人工智能如何改变人才获取 How Artificial Intelligence Is Changing Talent Acquisition现在大家都在关注招聘AI，并就如何改变招聘方式进行了大量的讨论。招募人工智能是下一代软件，旨在改进或自动化招聘工作流程的某些部分。
作者：Ji-A Min
人工智能对招聘的兴趣已经由三大趋势引发
经济的改善：最近的经济收益创造了一个候选人驱动型市场，这使得人才竞争比以往更加激烈。这一竞争只会继续增加 - LinkedIn调查的 56％的人才招聘领导者认为他们的招聘数量将在2017年增长。
对更好技术的需求：虽然人才招聘预计会增加，但是66％的人才招聘负责人表示他们的招聘团队将保持相同规模甚至缩小规模。这意味着时间有限的招聘人员需要更好的工具来有效地简化或自动化他们的工作流程的一部分，理想情况下用于最耗时的任务。
数据分析的进步：随着技术变得快速和成本效益足以收集和分析大量数据，人才招聘领导者越来越多地要求他们的招聘团队展示基于数据的雇佣质量指标，如新员工的表现和营业额。
人工智能在招聘中越来越受欢迎，这为招聘人员提高他们的能力提供了令人兴奋的机会，但同时也存在很多关于如何最佳利用人才的困惑。
为了帮助您理解这一切，以下是招聘人工智能最有前途的三个应用程序。
应用＃1：AI用于候选人采购
候选人采购仍然是一个主要的招聘挑战：最近的一项调查发现，46％的人才招聘领导表示他们的招聘团队正在为吸引合格的候选人而奋斗。
候选人采购人工智能技术可以搜索人们离线的数据（例如简历，专业投资组合或社交媒体档案），以找到符合您工作要求的被动候选人。
这种用于招聘的AI可以简化采购流程，因为它可以同时搜索多个候选人来源。这取代了自己手动搜索它们的需求，并可能节省每个请求的小时数。您节省采购的时间可以用来吸引，预选和面试最强大的候选人。
应用#2：人工智能进行候选人筛选
当您收到的75-88％的简历不合格时，很容易明白为什么简历筛选是招聘中最令人沮丧和耗时的部分。对于零售和客户服务等大批量招聘，大多数招聘团队没有时间手动筛选他们每个公开角色收到的数百到数千份简历。
AI筛选旨在自动执行简历筛选流程。这种智能筛选软件通过使用岗位聘用数据（例如业绩和营业额）为新申请人提供招聘建议，为ATS增添了功能。
它通过应用所学到的关于现有员工的经验，技能和其他资质的信息来自动筛选和评分新候选人，从而提出这些建议。这种类型的技术还可以通过使用关于以前的雇主和候选人的社交媒体档案的公共数据源来丰富简历。
AI进行简历筛选可实现低价值，重复性任务，并允许招聘人员将时间重点放在更高价值的优先事项上，如与候选人交谈并与其进行交流以评估他们的适合度。
应用＃3：AI用于候选人匹配
与采购相比，候选人匹配可能是一个更大的挑战：52％的招聘人员表示，他们工作中最难的部分是从大型申请人池中确定合适的人选。
用于候选人匹配的AI使用一种算法来识别打开的请求的最强匹配。匹配算法分析候选人的个性特征，技能和工资偏好等多种数据来源，根据工作要求自动评估候选人。
例如，LinkedIn求职公告通过将求职者描述中的技能与其LinkedIn个人资料中的申请人技能进行匹配来对候选人进行排名。人才市场使用匹配算法来匹配候选人社区以开放角色。这些人才市场通常迎合特定的候选技能，如软件开发或销售。
人工智能匹配用于从那些已经加入并且正在积极寻找新角色或者对新机会非常开放的人中找出最合格的候选人。这意味着招聘人员不需要浪费时间来吸引那些对新角色不感兴趣的被动应聘者。
关于人工智能的力量，让候选人与工作岗位相匹配的不同观点，请参阅“ 尽管您阅读或听取的内容，采购活动和确实如此”。
AI和招聘的未来
专家预测人工智能招聘会转变招聘人员的角色。由于低价值，耗时的招聘任务通过人工智能技术变得简化和自动化，招聘人员的角色有可能变得更具战略性。
了解AI如何提高其能力的招聘人员将通过在采购，简历筛选和候选人匹配方面节省几十个小时，从而提高效率。
人工智能招聘承诺释放招聘人员与候选人交流的时间，以确定合适人选，并确定候选人的需求并希望说服他们担任角色。它有可能授权他们与招聘经理和人才招聘领导者合作，根据未来增长和收入计划积极的招聘举措，而不是反应性回填。
了解如何最好地利用这项新技术的招聘人员将获得更高的KPI，如更高的招聘质量和更低的营业额。
以上由AI翻译完成。供参考
How Artificial Intelligence Is Changing Talent Acquisition
AI for recruiting is on everyone’s mind these days with a lot of talk on how it’s going to transform recruiting. Artificial intelligence for recruiting is the next generation of software designed to improve or automate some part of the recruiting workflow.
