Valoir 报告显示 HR 尚未准备好迎接 AI，你呢？
研究显示，人力资源管理领导者面临的主要问题包括缺少 AI 相关的专业知识以及面临的风险和合规性问题。
弗吉尼亚州阿灵顿--Valoir 发布的一项全球新报告显示，尽管 AI 驱动的自动化似乎无法避免，但人力资源部门似乎并未做好准备。这项涵盖超过150位人力资源执行官的调查揭示了利用 AI 的巨大机会，但同时也显示出在制定政策、实施实践和进行培训方面普遍存在不足，以便安全有效地将 AI 技术应用于人力资源管理。
“虽然许多机构开始采用生成式 AI，但很少有组织建立必要的政策、准则和保障措施。作为员工数据的保护者和公司政策的制定者，人力资源领导者需要在 AI 的政策和培训方面走在前列，不仅为自己的团队，也为广大员工群体做好准备。”
以下内容需要特别注意： “AI 正在快速融入人力资源管理领域，特别是在招聘、人才发展和劳动力管理等方面。然而，引入 AI 也伴随着诸如数据泄露、误解、偏见和不当内容等风险，”Valoir 的首席执行官 Rebecca Wettemann 表示。“面对这些挑战并采取措施减少风险的人力资源部门，可以显著提升其从 AI 中获得的益处。”
人力资源的自动化与战略转型潜力
报告指出，有35%的人力资源部门员工的日常工作非常适合自动化处理。在所有人力资源管理活动中，招聘环节最有潜力应用 AI 技术，并且已成为采纳率最高的领域，近四分之一的组织已经开始利用 AI 支持的招聘流程。人才发展、劳动力管理以及培训和发展同样被视为 AI 自动化的关键领域。
生成式 AI 正在加速人力资源部门的生产力提升及风险增加
尽管到2023年中旬，超过三分之四的人力资源领域工作者已经尝试使用过某种形式的生成式 AI，但仅有16%的组织制定了关于使用生成式 AI 的具体政策。而且，真正关于其伦理使用的政策数量更是寥寥无几。人力资源领导者认为，缺乏 AI 相关技能和专业知识是采纳 AI 的最大障碍，但只有14%的组织制定了有效的 AI 使用培训政策。这些政策对于确保所有员工都能充分利用 AI 带来的好处并最小化风险是至关重要的。
“尽管生成式 AI 正被广泛采纳，但几乎没有哪些组织建立了必要的政策、准则和保护措施。作为员工数据的守护者和公司政策的制定者，人力资源领导者必须在 AI 政策和培训方面先行一步，这不仅是为了他们自己的团队，也是为了整个员工群体的利益，”Wettemann 表示。
报告的关键知识点：
Integration Challenges: HR faces challenges in managing AI use due to lack of policies, practices, and training.
Early Adoption vs. Preparedness: While HR has been an early adopter of AI, most organizations still lack the proper frameworks for safe and effective AI adoption.
Rapid Product Release: Post-Chat GPT announcement, HR software vendors have rapidly released generative AI products with varying capabilities.
AI’s Double-Edged Sword: AI offers great benefits but also poses risks of "accidents" due to immature technology, inadequate policies, and lack of training.
AI Experimentation and Automation Opportunity: Over three-quarters of HR workers have experimented with generative AI. 35% of HR tasks could potentially be automated by AI.
Current AI Utilization: The main opportunities for HR benefits from AI are in recruiting, learning and development, and talent management, with recruiting leading in AI adoption.
Adoption Barriers: Main hurdles include lack of AI expertise (28%), fear of compliance and risk (23%), and lack of resources (21%).
Policy and Training Deficiencies: Only 16% of organizations have policies on generative AI use, and less than 16% have training policies for AI usage.
Risk Areas in AI: Data compromises, AI hallucinations, bias and toxicity, and recommendation bias are identified as primary risks.
Future Plans for AI: Over 50% of organizations plan to apply AI in recruiting, talent management, and training within the next 24 months.
Least Likely AI Adoption: Benefits management has the lowest likelihood of current or future AI adoption due to data sensitivity concerns.
AI Skills and Expertise: The significant gap in AI skills and expertise impacts the adoption and effective use of AI in HR.
HR’s Role in AI Adoption: HR needs to develop policies, provide training, and ensure ethical AI use aligning with organizational principles.
Recommendations for HR: Suggestions include experimenting with generative AI, developing ethical AI usage policies, creating role-specific AI training, and identifying employee groups at risk from AI automation.
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2024年03月12日
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根据美世 2024 年全球人才趋势研究，高管认为人工智能是提高生产力的关键，但大多数员工尚未做好转型的准备Mercer's 2024 Global Talent Trends Study unveils critical insights from over 12,000 global leaders and employees, highlighting the increasing importance of AI in productivity, discrepancies between executive and HR perceptions, the necessity of human-centric work design, and the growing challenges in trust, diversity, and resilience within the workforce. The study emphasizes the urgency of adapting talent strategies to foster greater agility and employee well-being amidst technological advances and shifting workforce dynamics.
