Intel to empower more than 30 million people with AI skills for current and future jobs by 2030.
Microsoft to train and certify 10 million people from underserved communities with in-demand digital skills for jobs and livelihood opportunities in the digital economy by 2025.
SAP to upskill two million people worldwide by 2025.
Google has recently announced EUR 25 million in funding to support AI training and skills for people across Europe.
Accenture
"Helping organizations identify skills gaps and train people at speed and scale is a major priority for Accenture, and this consortium brings together an impressive ecosystem of industry partners committed to growing leading-edge technology, data and AI skills within our communities. Reskilling people to work with AI is paramount in every industry. Organizations that invest as much in learning as they do in the technology not only create career pathways, they are well positioned to lead in the market." - Ellyn Shook, chief leadership & human resources officer, Accenture
Eightfold
"The dynamics of work and the very essence of work are evolving at an unprecedented pace. Eightfold examines the most sought-after job roles, delving into the needs for reskilling and upskilling. Through its Talent Intelligence Platform, it empowers business leaders to adapt swiftly to the changing business environment. We take pride in contributing to the creation of a knowledgeable and responsible resource that assists organizations in preparing for the future of work." - Ashutosh Garg, CEO and Co-Founder, Eightfold AI
Google
"Google believes the opportunities created by technology should truly be available to everyone. We're proud to join the AI-Enabled Workforce Consortium, which will advance our work to make AI skills training universally accessible. We're committed to collaborating across sectors to ensure workers of all backgrounds can use AI effectively and develop the skills needed to prepare for future-focused jobs, qualify for new opportunities, and thrive in the economy." - Lisa Gevelber, Founder, Grow with Google
IBM
"IBM is proud to join this timely business-led initiative, which brings together our shared expertise and resources to prepare the workforce for the AI era. Our collective responsibility as industry leaders is to develop trustworthy technologies and help provide workers—from all backgrounds and experience levels—access to opportunities to reskill and upskill as AI adoption changes ways of working and creates new jobs." - Gian Luigi Cattaneo, Vice President, Human Resources, IBM EMEA
Indeed
"Indeed's mission is to help people get jobs. Our research shows that virtually every job posted on Indeed today, from truck driver to physician to software engineer, will face some level of exposure to GenAI-driven change. We look forward to contributing to the Workforce Consortium's important work. The companies who empower their employees to learn new skills and gain on-the-job experience with evolving AI tools will deepen their bench of experts, boost retention and expand their pool of qualified candidates." - Hannah Calhoon, Head of AI Innovation at Indeed
Intel
"At Intel, our purpose is to create world-changing technology that improves the lives of every person on the planet, and we believe bringing AI everywhere is key for businesses and society to flourish. To do so, we must provide access to AI skills for everyone. Intel is committed to expanding digital readiness by collaborating with 30 countries, empowering 30,000 institutions, and training 30 million people for current and future jobs by 2030. Working alongside industry leaders as part of this AI-enabled ICT workforce consortium will help upskill and reskill the workforce for the digital economy ahead." – Christy Pambianchi, Executive Vice President and Chief People Officer at Intel Corporation
Microsoft
"As a global leader in AI innovation, Microsoft is proud to join the ICT Workforce Consortium and continue our efforts to shape an inclusive and equitable technology future for all. As a member of the consortium, we will work with industry leaders to share best practices, create accessible learning opportunities, and collaborate with stakeholders to ensure that workers are equipped with the technology skills of tomorrow," - Amy Pannoni, Vice President and Deputy General Counsel, HR Legal at Microsoft
SAP
"SAP is proud to join this effort to help prepare our workforce for the jobs of the future and ensure AI is relevant, reliable, and responsible across businesses and roles. As we navigate the complexities of our ever-evolving world, AI has the potential to reshape industries, revolutionize problem-solving, and unlock unprecedented levels of human potential, enabling us to create a more intelligent, efficient, and inclusive workforce. Over the years, SAP has supported many skills building programs, and we look forward to driving additional learning opportunities, innovation, and positive change as part of the consortium." - Nicole Helmer, Vice President & Global Head of Development Learning at SAP
About Cisco
Cisco (NASDAQ: CSCO) is the worldwide technology leader that securely connects everything to make anything possible. Our purpose is to power an inclusive future for all by helping our customers reimagine their applications, power hybrid work, secure their enterprise, transform their infrastructure, and meet their sustainability goals. Discover more on The Newsroom and follow us on X at @Cisco.
Cisco and the Cisco logo are trademarks or registered trademarks of Cisco and/or its affiliates in the U.S. and other countries. A listing of Cisco's trademarks can be found at www.cisco.com/go/trademarks. Third-party trademarks mentioned are the property of their respective owners. The use of the word partner does not imply a partnership relationship between Cisco and any other company.
SOURCE Cisco Systems, Inc.