Interest in AI for recruiting has been sparked by three major trends:
The improving economy: The recent economic gains have created a candidate-driven market that’s made competing for talent tougher than ever. This competition will only continue to increase – 56% talent acquisition leaders surveyed by LinkedIn believe their hiring volume will grow in 2017.
The need for better technology: Although hiring is predicted to increase, 66% of talent acquisition leaders state their recruiting teams will stay the same size or even shrink. This means time-constrained recruiters need better tools to effectively streamline or automate a part of their workflow, ideally for tasks that are the most time-consuming.
The advancements in data analytics: As technology becomes fast and cost-effective enough to collect and analyze vast quantities of data, talent acquisition leaders are increasingly asking their recruiting teams to demonstrate data-based quality of hire metrics such as new hires’ performance and turnover.
The growing popularity of AI for recruiting represents exciting opportunities for recruiters to enhance their capabilities but there’s also a lot of confusion about how to best leverage it.
To help you make sense of it all, here are the three most promising applications for AI for recruiting.
Application #1: AI for candidate sourcing
Candidate sourcing is still a major recruiting challenge: a recent survey found 46% of talent acquisition leaders say their recruiting teams struggle with attracting qualified candidates.
AI for candidate sourcing is technology that searches for data people leave online (e.g., resumes, professional portfolios, or social media profiles) to find passive candidates that match your job requirements.
This type of AI for recruiting streamlines the sourcing process because it can simultaneously search through multiple sources of candidates for you. This replaces the need to manually search them yourself and potentially saves you hours per req. The time you save sourcing can be spent attracting, pre-qualifying, and interviewing the strongest candidates instead.
Application #2: AI for candidate screening
When 75-88% of the resumes you receive are unqualified, it’s easy to see why resume screening is the most frustrating and time-consuming part of recruiting. For high-volume recruitment such as retail and customer service roles, most recruiting teams just don’t have the time to manually screen the hundreds to thousands of resumes they receive per open role.
AI for screening is designed to automate the resume screening process. This type of intelligent screening software adds functionality to the ATS by using post-hire data such as performance and turnover to make hiring recommendations for new applicants.
It makes these recommendations by applying the information it learned about existing employees’ experience, skills, and other qualifications to automatically screen and grade new candidates. This type of technology can also enrich resumes by using public data sources about previous employers and candidates’ social media profiles.
AI for resume screening automates a low-value, repetitive task and allows recruiters to re-focus their time on higher value priorities such as talking and engaging with candidates to assess their fit.
Application #3: AI for candidate matching
Candidate matching can be an even bigger challenge than sourcing: 52% of recruiters say the hardest part of their job is identifying the right candidates from a large applicant pool.
AI for candidate matching uses an algorithm to identify the strongest matches for your open req. Matching algorithms analyze multiple sources of data such as candidates’ personality traits, skills, and salary preferences to automatically assess candidates against the job requirements.
For example, a LinkedIn job posting ranks candidates by matching the skills on your job description to applicants’ skills on their LinkedIn profiles. Talent marketplaces use matching algorithms to match their community of candidates to open roles. These talent marketplaces usually cater to specific candidate skill sets such as software development or sales.
AI for matching is used to identify the most qualified candidates from those who have opted-in and are either actively looking for a new role or are very open to a new opportunity. This means recruiters don’t need to waste time trying to attract passive candidates who just aren’t interested in a new role.