美世今天发布了2024年全球人才趋势研究。该研究借鉴了全球 12,000 多名高管、人力资源主管、员工和投资者的见解，揭示了雇主为在这个新时代蓬勃发展而采取的行动。
“今年的调查结果突显了工作中的惊人转变，”美世总裁帕特·汤姆林森 (Pat Tomlinson) 表示。“他们指出，高管层和人力资源部门对于 2024 年业务发展的看法存在显着分歧，而且员工对于技术影响的看法也存在滞后。随着我们迎来人机团队的时代，组织需要将人置于转型的核心。”
生成式人工智能 (AI) 被视为提高生产力的关键
生成式人工智能能力的快速增长引发了人们对劳动力生产力提升的希望，40% 的高管预测人工智能将带来超过 30% 的收益。然而，五分之三 (58%) 的人认为科技进步的速度超过了公司对员工进行再培训的速度，不到一半 (47%) 的人认为他们可以通过当前的人才模式满足今年的需求。
“通过人工智能提高生产力是高管们最关心的问题，但答案不仅仅在于技术。提高员工生产力需要有意识的、以人为本的工作设计。”美世全球人才咨询主管兼该研究的作者 Kate Bravery 说道。“领先的公司认识到人工智能只是其中的一部分。他们正在从整体的角度来解决生产力下降的问题，并通过新的人机协作模式提供更大的敏捷性。”
寻找通向未来工作的可持续道路面临着挑战。四分之三 (74%) 的高管担心他们的人才的转变能力，不到三分之一 (28%) 的人力资源领导者非常有信心他们能够使人机团队取得成功。提高敏捷性的关键是采用技能驱动的人才模型，这是高增长公司已经掌握的。
员工信任度全面下降
2023 年，对雇主的信任度从 2022 年的历史最高水平下降，这是一个危险信号，因为研究表明信任对员工的精力、蓬勃发展感和留下来的意愿产生重大影响。那些相信雇主会为他们和社会做正确事情的人，表示自己正在蓬勃发展、具有强烈的使命感、归属感和被重视感的可能性是其他人的两倍。
近一半的员工表示，他们希望为一个令他们感到自豪的组织工作，一些公司的回应是优先考虑可持续发展工作和“良好工作”原则。鉴于公平薪酬（34%）和发展机会（28%）是员工今年留下来的主要驱动力，雇主有动力在未来一年在薪酬公平、透明度和公平获得职业机会方面取得更快进展。
在全球范围内，员工都清楚，归属感有助于他们成长，但只有 39% 的人力资源领导者表示，女性和少数族裔在其组织的领导团队中拥有良好的代表，只有 18% 的人表示，最近的多元化、公平性和包容性努力提高了员工保留率关键多元化群体。四分之三的员工 (76%) 目睹过年龄歧视。由于这些挑战加上持续的技能短缺，更多地关注包容性和满足员工的需求将有助于所有员工蓬勃发展。
未来几年，韧性将至关重要
最近在风险缓解方面的投资已获得回报，64% 的高管表示他们的业务能够承受不可预见的挑战，而两年前这一比例为 40%。通货膨胀等近期担忧严重影响高管的三年计划，但网络和气候等长期风险可能没有得到应有的必要关注。
建立个人韧性与企业韧性同样重要，五分之四 (82%) 的员工担心自己今年会精疲力竭。为员工福祉重新设计工作对于缓解这一风险至关重要，51% 的高增长公司（2023 年收入增长 10% 或以上）已经这样做了，而低增长同行中只有 39% 这样做了。
员工体验是重中之重
超过一半的高管 (58%) 担心他们的公司在激励员工采用新技术方面做得不够，三分之二 (67%) 的人力资源领导者也担心他们在没有改变工作方式的情况下实施了新技术解决方案。员工体验是今年HR的首要任务；这是一个值得关注的问题，因为蓬勃发展的员工表示雇主设计的工作体验能够发挥他们的最佳水平的可能性是普通员工的 2.6 倍。
人力资源部门在改善所有人的工作方面发挥着关键作用，但人力资源部门越来越有必要与风险和数字化领导者合作，以按要求的速度引入必要的变革。为了满足组织和员工的期望，96% 的公司计划今年对人力资源职能进行一些重新设计，重点是跨部门交付和领先的数字化工作方式。
投资者重视敬业的员工队伍
今年，美世首次收集资产管理公司关于组织的人才战略如何影响其投资决策的意见。近十分之九 (89%) 的人将员工敬业度视为公司绩效的关键驱动力，84% 的人认为“流失和燃烧”方法会损害商业价值。投资者还表示，营造信任和公平的氛围是未来五年建立真正、可持续价值的最重要因素。
单击此处了解更多信息并下载今年的研究。
关于美世 2024 年全球人才趋势研究
美世全球人才趋势目前已进入第九个年头，汇集了来自 17 个地区和 16 个行业的 12,200 多名高管、人力资源领导者、员工和投资者的见解，该研究重点介绍了当今领先组织为确保人员长期可持续发展所采取的措施。在此过程中走得更远的组织在四个领域取得了长足的进步。(1) 他们认识到，以人为本的生产力需要关注工作的演变以及工作人员的技能和动机。(2) 他们认识到信任是真正的工作对话，通过透明度和公平的工作实践得到加强。(3) 随着风险变得更加关联且难以预测，他们认识到，提高风险意识和缓解水平对于建立一支准备就绪、有复原力的员工队伍至关重要。(4) 他们承认，随着工作变得越来越复杂，简化、吸引和激励员工走向数字化的未来至关重要。
关于美世
美世坚信，可以通过重新定义工作世界、重塑退休和投资成果以及释放真正的健康和福祉来建设更光明的未来。美世在 43 个国家/地区拥有约 25,000 名员工，公司业务遍及 130 多个国家/地区。美世是Marsh McLennan （纽约证券交易所股票代码：MMC）旗下的企业，Marsh McLennan 是风险、战略和人才领域全球领先的专业服务公司，拥有超过 85,000 名同事，年收入达 230 亿美元。通过其市场领先的业务（包括达信、Guy Carpenter和奥纬咨询），达信帮助客户应对日益动态和复杂的环境。
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2024年03月07日
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FlexJobs 分享 20 个远程求职骗局以及 2024 年安全求职的关键提示
强烈推荐了解一下，HR要避免出现类似骗局的招聘信息。随着远程和混合工作需求的增加，FlexJobs分享了2024年20种常见的远程工作诈骗，并提供了安全求职的建议。文章强调了在当前就业市场中，骗子利用AI和社交媒体等新工具和方法盗取个人和财务信息的现象。为了保护求职者，FlexJobs展示了诈骗职位描述的语言和呈现方式，强调了识别职位描述、面试过程和社交媒体上的诈骗警告标志的重要性。文章结束时，给出了如何保持安全的建议，包括研究公司和联系人、直接联系公司以及立即报告欺诈活动。
Remote work, AI developments add to expanding employment scams in today's job marketplace
BOULDER, Colo., March 5, 2024 Work-from-home jobs have long been a target for scammers seeking access to personal and financial information, and with the demand for remote and hybrid work, the number of online job scams has steadily increased. According to the Better Business Bureau (BBB), employment scams ranked as the second riskiest in recent years, with a 23% increase in reported cases. In honor of National Consumer Protection Week on March 3-9, and to help professionals stay safe in their job search, FlexJobs® has shared 20 remote job scams and advice on how to job search safely in 2024.