SHRM:Most American Workers Experience Incivility in the Workplace; Divisive Dialogue Undermines Inclusion and Employee Wellbeing
2024年SHRM文明研究指出，工作场所不文明行为日益普遍，近三分之二的员工在过去一个月内经历或目睹了此类行为。研究强调维护文明的重要性，将不文明的工作环境与员工不满和更高的离职率联系起来。不文明行为阻碍了员工真实自我表达和福祉，导致员工过滤他们的话语并犹豫不决地分享诚实的想法。研究确定了工作场所观察到的五大不文明行为，并鼓励组织通过参与文明对话来促进文明。
SHRM Launches "1 Million Civil Conversations" Initiative to Propel Workplace Civility
ALEXANDRIA, Va.SHRM, the trusted authority on all things work, today announced its "1 Million Civil Conversations" initiative, aimed at fostering inclusive and respectful workplace cultures that allow people and business to thrive. A reported two-thirds of U.S. workers experienced or witnessed incivility in their workplace over the past month, underscoring the critical need to foster spaces of respect and understanding. SHRM believes everyone can play a role in transforming workplaces to be more civil, one conversation at a time.
With two major elections on the horizon in 2024 (United States and India), the world will likely see heightened tensions and polarizing viewpoints. In addition to challenging people worldwide to engage in 1 million civil conversations this year, SHRM is equipping employers with the necessary research, resources, and guidance to empower their workforce with the skills and tools to foster civil dialogue in their workplaces.
SHRM 2024 research shows the disturbing trend of incivility in today's workplaces, ultimately impacting workplace wellbeing and employee retention:
Two-thirds of U.S. workers (66%) experienced or witnessed incivility in the workplace over the past month.
Workers who rate their workplace as uncivil are three times more likely to express job dissatisfaction (28%); and more than twice as likely to consider leaving their job in the next year (38%).
Thirty three percent of U.S. workers expect workplace conflict to increase over the next 12 months.
Johnny C. Taylor, Jr., SHRM-SCP, SHRM President and CEO, emphasizes the significance of individual contributions to building a truly inclusive workplace culture. "If we want to build a world of work that works for all, we need more than corporate objectives. Civility is inclusion in action and must be carried out by the people in their daily interactions," he affirms. “Looking forward, the future of work hinges on collaboration, ideation, and innovation, with civility serving as the indispensable catalyst for bridging discord and empowering workforce synergy. SHRM is encouraging organizations and individuals to be catalysts for civility by starting 1 million civil conversations.”
Throughout 2024, SHRM will be engaging people across the country through experiential pop-up events and will be measuring civility by the upcoming Civility Index, a periodic pulse survey designed to gauge the prevailing levels of civility in the workplace and society.
Learn more about how SHRM is creating more civil workplaces and how you can join the conversation at https://www.shrm.org/topics-tools/topics/civility
SHRM is a member-driven catalyst for creating better workplaces where people and businesses thrive together. As the trusted authority on all things work, SHRM is the foremost expert, researcher, advocate, and thought leader on issues and innovations impacting today’s evolving workplaces. With nearly 340,000 members in 180 countries, SHRM touches the lives of more than 362 million workers and their families globally. Discover more at SHRM.org.
[caption id="attachment_1678" align="alignnone" width="1056"] "1 Million Civil Conversations"[/caption]
collaboration
2024年03月08日
collaboration
How Generative AI Adds Value to the Future of Work
这篇Upwork的文章深入探讨了生成式人工智能（AI）在重新塑造工作价值方面的变革力量，强调了自动化和创新不仅改变了工作岗位，还在各个行业提高了生产力和创造力。文章着重讨论了对劳动力市场的细微影响，强调了技能发展和道德考虑的重要性，并对人工智能与人类合作的未来提供了前瞻性的视角。
Authors: Dr. Ted Liu, Carina Deng, Dr. Kelly Monahan
Generative AI’s impact on work: lessons from previous technology advancements
In this study, we provide a comprehensive analysis of the initial impact of generative AI (artificial intelligence) on the Upwork marketplace for independent talent. Evidence from previous technological innovations suggests that AI will have a dual impact: (1) the displacement effect, where job or task loss is initially more noticeable as technologies automate tasks, and (2) the reinstatement effect, where new jobs and tasks increase earnings over time as a result of the new technology. Take for example the entry of robotics within the manufacturing industry. When robotic arms were installed along assembly lines, they displaced some of the tasks that humans used to do. This was pronounced in tasks that were routine and easy to automate. However, new tasks were then needed with the introduction of robotics, such as programming the robots, analyzing data, building predictive models, and maintaining the physical robots. The effects of new technologies often counterbalance each other over time, giving way to many new jobs and tasks that weren’t possible or needed before. The manufacturing industry is now projected to have more jobs available as technologies continue to advance, including Internet of Things (IoT), augmented reality, and AI, which transform the way work is completed. The issue now at hand is ensuring enough skilled workers are able to work alongside these new technologies.
While this dynamic of displacement and reinstatement generally takes years to materialize, as noted above in the manufacturing example, the effects of generative AI may be taking place already on Upwork. For the platform as a whole, we observe that generative AI has increased the total number of job posts and the average spend per new contract created. In terms of work categories, generative AI has reduced demand in writing and translation, particularly in low-value work, while enhancing earnings in high-value work across all groups. In particular, work that relies on this new technology like Data Science and Analytics are reaping the benefits. The report highlights the importance of task complexity and the skill-biased nature of AI's impact. Skills-biased technology change is to be expected as the introduction of new technologies generally favors highly skilled workers. We observe this on our platform as high-skill freelancers in high-value work are benefiting more, while those in low-value work face challenges, underscoring the need for skilling and educational programs to empower freelancers to adapt and transition in this evolving work landscape.