"With scammers using new tools and methods of phishing for personal and financial information, it's more important than ever before that job seekers stay vigilant to the latest online career scams," said Keith Spencer, Career Expert at FlexJobs. "When in doubt, walk away––if you feel like a job may be a scam, it's not worth finding out the hard way," Spencer added.
20 Common Remote Job Scams in 2024
1. AI-Generated Job Postings and Fake Company Websites2. Cryptocurrency Exchanges and Ponzi Schemes3. Posing as a Legitimate Company or Job Board4. Using Fake URLs, Photos, and Company Names5. Gaining Access to Personal Financial Information6. Recruitment Over Social Media7. Posing as Recruiters with ATS-Compliant "Services"8. Communicating Through Chat9. Phishing Attacks Over Text Message10. Google Docs Inviting or Mentioning11. Paying for Remote Work Equipment12. Data Entry13. Pyramid Marketing14. Stuffing Envelopes from Home15. Wire Transfers16. Unsolicited Job Offers17. Online Reshipping18. Rebate Processor19. Assembling Crafts/Products20. Career Advancement Grants
Notably, social media and technology advancements like AI have created new avenues for fraud. For example, one of the latest scams uses AI to create fake job postings and company profiles or websites that collect money directly from applicants and steal sensitive personal information. Scammers can also take to social media platforms to target potential victims and steal information with attractive job offers or involve them in multi-level marketing schemes.
In addition to sharing the 20 newest and most common remote job scams, FlexJobs' remote work experts have provided examples of job postings that demonstrate the language and presentations of scams. They stress the importance of knowing the latest warning signs of a scam in job descriptions, interviews, and across social media.
Job Scam Warning Signs: Job Descriptions
The job posting uses words that are probably too good to be true, such as "quick money," "unlimited earning potential," or "free work-from-home jobs"
The job claims to pay a lot of money for little work
The company boasts several rags-to-riches stories that showcase high-flying lifestyles
The job description is unusually vague
The job posting mentions quick money or drastic income changes overnight
The job posting has glaring grammatical or spelling errors
The product is supposedly endorsed by celebrities or public figures
The contact email address is personal (e.g., johnsmith3843@gmail.com) or one that mimics a real company's email address (e.g., johnsmith@dellcomputercompany.com)
The job requires several up-front expenses from candidates
Job Scam Warning Signs: Interviews
Candidates get a message from a generic company email address – Recruiters use the job board or social media platform to communicate with candidates instead of their personal email addresses.
The interview is alarmingly short – Job scammers don't want to conduct lengthy interviews and will offer candidates the job immediately. Legitimate recruiters want to establish a relationship, verify applicants' work experience, and ask for references.
The entire interview process is done without speaking to a live person – Not speaking to a live person or including text or online chat tools is a red flag. Most legitimate companies don't reach out to recruit via text unless a candidate already applied on the company's site and opted to receive text messages.
The candidate is asked for personal information or money – Sensitive information (like a social security number, date of birth, or bank account information) should never be a part of the early recruitment process. Legitimate employers and hiring managers don't require an application fee or expect candidates to pay for training.