Understanding the lifecycle of work on Upwork and the impact of gen AI
Generative AI has a growing presence in how people do their work, especially since the public release of ChatGPT in 2022. While there’s been extensive discussion about the challenges and opportunities of generative AI, there is limited evidence of such impact based on transaction data in the broader labor market. In this study, we use Upwork’s platform data to estimate the short-term effects of generative AI on freelance outcomes specifically. The advantage of the Upwork platform is that it is in itself a complete marketplace for independent talent, as we observe the full life cycle of work: job posts, matching, work execution, performance reviews, and payment. Few other instances exist where a closed-system work market can be studied and observed. Thus, the results of this study offer insights into not only the online freelance market, but also the broader labor market.
How technological progress disrupts the labor market is not a new topic. Acemoglu and Restrepo (2019) argue that earning gain arises from new tasks created by technological progress, which they term the “reinstatement effect,” even if the automation of certain tasks may have a displacement effect in the labor market initially. What this means is that there may be a dynamic effect going on: the displacement effect (e.g., work loss) may be more noticeable in the beginning of a new technology entry, but as new jobs and tasks are being created, the reinstatement effect (e.g., rates increase, new work) will begin to prevail. In the broader labor market, such dynamics will likely take years to materialize. But in a liquid and active independent work marketplace like Upwork, it’s possible that we’re already observing this transition happening.
Existing studies such as this provides a useful conceptual framework to think about the potential impact of generative AI. It’s likely that in the short term, the replacement of generative AI will continue to be more visible, not just at Upwork, but also in the broader labor market. Over time and across work categories, however, generative AI will likely spur new tasks and jobs, leading to the reinstatement effect becoming stronger and increasing rates for those occupations with new tasks and a higher degree of task complexity. We’ve already seen evidence of new demand as a result of gen AI on our Upwork platform, with brand new skill categories like AI content creator and prompt engineer emerging in late 2022 and early 2023. We test this hypothesis of both work displacement and reinstatement, and provide insights into how generative AI affects work outcomes.
Impact of generative AI on work
To understand the short-term impact of generative AI on the Upwork freelance market, we capitalize on a natural experiment arising from the public release of ChatGPT in November 2022. Because this release was largely an unanticipated event to the general public, we’re able to estimate the causal impact of generative AI. The essential idea behind this natural experiment is that we want to compare the work groups affected by AI with the counterfactual in which they are not. To implement this, we use a statistical and machine-learning method called synthetic control. Synthetic control allows us to see the impact that an intervention, in this case, the introduction of gen AI, has on a group over time by comparing it to a group with similar characteristics not exposed to the intervention. The advantage of this approach is that it allows us to construct reasonably credible comparison groups and observe the effect over time.
The units of analysis we use are work groups on the Upwork platform; we analyze variables such as contract number and freelancer earnings. Instead of narrowly focusing on a single category like writing, we extend the analysis to all the major work groups on Upwork. Moreover, we conduct additional analysis of the more granular clusters within each major group. The synthetic control method allows for flexibility in constructing counterfactuals at different levels of granularity. The advantage of our comprehensive approach is that we offer a balanced view of the impact of generative AI across the freelance market.
Generative AI’s short-term impact on job posts and freelancer earnings
Looking at the platform as a whole, we observe that generative AI has increased the total number of job posts by 2.4%, indicating the overall increased demand from clients. Moreover, as shown in Figure 1, for every new job contract, there is an increase of 1.3% in terms of freelancer earnings per contract, suggesting a higher value of contracts.
Figure 1 Effect of Generative AI on Freelancer Earning per Contract
The Upwork platform has three broad sectors: 1. Technological and digital solutions (tech solutions); 2. Creative & outreach; 3. Business operations and consulting. We have observed both positive and negative effects within each of the sectors, but two patterns are worth noting:
The reinstatement effect of generative AI seems to be driving growth in freelance earnings in sectors related to tech solutions and business operations. In contrast, within the creative sector, while sales and marketing earnings have grown because of AI, categories such as writing and translation seem disproportionately affected more by the replacement effect. This is to be expected due to the nature of tasks within these categories of work, where large language models are now able to efficiently process and generate text at scale.
Generative AI has propelled growth in high-value work across the sectors and may have depressed growth in low-value work. This supports a skills-biased technology change argument, which we’ve observed throughout modern work history.
More specifically and within tech solutions, data science & analytics is a clear winner, with over 8% of growth in freelance earnings attributed to generative AI. This makes sense as the reinstatement effect is at work; new work and tasks such as prompt engineering have been created and popularized because of generative AI. Simultaneously, while tools such as ChatGPT automate certain scripting tasks (therefore leading to a replacement effect), it mainly results in productivity enhancements for freelancers and potentially leads to them charging higher rates and enjoying higher overall earnings per task.
In terms of contracts related to business operations, we observe that accounting, administrative support, and legal services all experience gains in freelance earnings due to generative AI, ranging from 6% to 7%. In this sector, customer service is the only group that has experienced reduced earnings (-4%). The reduced earnings result for customer service contracts is an example of the aggregate earnings outcomes of AI, related to the study by Brynjolfsson et al (2023), who find that generative AI helps reduce case resolution time at service centers.
A potential outcome of this cut in resolution time is that service centers will need fewer workers, as more tasks can be completed by a person working alongside AI. At the same time, the reinstatement effect has not materialized yet because there are no new tasks being demanded in such settings. This may be an instance where work transformation has not yet been fully realized, with AI enabling faster work rather than reinventing a way of working that leads to new types of tasks. A contrasting case is the transformation that happened with bank tellers when ATMs were introduced. While the introduction of these new technologies resulted in predictions of obsolete roles in banks, something different happened over time. Banks were able to increase efficiency as a result of ATMs and were able to scale and open more branches than before, thereby creating more jobs. In addition, the transactional role of a bank teller became focused on greater interpersonal skills and customer relationship tasks.
When taken together, the overall gains in such business operations work on Upwork are an encouraging sign. These positions tend to require relatively intensive interpersonal communication, and it seems the short-term effects of generative AI have helped increase the value of these contracts, similar to what we saw in the banking industry when ATMs were introduced.
As of now, the replacement effect of AI seems more noticeable in creative and outreach work. The exception is sales and marketing contracts, which have experienced a 6.5% increase in freelance earnings. There is no significant impact yet observed on design. For writing and translation, however, generative AI seems to have reduced earnings by 8% and 10% respectively. However, as we will discover, task complexity has a moderating effect on this.
High-value work benefit from generative AI, upskilling needed for low-value work
Having discussed the overall impact of generative AI across categories, we now decompose the impact by values. The reason we’re looking at the dimension of work value is that there may be a positive correlation between contract value and skill complexity. Moreover, skill complexity may also be positively correlated with skill levels. Essentially, by evaluating the impact of AI by different contract values, we can get at the question of AI's impact by skill levels. This objective is further underscored by a discrepancy that sometimes exists in the broader labor markets – a skills gap between demand and supply. It simply takes time for upskilling to take place, so it’s typical for demand to exceed supply until a more balanced skilled labor market takes place. It is worth noting, however, freelancers on the Upwork platform seem more likely than non-freelancers to acquire new skills such as generative AI.
For simplicity, let’s assume that the value of contracts is a good proxy for the level of skill required to complete them. We’d then assume that high-skill freelancers typically do high-value work, and low-skill freelancers do low-value work. In other words, our goal is also to understand whether the impact of generative AI is skills-biased and follows a similar pattern from what we’ve seen in the past with new technology disruptions. Note that we’re focusing on the top and bottom tails of the distribution of contract values, because such groups (rather than median or mean) might be most susceptible to displacement and/or reinstatement effects, therefore of primary concern. We define high-value (HV) work as those with $1,000 or more earnings per contract. For the remaining contracts, we focus on a subset of work as low-value (LV) work ($251-500 earnings).
Figure 2 shows the impact of AI by work value, across groups on Upwork. As we discussed before, writing and translation work has experienced some reduction in earnings overall. However, if we look further into the effect of contract value, we see that the reduction is largely coming from the reduced earnings from low-value work. At the same time, for these two types, generative AI has induced substantial growth in high-value earnings – the effect for translation is as high as 7%. We believe the positive effect on translation high-value earning is driven by more posts and contracts created. In the tech solutions sector, the growth in HV earnings in data science and web development is also particularly noticeable, ranging from 6% to 9%. Within the business solutions sector, administrative support is the clear winner.
There are two takeaways from this analysis by work value. First, while we’re looking at a sample of all the contracts on the platform, it’s possible that the decline of LV work is more than made up for by the growth of HV work in the majority of the groups. In other words, except for select work groups, the equilibrium results for the Upwork freelance market overall seem to be net positive gains from generative AI. Second, if we assume that freelancers with high skills (or a high degree of skill complexity) tend to complete such HV work (and low-skill freelancers do LV work), we observe that the impact of generative AI may be biased against low-skill freelancers. This is an important result: In the current discussion of whether generative AI is skill-based, there exists limited evidence based on realized gains and actual work market transactions. We are one of the first to provide market-transaction-based evidence to illustrate this potentially skill-biased impact. Finally, additional internal Upwork analysis finds that independent talent engaged in AI-related work earn 40% more on the Upwork marketplace than their counterparts engaged in non-AI-related work. This suggests there may be additional overlap between high-skill work and AI-related work, which can further reinforce the earning potential of freelancers in this group.
Figure 2
Case study: 3D content work
To illustrate the impact of generative AI in more depth, we have conducted a case study of Engineering & Architecture work within the tech solutions sector. The reason is that we want to illustrate the potentially overlooked aspects of AI impact, compared with the examples of data science and writing contracts. This progress in generative AI has the potential to reshape work in traditional areas like design in manufacturing and architecture, which rely heavily on computer-aided design (CAD) objects, and newer sectors such as gaming and virtual reality, exemplified by NVIDIA's Omniverse.
Based on activities on the Upwork platform, we see that there is consistent growth of job posts and client spending in this category, with up to 12% of gross service value growth year over year in 2023 Q3, and over 11% in job posts during the same period. Moreover, applying the synthetic control method, we show a causal relationship between gen AI advancements and the growth in job posts and earnings per contract. More specifically, there is a significant increase in overall earnings because of AI, an average 11.5% increase. Additionally, as shown by Figure 3, the positive effect also applies to earning per contract. This indicates a positive impact on freelancer productivity and quality of work, due to the fact that we’re measuring the income for every unit of work produced. This suggests that gen AI is not just a facilitator of efficiency but also enhances the quality of output.