The interview is with a "mystery company" – Legitimate employers will always disclose the name of the company to candidates.
Candidates are offered the job quickly – Often with a job scam, candidates are offered the role without a recruiter or HR verifying their work experience or asking for references.
Pay is based on recruiting – Particularly with pyramid and other scams, a worker's compensation is based on how many people they recruit.
Job Scam Warning Signs: Social Media
Unclear or unrelated comments from a stranger – No matter what kind of post or which platform it appears on, if comments are enabled, scammers may appear in a job seeker's comments section. They commonly post a random message unrelated to the subject, then try to get users to directly message them (often by clicking a link) about an "amazing opportunity."
Posts shared on an individual's feed or in their direct messages – Scammers will post or direct message people in hopes of getting them to take the bait on a job scam. When a scam appears on social media, report it. Never click any links or engage with these posts in any way.
While anyone can fall prey to job scams, there are a few other things workers can do to stay safe:
Research the company and contacts – What results do you get when searching [Company Name] + scam? Workers can also use the Better Business Bureau's scam tracker to review companies.
Connect directly with the company – Go directly to the company website and see if the job is posted on their jobs page.
Report fraudulent activities immediately – If a scam has been found, report the scam to organizations like the BBB and FTC.
Please visit https://www.flexjobs.com/blog/post/common-job-search-scams-how-to-protect-yourself-v2/ or contact Shanna Briggs at shanna.briggs@bold.com for more information.
About FlexJobsFlexJobs is the leading career service specializing in remote, hybrid, and flexible jobs, with over 135 million people having used its resources since 2007. FlexJobs provides the highest-quality database of vetted remote and flexible job listings, from entry-level to executive, startups to public companies, part-time to full-time. To support job seekers in all phases of their career journey, FlexJobs also offers extensive expert advice, webinars, and other resources. In parallel, FlexJobs works with leading companies to recruit quality remote talent and optimize their remote and flexible workplace. A trusted source for data, trends, and insight, FlexJobs has been cited extensively in top national outlets, including CNN, the Wall Street Journal, the New York Times, CNBC, Forbes magazine, and many more. FlexJobs also has partner sites Remote.co and Job-Hunt.org to help round out its content and job search offerings. Follow FlexJobs on LinkedIn, Facebook, Twitter, Instagram, TikTok, and YouTube.
Workday收购HiredScore的意义，这可能颠覆人力资源科技领域Workday计划收购HiredScore，这是人力资源技术领域的一次重大变革。HiredScore是一家领先的基于AI的招聘匹配工具提供商，此举将大大增强Workday在人才智能和招聘方面的能力。这次收购预计将整合HiredScore的专长到Workday的系统中，显著改善其应聘者追踪系统（ATS）、技能云和整体人才智能产品。此战略性收购可能会重塑人力资源软件市场，迫使其他供应商加速他们的AI计划，可能激发一轮新的收购热潮。
以下是原文：
This week Workday announced intent to acquire HiredScore, a leading provider of AI-based matching tools for recruiting (called “talent orchestration”). While it wasn’t discussed much in the earnings call, this deal is a big positive for Workday and could have many implications for the HR Tech market.
Let me explain. (I have not been briefed by Workday yet, so more information will come as I learn more.)
Right now there is a massive marketplace war for high-powered AI-based recruiting tools (estimated at $30.1 billion). Historically dominated by applicant tracking systems (ATS), this market provides essential technology to help every company grow.
The ATS market, which is more than 25 years old, has been rapidly transformed with high-powered AI tools that help with candidate matching, search, skills inference, and sourcing. And now that AI tools are readily available, these systems are becoming big data platforms loaded with billions of employee profiles, running complex AI models to help match people to jobs, projects, and gigs.
Most ATS vendors (including Workday) have slowly extended into this space through matching. The original idea of a resume parser (software that reads a resume and scores it against a job description) has evolved into complex text analysis and AI-powered inference technology, forcing ATS vendors to invest.
As the ATS vendors enhance their AI capabilities, a parallel universe of AI-first Talent Intelligence vendors emerged. These vendors, like Eightfold, Gloat, Beamery, Phenom, Seekout, Skyhive, Retrain, and Techwolf are building skills-centric big data platforms to match people to jobs, gigs, and mentors. These systems do much more than rate matches: they identify skills, find adjacent skills, match people to careers, find mentors, and more. They are essentially open big-data AI platforms built on vector databases that can be used for many enterprise apps (job architecture design, skills planning, internal mobility, pay equity analysis, etc.). In many ways they represent the future of HR Tech.
(Read our Talent Intelligence Primer for more.)
As the Talent Intelligence vendors grow, they start to deliver “HCM-threatening” platforms that impinge on the HCM “System of Record” idea. If you have all your employees, candidates, alumni, and prospects in Eightfold, Phenom, Seekout, or Gloat, for example, Workday or SAP look like a tactical payroll and workflow management system. (ServiceNow also understands this, and is building talent intelligence into its workflow platform.)
Up until now the big HCM vendors like Workday, Oracle, and SAP have struggled to build these new systems, largely because their original architectures were not AI-based. So they’ve attracted customers with offerings like the Workday Skills Cloud or SAP Opportunity Marketplace that aren’t fully completed yet. We have talked with dozens of Workday Skills Cloud customers, for example, and they see it as an important “skills system of record,” but its real AI matching and inference capabilities have been limited.
Along comes HiredScore, a well respected AI-based matching system with 150 employees and 40+ seasoned AI engineers in Israel. These folks are experts at candidate matching (quite a complex problem), and they’ve built a very innovative “orchestration” system to help line managers coordinate activities with HR business partners and recruiters (more on this later). While I’m sure they’ll continue to build out HiredScore, they can also contribute to Workday’s overall talent intelligence offering, improving the entire system – including the Skills Cloud, Workday Learning, Workday’s Talent Marketplace.
As large as the recruiting software market is, the market for internal career tools, talent mobility, skills inference, and corporate learning is five times bigger. This acquisition gives Workday a shot in the arm to accelerate its entire AI platform strategy. (As the Identified acquisition did back in 2014. Identified was the roots of the Workday Skills Cloud.)
Market Implications Of This Move
This move could change the market for HR software in a few significant ways.
First, Workday Recruiting customers will be thrilled. Workday’s ATS now benefits from a first class matching and candidate scoring solution. This helps Workday compete with the bigger ATS players and gives Workday a new revenue source as they sell HiredScore to the existing 4,000+ Workday ATS customers. (Similar to the Peakon acquisition in Employee Experience.) And the talent orchestration features (kind of like a “staffing copilot”) gives Workday a very unique feature set.
Second, this forces Workday’s talent intelligence partners to step up their game. Remember when Apple acquired Dark Sky, the most compelling micro-weather app on the market? Once they integrated it into Apple’s other apps, the market for third party weather apps went away. Workday could limit its partner network to avoid letting HiredScore competitors into the ecosystem.
Third, this forces HCM vendors to accelerate their AI. Since HiredScore is such a well-respected product (every client we talk with adores it), it will become part of Workday demos and sales proposals quickly. Workday’s HCM competitors will start scratching around to find a similarly mature AI vendor to acquire. And that could kick off another round of acquisitions, similar to the frenzy that took place in the mid 2010s.
Finally, there’s one more scenario, and I give this good odds. Not to be outdone by Workday, the Talent Intelligence vendors may just expand their ATS capability and decide to go “full stack.” I wouldn’t be surprised to see this happen.
Why Is AI-Based Candidate Matching So Important
Why is this technology so important? Well if you’ve ever tried to recruit on Indeed or LinkedIn, you know why. The quality and reliability of “candidate matching technology” is a lynchpin of a talent platform. Just as Google Search crushed Yahoo, Excite, and Inktomi, a powerful next-gen matching tool adds an enormous amount of value. Not only does it speed talent acquisition, it fuels all the internal mobility, career portals, skills, and eventually learning and pay systems.
Why do I say this? A “match” is a sophisticated problem. Unlike a Google search which looks at text and traffic, when you search for a person to fill a role you have to think about dozens of complex relationships. What are this person’s skills and capabilities? What are their credentials or certifications? Who else are they connected with? How likely will they fit into the job, role, and company? What is the impact of their industry experience? What tools and technologies do they understand?
And it gets much more complex. The Heidrick Navigator platform (built on Eightfold), uses AI to assess functional skills for management and leadership, identifies a person’s “ability to drive results,” and more. This important application of AI powers many of the most important decisions we make in business.
That’s why the Talent Intelligence space is growing so fast. As of this week there are more than 1,800 Director or VPs of “Talent Intelligence” in LinkedIn, and that number is up almost six-fold from one year ago.
Can Workday take the lead in this emerging space? It’s impossible to tell at this point, but the horses have left the gate and the race is on. This deal sets the players in the right lanes and feels like the earthquake to shake things up.
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2024年03月01日
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滴滴出行选用NICE，以提供基于实时 AI 的个性化服务NICE has partnered with DiDi Global to enhance customer and employee experiences through its cloud-based Workforce Management (WFM) and Employee Engagement Manager (EEM) solutions. This collaboration aims to streamline DiDi's global contact center operations, improving operational efficiency and customer satisfaction with AI-driven forecasting and scheduling. The implementation of NICE's solutions facilitates real-time management and self-scheduling for agents, boosting employee engagement and operational efficiency. DiDi's choice of NICE highlights the importance of advanced, flexible technology in supporting the dynamic needs of modern, app-based transportation services.