Figure 3 Effect of Generative AI on Freelancer Earning per Contract in EngineeringIn a traditional workflow to create 3D objects without generative AI, freelancers would spend extensive time and effort to design the topology, geometry, and textures of the objects. But with generative AI, they can do so through text prompts to train models and generate 3D content. For example, this blog by NVIDIA’s Omniverse team showcases how ChatGPT can interface with traditional 3D creation tools.
Thus, the positive trajectory of generative AI in 3D content generation we see is driven by several factors. AI significantly reduces job execution time, allowing for higher productivity. It facilitates the replication and scaling of 3D objects, leading to economies of scale. Moreover, freelancers can now concentrate more on the creative aspects of 3D content, as AI automates time-consuming and tedious tasks.
This shift has not led to a decrease in rates due to the replacement effect. In fact, this shift of workflow may create new tasks and work. We will likely see a new type of occupation in which technology and humanities disciplines converge. For instance, a freelancer trained in art history now has the tools to recreate a 3D rendering of Japan in the Edo period, without the need to conduct heavy coding. In other words, the reinstatement effect of AI will elevate the overall quality and value proposition of the work, and ultimately enable higher earning gains. This paradigm shift underscores generative AI's role in not just transforming work processes but also in creating new economic dynamics within the 3D content market. Fortunately, it seems many freelancers on Upwork are ready to reap the benefits: 3D-related skills, such as 3D modeling, rendering, and design, are listed among the top five skills of freelancer profiles as well as in job posts.
A dynamic interplay: task complexity, skills, and gen AI
Focusing on the Upwork marketplace for independent talent, we study the impact of generative AI by using the public release of ChatGPT as a natural experiment. The results suggest a dynamic interplay of replacement and reinstatement effects; we argue that this dynamic is influenced by task complexity, suggesting a skill-biased impact of gen AI. Analysis across Upwork's work sectors shows varied effects: growth in freelance earnings in tech solutions and business operations, but a mixed impact in the creative sector. Specifically, high-value work in data science and business operations see significant earnings growth, while creative contracts like writing and translation experience a decrease in earnings, particularly in lower-value tasks. Using the case study of 3D content creation, we show that generative AI can significantly enhance productivity and quality of work, leading to economic gains and a shift toward higher-value tasks, despite initial concerns of displacement.
Acemoglu and Restrepo (2019) argue that the slowdown of earning growth in the United States the past three decades can partly be explained by new technologies’ replacement effect overpowering the reinstatement effect. But with generative AI, we’re at a point of completely redefining what human tasks mean, and there may be ample opportunities to create new tasks and work. It's evident that while high-value types of work are being created, freelancers engaged in low-value tasks may face negative impact, possibly due to a lack of skills needed to capitalize on AI benefits. This situation underscores the necessity of supporting freelancers not only in elevating their marketability within their current domains but also in transitioning to other work categories.
To ensure as many people as possible benefit, there’s an imperative need to provide educational resources for them to gain the technical skills, and more importantly skills of adaptability to reinvent their work. This helps minimize the chance of missed opportunities by limiting skills mismatch between talent and new demands created by new technologies. Upwork has played a significant role here by linking freelancers to resources such as Upwork Academy’s AI Education Library and Education Marketplace, thereby equipping them with the necessary tools and knowledge to adapt and thrive in an AI-present job market. This approach can help bridge the gap between low- and high-value work opportunities, ensuring a more equitable distribution of the advantages brought about by generative AI.
Methodology
To estimate the causal impact of generative AI, we take a synthetic control approach in the spirit of Abadie, Diamond, and Hainmueller (2010). The synthetic control method allows us to construct a weighted combination of comparison units from available data to create a counterfactual scenario, simulating what would have happened in the absence of the intervention. We use this quasi-experimental method due to the infeasibility of conducting a controlled large-scale experiment. Additionally, we use Lasso regularization to credibly construct the donor pool that serves the basis of the counterfactuals and minimize the chance of overfitting the data.
Moreover, we supplement the analysis by scoring whether a sub-occupation is impacted or unaffected by generative AI. The scoring utilizes specific criteria: 1. Whether a certain share of job posts are tagged as AI contracts by the Upwork platform; 2. AI occupational exposure score, based on a study by Felten, Raj, and Seamans (2023), to tag these sub-occupations. We also use data smoothing techniques through three-month moving averages. We analyzed data collected on our platform from 2021 through Q3 2023. We specifically look at freelancer data across all 12 work categories on the platform for high-value contracts, defined as those with a contract of at least $1,000, and low-value contracts, consisting of those between $251 and under $500.
The main advantage of our approach is that it is a robust yet flexible way to identify the causal effects on not only the Upwork freelance market but also specific work categories. Additionally, we control for macroeconomic or aggregate shocks such as U.S. monetary policy in the pre-treatment period. However, we acknowledge the potential biases in identifying which sub-occupations are influenced by generative AI and the effects of external factors in the post-treatment period.
About the Upwork Research Institute
The Upwork Research Institute is committed to studying the fundamental shifts in the workforce and providing business leaders with the tools and insights they need to navigate the here and now while preparing their organization for the future. Using our proprietary platform data, global survey research, partnerships, and academic collaborations, we produce evidence-based insights to create the blueprint for the new way of work.