领先的移动出行平台通过利用 NICE 的客户体验 AI 技术，使其员工能够提供轻松且高效的客户服务体验
新泽西州霍博肯-NICE (纳斯达克: NICE) 今日宣布，滴滴出行已经选用了 NICE 劳动力管理 (WFM) 和员工参与管理 (EEM) 作为其云端创新技术的一部分。滴滴现在可以全面预测、规划和管理其全球客户联系中心的运作；同时提升运营效率和员工的参与度，并确保客服代表能够在首次通话中解决问题。Betta作为全球最大的 WFM 客户群之一的支持者，在实施过程中与 NICE 价值实现服务携手合作，负责执行集成，并在多国提供咨询、培训和支持服务。
滴滴出行寻求一种能够满足其核心业务、功能及技术需求，并能够随公司成长而扩展的劳动力管理解决方案。NICE WFM 结合了 AI 技术与灵活性，能够满足跨多个大洲、具有特定区域特色的运营需求，这不仅成本效益高，而且精确度高，确保维持最佳的服务水平。通过精准预测，确保在合适的时间有合适技能的代理人，从而大幅提升客户满意度。
通过引入 NICE EEM，可以实时解决人员配置需求，使得客服代理能够自我调节工作时间表，从而增强员工参与度和工作满意度。此外，利用智能日内自动调整功能，能够主动地进行调整，预防问题的发生。
滴滴出行国际客户体验执行总监 Caio Poli 表示：“基于多个考量因素，NICE 显然是我们的首选。我们寻找的是一个顶尖的云端劳动力管理解决方案，能够使我们的全球运营在保证运营效率和员工参与度的同时，提供卓越的客户体验。NICE 的智能日内自动化功能给我们留下了深刻印象，我们的选择是基于 AI 驱动的策略以及云技术的速度和灵活性。”
NICE 美洲总裁 Yaron Hertz 表示：“随着滴滴持续全球扩张，NICE 很高兴有机会为这家数字时代最具创新和活力的应用型运输公司之一提供服务。我们相信，通过采用 NICE 的 AI 驱动预测和机器学习来进行最适合的调度安排，对于联系中心和员工而言，这将有助于推动滴滴的未来发展。”
关于滴滴出行公司
滴滴出行公司是一个领先的移动技术平台，它在亚太地区、拉丁美洲及其他全球市场提供一系列基于应用的服务，包括网约车、叫车服务、代驾以及其他共享出行方式，还涵盖某些能源和车辆服务、食品配送和城市内部货运服务。滴滴为车主、司机和配送伙伴提供灵活的工作和收入机会，致力于与政策制定者、出租车行业、汽车行业及社区合作，利用 AI 技术和本地化智能交通创新解决全球的交通、环境和就业挑战。滴滴力图为未来城市构建一个安全、包容和可持续的交通与本地服务生态系统，以创造更好的生活体验和更大的社会价值。更多信息，请访问：www.didiglobal.com
关于 NICE
借助 NICE (纳斯达克: NICE)，全球各地不同规模的组织现在可以更容易地创造卓越的客户体验，同时满足关键的业务指标。作为世界领先的云原生客户体验平台 CXone 的提供者，NICE 是 AI 驱动自助服务和代理辅助客户体验软件领域的全球领导者，服务范围超出了传统的联系中心。超过 25,000 个组织在超过 150 个国家，包括 85 家以上的财富 100 强公司，都选择与 NICE 合作，以改造并提升每一次客户互动。www.nice.com
商标说明：NICE 和 NICE 标志是 NICE Ltd. 的商标或注册商标。所有其他标志属于它们各自的所有者。NICE 商标的完整列表，请访问：www.nice.com/nice-trademarks。
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2024年02月27日
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Is DEI Going to Die in 2024?Josh Bersin 的文章讨论了 2024 年多元化、公平与包容（DEI）项目所面临的重大挑战和批评，特别强调了 "反觉醒 "评论家的攻击和克劳迪娜-盖伊（Claudine Gay）从哈佛辞职的事件。报告探讨了多元包容计划在当前的文化战争中扮演的角色、人们对它的看法以及法律挑战对多元包容计划招聘和投资的影响。尽管存在这些挑战，贝尔辛还是强调了发展型企业的实际商业利益，展示了成功的战略以及将发展型企业融入业务而不仅仅是人力资源的重要性。他认为，应将重点转向在所有业务部门嵌入包容、公平薪酬和开放讨论的原则，并指出，未来的企业发展指数至关重要，但需要适应和领导层的承诺才能茁壮成长。
Is DEI Going to Die in 2024? By Josh Bersin
For anyone working in Diversity, Equity, and Inclusion (DEI), it is safe to say that it has been a tough start to 2024. For a while now, there has been a concerted attack on DEI programs, with ‘anti-woke’ commentators and public figures querying their value, worth, and even existence.
Those attacks increased enormously in 2024 with the resignation of Claudine Gay from Harvard. While the call to resign was supposedly related to plagiarism, one can’t help but feel that her position as a leading DEI advocate also fuelled the demand.
It means that DEI has come under increased and sustained fire, and despite the many benefits provided by a good DEO program – to both employer and employee – there is a feeling that 2024 could be the year that DEI fades away. How likely is this to happen, and what would the impact be if it did?
DEI and the culture wars
Anyone living and working in the US (or most other countries worldwide) over the past few years will have likely heard of the culture wars. Brought on by declining trust in institutions, growing inequalities, and the proliferation of technology, the culture wars involve opposing social groups seeking to impose their ideologies.
All manner of things has been caught up in this, from what’s on the curriculum at schools to taking a knee at sporting events and from definitions of what constitutes a woman to allegations of tokenism in the workplace. DEI has played an unwitting but central part in the culture wars.
There’s a perception that DEI programs are ‘woke’ and prioritize ethnicity and gender over achievement and ability. In August of 2023, an attorney filed (and won) a lawsuit against a VC firm that gives grants to black entrepreneurs. Similar suits have been filed against firms with diversity hiring programs, scholarships, and internships.
The resignation of Claudine Gay has reinvigorated the commentary around DEI programs. Josh Hammer, a conservative talk show host and writer, wrote on the social media platform X that taking down Dr. Gay was a “huge scalp” in the “fight for civilizational sanity. ” It was described as “a crushing loss to DEI, wokeism, antisemitism & university elitism,” by conservative commentator Liz Wheeler, and the “beginning of the end for DEI in America’s institutions,” by the conservative activist Christopher Rufo, who had helped publicize the plagiarism allegations against Claudine Gay.
When something is as consistently criticized and devalued as DEI programs have been, a toll is inevitably taken. That is certainly indicated by the latest hiring data for DEI professionals. According to data from labor market analytics company Lightcast, hiring for DEI positions in the US is down by 48% year over year, in the middle of an economic boom. Clearly, DEI investments are under attack.
And when you look at companies doing layoffs, DEI jobs are frequently high on the list of jobs to cut. I even heard a recent podcast with four well-known venture capitalists – three agreed that “doing away with DEI programs” was top on their list.
The value of DEI
Given this criticism of DEI programs, one could be forgiven for thinking such programs carry no value to HR and the wider business. Yet many companies invest in DEI programs, and the value is high in almost every case I come across.
Our Elevating Equity research in 2022 and 2023 found companies focus on diversity and inclusion for very pragmatic reasons, including:
An inclusive hiring strategy broadens and deepens the recruiting pool.
An inclusive leadership strategy drives a deeper leadership pipeline.
An inclusive management approach helps attract diverse customers and markets.
An inclusive board drives growth and market leadership. (proven statistically)
An inclusive supply chain program improves sustainability of the supply chain.
An inclusive culture creates growth, retention, and engagement in the employee base.
Organizations are not prioritizing DEI programs because they are woken or as a box-ticking exercise. They do so because DEI provides real and tangible business benefits. Workday, one of the most admired HR technology companies in the market, has pioneered DEI internally and through its products, and the company has outgrown and outperformed its competitors for years. Their product VIBE, an analytics system designed for this purpose, shows intersectionality, and helps companies set targets and find inequities in leadership, hiring, pay, and career development.
But some law firms have posited that these types of programs are illegal – is there a case to answer?
DEI legality
In response, it’s important to consider the massive and complex pay equity problem. Until the last few years, most companies had no problem paying people in very idiosyncratic ways. The Josh Bersin Company looked at leadership, succession, and pay programs worldwide last year and found that there are massive variations in pay with no clear statistical correlation in most larger companies.
This problem is called “pay equity,” and when you look at pay vs. gender, age, race, nationality, and other non-performance factors, most companies find problems. Is this a “DEI” program?
When we looked at pay equity in detail last year, we found that only 5% of companies have embarked on a strategic equity analysis. While most companies do their best to keep pay consistent with performance, these studies always find problems. Would it be considered illegal to analyze pay by race or nationality and then fix the disparities?
The future of DEI
DEI is undoubtedly a complex issue, and many organizations will be uncertain about the best course of action. Despite the current wave of criticism, there has been vast investment in DEI strategy over recent years, and business leaders are highly unlikely to let that fade away.
Despite the anti-woke movement, political debates, and the inability of Harvard, Penn, and other universities to speak clearly on these topics, businesses will not stop. Affirmative Action was not created to discriminate; it was designed to reduce discrimination. At the University of California, where Affirmative Action was halted in 1995, studies found that earnings among African American STEM graduates decreased significantly. So, one could argue that they were making a real difference.
DEI will not die – it is far too important for that to happen. However, it’s time to do away with the “DEI police” in HR and focus on embedding the principles of inclusion, fair pay, and open-minded discussions across all business units. Senior leaders must take ownership of this issue.
In the early 2000s, companies hired Chief Digital Officers to drive digital technology implementation, ideas, and strategies. As digital tools became commonplace, the role went away. We may be entering a period where the Chief Diversity Officer has a new role: putting the company on a track to embrace inclusion and diversity in every business area and spending less time pushing the agenda from a central group.
In every interview we conduct on this topic, we see overwhelming positive stories from various DEI strategies. Each successful company frames DEI as a business rather than an HR strategy. While HR-centric DEI investments are shrinking, it’s more like them migrating into the business where they belong.