About Ted Liu
Dr. Ted Liu is Research Manager at Upwork, where he focuses on how work and skills evolve in relation to technological progress such as artificial intelligence. He received his PhD in economics from the University of California, Santa Cruz.
About Carina Deng
Carian Deng is the Lead Analyst in Strategic Analytics at Upwork, where she specializes in uncovering data insights through advanced statistical methodologies. She holds a Master's degree in Data Science from George Washington University.
About Kelly Monahan
Dr. Kelly Monahan is Managing Director of the Upwork Research Institute, leading our future of work research program. Her research has been recognized and published in both applied and academic journals, including MIT Sloan Management Review and the Journal of Strategic Management.
collaboration
2024年02月23日
collaboration
Workday: It’s Time to Close the AI Trust GapWorkday, a leading provider of enterprise cloud applications for finance and human resources, has pressed a global study recently recognizing the importance of addressing the AI trust gap. They believe that trust is a critical factor when it comes to implementing artificial intelligence (AI) systems, especially in areas such as workforce management and human resources.
Research results are as follows:
At the leadership level, only 62% welcome AI, and only 62% are confident their organization will ensure AI is implemented in a responsible and trustworthy way. At the employee level, these figures drop even lower to 52% and 55%, respectively.
70% of leaders say AI should be developed in a way that easily allows for human review and intervention. Yet 42% of employees believe their company does not have a clear understanding of which systems should be fully automated and which require human intervention.
1 in 4 employees (23%) are not confident that their organization will put employee interests above its own when implementing AI. (compared to 21% of leaders)
1 in 4 employees (23%) are not confident that their organization will prioritize innovating with care for people over innovating with speed. (compared to 17% of leaders)
1 in 4 employees (23%) are not confident that their organization will ensure AI is implemented in a responsible and trustworthy way. (compared to 17% of leaders)
“We know how these technologies can benefit economic opportunities for people—that’s our business. But people won’t use technologies they don’t trust. Skills are the way forward, and not only skills, but skills backed by a thoughtful, ethical, responsible implementation of AI that has regulatory safeguards that help facilitate trust.” said Chandler C. Morse, VP, Public Policy, Workday.
Workday’s study focuses on various key areas:
Section 1: Perspectives align on AI’s potential and responsible use.
“At the outset of our research, we hypothesized that there would be a general alignment between business leaders and employees regarding their overall enthusiasm for AI. Encouragingly, this has proven true: leaders and employees are aligned in several areas, including AI’s potential for business transformation, as well as efforts to reduce risk and ensure trustworthy AI.”
Both leaders and employees believe in and hope for a transformation scenario* with AI.
Both groups agree AI implementation should prioritize human control.
Both groups cite regulation and frameworks as most important for trustworthy AI.
Section 2: When it comes to the development of AI, the trust gap between leaders and employees diverges even more.
“While most leaders and employees agree on the value of AI and the need for its careful implementation, the existing trust gap becomes even more pronounced when it comes to developing AI in a way that facilitates human review and intervention.”
Employees aren’t confident their company takes a people-first approach.
At all levels, there’s the worry that human welfare isn’t a leadership priority.
Section 3: Data on AI governance and use is not readily visible to employees.
“While employees are calling for regulation and ethical frameworks to ensure that AI is trustworthy, there is a lack of awareness across all levels of the workforce when it comes to collaborating on AI regulation and sharing responsible AI guidelines.”
Closing remarks: How Workday is closing the AI trust gap.
Transparency: Workday can prioritize transparency in their AI systems. Providing clear explanations of how AI algorithms make decisions can help build trust among users. By revealing the factors, data, and processes that contribute to AI-driven outcomes, Workday can ensure transparency in their AI applications.
Explainability: Workday can work towards making their AI systems more explainable. This means enabling users to understand the reasoning behind AI-generated recommendations or decisions. Employing techniques like interpretable machine learning can help users comprehend the logic and factors influencing the AI-driven outcomes.
Ethical considerations: Working on ethical frameworks and guidelines for AI use can play a crucial role in closing the trust gap. Workday can ensure that their AI systems align with ethical principles, such as fairness, accountability, and avoiding bias. This might involve rigorous testing, auditing, and ongoing monitoring of AI models to detect and mitigate any potential biases or unintended consequences.
User feedback and collaboration: Engaging with users and seeking their feedback can be key to building trust. Workday can involve their customers and end-users in the AI development process, gathering insights and acting on user concerns. Collaboration and open communication will help Workday enhance their AI systems based on real-world feedback and user needs.
Data privacy and security: Ensuring robust data privacy and security measures is vital for instilling trust in AI systems. Workday can prioritize data protection and encryption, complying with industry standards and regulations. By demonstrating strong data privacy practices, they can alleviate concerns associated with AI-driven data processing.