中文翻译如下，仅供参考：
2024年，多样性、公平与包容（DEI）将走向消亡吗？作者：Josh Bersin
对于那些致力于多样性、公平与包容（DEI）领域的人士来说，2024年的开端无疑充满挑战。近期，DEI项目遭到了前所未有的集中攻击，包括一些“反觉醒”评论员和公众人物对其价值、意义乃至存在的质疑。
特别是随着Claudine Gay从哈佛大学的辞职，这种攻击愈发激烈。尽管她的辞职表面上与剽窃事件有关，但不难察觉，她作为DEI领域的领军人物，这一身份似乎也是辞职呼声高涨的一个重要因素。
这意味着，DEI正面临着前所未有的挑战。尽管高效的DEI项目能够为雇主和雇员带来众多益处，但人们仍担忧2024年可能成为DEI逐渐淡出视野的一年。这种情况发生的可能性有多大？如果真的发生，又会产生何种影响？
DEI与文化战争
近年来，无论是在美国还是全球其他大多数国家，你可能都会听说过“文化战争”。这场战争源于对机构的信任下降、不平等现象的加剧以及技术的广泛传播，涉及到试图强加自己意识形态的社会对立群体。
从学校课程内容、体育赛事中的下跪行为，到对“女性”定义的争议、以及工作场所中的代表性指控等，无一不被卷入这场文化战争。而DEI，在这场战争中虽不愿意却占据了核心位置。
人们普遍认为DEI项目倾向于“觉醒”，过分强调种族和性别因素，而忽视了成就和能力。2023年8月，一位律师成功对一家支持黑人创业者的风险投资公司提起诉讼。类似的诉讼也针对那些实施多样性招聘、奖学金和实习计划的公司提起。
Claudine Gay的辞职再次引发了对DEI项目的广泛讨论。保守派脱口秀主持人和作家Josh Hammer在社交媒体平台X上表示，击败Gay博士是“为文明理智而战的一大胜利”。保守派评论员Liz Wheeler称之为“对DEI、觉醒主义、反犹太主义及大学精英主义的沉重打击”，而保守派活动家Christopher Rufo则称这是“DEI在美国机构中走向终结的开始”。
如此一致的批评和贬低无疑对DEI项目造成了重创。根据劳动力市场分析公司Lightcast的数据显示，尽管经济蓬勃发展，但美国DEI相关职位的招聘量同比下降了48%。显然，DEI正面临严峻挑战。
当提到公司裁员时，DEI相关职位往往是裁减名单上的重点。我最近听到一个播客，四位知名风险投资家中有三位认为“取消DEI项目”是他们的首要任务。
DEI的价值
面对如此批评，人们或许会误以为DEI项目对人力资源和更广泛的商业活动没有任何价值。然而，实际上，许多公司对DEI项目的投资极具价值，几乎每个案例都能证明这一点。
我们在2022年和2023年的《提升公平研究》中发现，公司出于实际原因关注多样性和包容性，这包括：
包容性招聘策略扩大了招聘范围。
包容性领导力策略深化了领导力储备。
包容性管理方式吸引了多元化的客户和市场。
包容性董事会推动了市场增长和领导地位（这一点已通过统计数据得到证明）。
包容性供应链项目提升了供应链的可持续性。
包容性文化促进了员工的增长、留存和参与。
组织之所以优先考虑DEI项目，并非仅仅因为“觉醒”，或者作为勾选式行动。他们这样做是因为DEI确实带来了实际和有形的商业利益。例如，Workday这样的HR技术公司在市场上备受尊敬，它不仅在内部推广DEI，在其产品中也体现了这一点，多年来一直超越竞争对手的增长和表现。它们的产品VIBE，一个专门设计的分析系统，展示了交叉性，帮助公司设定目标，找出领导力、招聘、薪酬和职业发展中的不平等。
然而，一些律所提出这类计划可能违法——这是否成立呢？
DEI的合法性
面对这一问题，我们不得不考虑到复杂且广泛的薪酬公平问题。直到最近几年，大多数公司在个性化支付薪酬方面并未遇到太大问题。Josh Bersin Company去年对全球的领导力、继承计划和薪酬计划进行了研究，发现在许多大公司中，薪酬存在巨大差异，且大多没有明显的统计相关性。
这个问题被称作“薪酬公平”。当涉及到性别、年龄、种族、国籍等非绩效因素时，大多数公司都存在问题。那么，分析基于种族或国籍的薪酬差异并加以解决，这会被认为是非法的吗？
DEI的未来
DEI无疑是一个复杂的议题，许多组织对于采取何种措施感到不确定。尽管面临当前的批评浪潮，但近年来对DEI策略的巨大投资表明，商业领袖们不太可能让这一切付诸东流。
尽管存在反觉醒运动、政治辩论，以及哈佛、宾夕法尼亚大学等教育机构在这些议题上的模糊立场，但商界不会因此而停滞不前。平权行动的初衷不是为了歧视，而是为了减少歧视。例如，在加州大学，自从1995年停止实施平权行动以来，研究发现非洲裔美国人STEM专业毕业生的收入显著下降。因此，可以说这些措施确实产生了积极的影响。
DEI不会消亡——它对此太重要了。然而，现在是时候取消人力资源部门中的“DEI警察”，转而专注于在所有业务单元中嵌入包容性、公平薪酬和开放性讨论的原则。高级领导层必须对这一议题负起责任来。
回顾21世纪初，许多公司聘请首席数字官来推动数字技术的实施、创意和战略。随着数字工具成为常态，这一角色逐渐消失。我们可能正处于一个新的时期，首席多样性官的角色也在发生变化：不再是从中心团队推动议程，而是引导公司在每一个业务领域都拥抱包容性和多样性。
通过我们在这个话题上的每次采访，我们都能看到各种DEI策略的积极故事。每个成功的公司都将DEI视为一项业务策略，而非仅仅是人力资源策略。虽然以HR为中心的DEI投资正在减少，但这更像是它们向业务领域的转移，这正是它们应有的归属。
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2024年02月23日
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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.
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