SOURCE Workday
视频：Leading Through Transformation The Future of HR in the AI Era
Leading Through Transformation The Future of HR in the AI Era
Jiajia Chen
Senior Group Product Manager
Nvidia
点击访问：https://www.youtube.com/watch?v=toiy_sBDXHs
以下为演讲稿翻译整理，仅供参考：
引领变革：人工智能时代人力资源的未来
欢迎大家，我很高兴有机会讨论一个自2022年底以来成为焦点的话题。随着chat的广泛成功，许多人开始思考一个问题：我还会有工作吗？对于一些父母来说，这个问题可能会有所不同：我的孩子将来会有工作吗？在深入这个问题之前，让我简单介绍一下自己。我早期的职业生涯涉及多个商业领域，包括人力资源，后来我专注于人工智能产品管理。我拥有几个学位，包括法律学位、MBA学位、经济学科学学位和软件工程学位。我曾在Nidia管理人工智能基础设施产品组合几年。去年晚些时候，我转移到另一个名为Nidia Omniverse的产品组，这是一个数字孪生平台工业元宇宙。我们的企业客户可以使用Omniverse来创建数字孪生工业元宇宙，通过利用模拟和生成性人工智能以及与大型生态系统合作。通过这些经历，我对人工智能和人力资源有了深刻的理解。在这次演讲中，我希望能提供一个框架，帮助大家思考如何在人工智能时代领导转型，如何保持相关性并比人工智能发展得更快。
人工智能并不是一个新概念。让我们快速回顾一下人工智能发展的简史，为今天的对话奠定基础。人工智能领域诞生于1950年代。1950年，艾伦·图灵提出了模仿人类智能的通用机器的概念。1956年，人工智能这一术语被创造出来。在1970年代和1980年代，人工智能最初的乐观预期开始减弱，因为进展没有达到高期望，人工智能研究的资金减少，领域经历了被称为人工智能冬天的时期。在人工智能冬天期间，研究人员专注于发展专家系统，这是基于规则的系统，旨在模仿人类专家在特定领域的知识和决策能力。这种方法在实际应用中取得了一些进展，例如医学诊断和工业自动化。1980年代，人工智能的焦点转向了机器学习和神经网络。机器学习算法允许计算机在没有明确编程的情况下从数据中学习，并做出预测或决策。受人类大脑结构启发的神经网络引起了关注，并被应用于各种任务，包括图像和语音识别。得益于大量数据的可用性和计算能力的进步，人工智能经历了复兴。Nidia的贡献是关键的。
2022年11月推出的ChatGPT标志着人工智能的关键时刻。生成性人工智能正在推动机器创造的边界。人工智能越来越多地融入各种应用和行业，正在金融、医疗保健、网络安全等领域发挥作用，转变行业并创造新的机会。
你们中有多少人尝试过ChatGPT？你们喜欢它的哪些功能？是否用它来草拟电子邮件、创建培训材料，或者提出棘手的问题，试图愚弄chat GPT，证明你的人类智能更高级？人工智能预计将在各个维度对工作场所产生重大变化。
以下是人工智能可能带来的九个变化。
首先，提高生产力：人工智能是否会提高生产力和经济增长？许多人这样预期，但也有很多人告诉你，到目前为止，这种生成性人工智能趋势并没有大幅提高生产力，除了提供一些有趣的玩具。你们中的一些人可能听说过“生产力悖论”，这是1970年代和1980年代在美国发生的现象。我的预测是，人工智能不会发生这种情况。人工智能可以更快地传播，且所需的资本投资更少。这是因为人工智能在短期内的应用主要是软件革命，所需的大部分基础设施，如计算设备、网络和云服务，已经到位。你现在可以通过手机立即使用chat GPT和迅速增长的类似软件。
其次，收入不平等：人工智能是否会带来自动化的奢华时代，还是只会加剧现有的不平等？美国国家经济研究局发布的一份报告称，自1980年以来，美国工资变化的50%到70%可以归因于蓝领工人被自动化取代或降级导致的工资下降。人工智能、机器人技术和新的复杂技术导致财富高度集中。直到最近，受过大学教育的白领专业人士基本上没有受到低教育工人的命运。拥有研究生学位的人看到他们的薪水上涨，而低教育工人的薪水显著下降。这一问题将加剧，低技能的白领工人也将受到影响。
第三，劳动力技能提升和风险转移：随着某些任务的自动化，人工智能需要专注于提升和重新技能化劳动力。员工需要获得新的技能和知识，以适应不断变化的工作要求，并有效地与人工智能系统协作。有关这一主题的研究很多，不同研究的数据也有所不同。彭博社的研究显示，由于人工智能对工作的影响，全球将有超过1.2亿工人在未来三年内需要重新培训。据信，由于人工智能相关部署，中国将有超过5000万工人需要重新培训。美国将需要重新培训1150万人，以适应劳动力市场的需求。巴西、日本和德国的数百万工人也将需要帮助应对人工智能、机器人技术及相关技术带来的变化。根据麦肯锡的一项研究，由于快速自动化的采用，多达3.75亿工人可能需要转换职业类别。
第四，重新定义工作角色：人工智能有潜力重塑工作角色并创造新的角色。一些任务和工作可能会完全自动化，导致某些领域的工作流失。然而，人工智能也为创造涉及管理和协作人工智能系统、分析人工智能生成的内容、开发和维护人工智能技术的新角色创造了机会。例子包括美国政府试图将制造业带回美国。许多人认为，像第二次世界大战后一样，将创造数百万高薪的蓝领工人工作。然而，这最有可能不会发生，因为在美国建造的新工厂几乎不会雇用许多人类工人。一切都将通过机器人或管理系统自动化。
第五，增强决策制定：人工智能系统可以分析大量数据，检测模式，并生成支持决策过程的洞察。这可以使员工和管理者获得更准确、更及时的信息，使各种职能（如运营、市场营销、财务、人力资源）的决策更加明智。2019年哈佛商业评论提出了一个概念，称为人工智能驱动的决策，与数据驱动的决策相比，它允许我们克服作为人类处理器的固有局限性，如低效和认知偏见，因为你可以指派机器来处理大量数据，让我们人类应用判断力、文化价值观和情境来选择决策选项。
第六，人工智能与人类的协作：人工智能技术使得人与智能系统之间的协作成为可能。这种协作可能涉及利用人工智能在数据分析、模式识别和预测方面的优势，而人类则提供批判性思维、创造力、同理心和复杂问题解决技能。如果能够有效地实现人与人工智能系统的协作，可以带来改进的成果和创新。的确，许多公司已经使用人工智能自动化流程，但到目前为止，证据表明，那些旨在取代员工的部署只会带来短期的生产力提升。在一项涉及1500家公司的基本研究中发现，当人类和机器一起工作时，公司取得了最显著的绩效提升。
第七，增强智能：人工智能可以通过补充和增强人类能力来增强人类智能。它可以协助人们执行诸如信息检索、数据分析和问题解决等任务。人工智能支持的虚拟助手和机器人可以为人们提供即时支持和指导，提高他们的效率和效果。
第八，伦理考虑：人工智能在工作场所的整合引发了与隐私、安全、公平、透明度和问责制相关的伦理考虑。组织需要建立伦理框架和指南来确保人工智能系统的合理和可信赖的开发和部署。
第九，监控和评估AI实施。这个变化涉及到持续监控人工智能在工作场所的影响，并从员工那里收集反馈，以识别改进领域。定期的评估和反馈循环将有助于完善人工智能的实施和使用，确保其在增进工作效率、创新和其他方面的应用是有效和恰当的。（以上为AI补充，仅供参考）
目前，我们已经详细讨论了人工智能在工作场所创造的变化，以及人力资源应该如何应对这些变化。
现在，让我分享这张早先在一次HR会议上使用的幻灯片。2016年，我在一个名为“HR新模型”的会议上发表了演讲。现在，让我们看看这个模型。一个典型的组织结构包括首席执行官、人力资源业务伙伴、共享服务和一个运营部门，支持管理者和员工群体。公司是否能用这个模型应对人工智能在工作场所带来的变化？我们是否需要一个不同的模型？在回答这个问题之前，让我们看看应对每种类型变化需要发生什么。在这张幻灯片上，我展示了我简单的颜色编码技术。我简单地将所有类型的能力和技能分类并用不同颜色高亮显示。现在我们可以看到几个主要类别和一些零散项目。让我们稍微深入一些颜色分类的挑战。
首先，以蓝色突出显示的助理挑战和两个工作场所的变化。HR可以评估利用人工智能的技能和能力要求，为员工提供必要的资源，使他们能够理解和利用人工智能技术，以及如何通过人工智能来增强他们的工作。这包括关于人工智能概念、数据分析、自动化工具和人工智能支持决策的培训。HR可以培养持续学习的文化。
其次，以绿色突出显示的变革管理和沟通，在四个不同的工作场所变化中出现。HR可以积极地向员工传达人工智能实施的目的和好处，以提高生产力和效率。HR可以协助经理和员工分析工作并重新设计工作流程，以利用人工智能技术。这涉及识别可以自动化或由人工智能增强的任务和活动，简化工作流程，消除冗余或低价值测试，并确定人类和人工智能如何合作以优化生产力和效率。
第三，以热粉色突出显示的职业发展和内部流动性，在三个不同的工作场所变化中出现。HR可以进行技能评估，以确定组织内现有技能，并确定需要解决的AI相关角色的差距。这包括识别与人工智能技术合作所需的技术技能，如机器学习，以及有效沟通、批判性思维和问题解决所必需的软技能。
最后，以灰蓝色突出显示的伦理指导和治理，在三个不同的工作场所变化中出现。HR可以与法律、合规团队等相关利益相关者协作，为人工智能变革建立治理框架。那些仍以黑色显示的功能在未来几年将看到更多的自动化和置换，投资较少，因为这些能力在人工智能转型中的相关性较低。
为了跟上甚至领导人工智能趋势及其对工作场所的影响，HR可以采取几个积极的步骤。以下是我们可以考虑的一些关键行动：持续学习，HR专业人士可以深入了解人工智能技术、应用和影响；识别人力资源中的人工智能用例，HR可以探索各种可以增强其功能和简化流程的人工智能应用，例如自动化日常行政任务、改进候选人筛选和选拔流程，以及提供个性化的学习和发展机会；评估组织的人工智能准备情况，HR可以评估组织当前的基础设施、技术能力和文化，以确定其采用人工智能的准备情况；通信和透明度，人工智能实施期间的沟通和透明度对于缓解对工作安全的担忧、澄清人工智能采用的好处以及确保员工理解人工智能技术将如何增强而非取代他们的工作至关重要；监控和评估人工智能实施，HR可以持续监控人工智能对工作场所的影响，并从员工那里收集反馈，以识别改进领域。定期的评估和反馈循环将有助于完善人工智能实施。
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