如何成为招聘营销人员?How to Become a Recruitment Marketer
对招聘营销和雇主品牌有兴趣，但不知道如何推动你在这个方向上的职业生涯？不要再看！我们采访了三位专业人士，他们成功创造了明亮的招聘营销职业，以了解他们如何登上他们的第一场演出，以及你如何也能成功。
由 Kaitlyn Holbein 撰写
以下是我们的受访者以及他们成为招聘营销人员的三大秘诀：
Lane Sutton是RallyRM导师和招聘营销超级巨星。Lane 于2015年在Sprinklr发现了招聘营销。今天，Lane 在完成学位的同时支持迪士尼的招聘营销计划。Lane负责内容策划，战略以及人才市场调查。Lane也是一位备受追捧并备受推崇的演讲者，他在众多的营销和人才招聘会议上分享了他的见解。
提示＃1 - 营销人员，马上进入！
Lane的职业生涯最初始于市场营销。他的第一次实习是在HubSpot，在那里Lane提高了他的社交精明度。在Sprinklr，该团队热衷于让Lane将他的社交媒体营销技巧应用于他们的招聘需求。
“我起初对此犹豫不决，”莱恩承认道。“我不知道关于人力资源的事情。然而，我决定跳进去，很快就被抓住了。招聘营销基本上都是将你已经知道的营销策略和策略应用于候选人而不是客户。如果你来自营销背景，转型并不难。“
提示＃2 - 开始联网
“接触已经在太空工作的人，”Lane建议道。“许多人愿意和你谈谈他们的角色，职业生涯和他们工作的公司。您将获得有价值的信息并建立您的网络，这样人们就可以开始为您的团队未来的机会考虑您。“
制定招聘营销链接并获得一些知情人士的一种方法是申请RallyRM导师计划。免费课程将希望培养其招聘营销技巧的人员与像Lane这样的导师进行匹配，他们帮助他人发展事业并自信地引导新策略。
提示＃3 - 将招聘营销工作融入您当前的角色
Lane说：“越来越多的入门级招聘营销工作变得可用。“如果你的公司还没有人在做招聘营销，那么这是你的机会！开始接受项目建立一个案例在你的组织中发挥这样的角色。
“例如，如果您是招聘人员或招聘协调员，您可以询问您的经理是否可以尝试解决并改善特定的候选人体验问题。如果你在营销部门，你可以联系Talent Acquisition，看看你能否帮助他们改进他们的职业生涯内容战略。“
莱恩说，能够显示领导力，从你的工作中获得的收获可能会导致创建你的梦想职位 - 或者至少它会帮助你建立可转移的经验，在申请招聘营销职位时可以给你一个优势另一个组织。
Delaney Rader是Vanguard的招聘营销专家，她负责管理招聘博客，定义战略，采购和创建精彩内容。Delaney在加入Vanguard之前出席了亚利桑那大学。在亚利桑那大学期间，Delaney曾担任校园娱乐部的营销助理，同时还在Vanguard的雇主品牌和招聘营销团队实习。
德莱尼的重要提示：
提示＃1 - 您可能隐藏了招聘营销经验
考虑到她在Vanguard之前的日子，Delaney意识到她在成为招聘营销人员之前拥有招聘营销经验。
“在大学期间，我是商业联盟的一员，”Delaney解释道。“我帮助制作和发行传单，每年招聘新成员。我会鼓励任何想要在招聘营销中开始职业生涯的人去思考他们是否有经验可以为自己打开一扇门。“
提示＃2 - 与团队见面并挑选他们的大脑
“如果你为一个拥有完整的招聘营销团队的组织工作，或者甚至是一个管理招聘营销的人，看看你是否可以与他们见面，提出问题并开始学习。把自己放在他们的雷达上，让他们知道你对他们在做什么感兴趣。激情有很长的路要走，他们可能会想你下一次开放！“
提示＃3 - 发展你的技能，让你的脚在你身上
Delaney指出：“招聘营销人员需要的一些关键技能可以通过很多方式进行开发。“考虑如何提高你的沟通技巧，以及如何获得任何营销经验。如果你属于一个俱乐部或团队，你可以为他们管理社交饲料吗？你能帮助网站或自愿组织一个活动吗？这些都是非常棒的技能和丰富的经验，可以帮助您逐渐成长为理想的招聘营销人选。“
Ted Nehrbas是汤森路透的人才品牌营销专家。在他目前的职位上，特德执行了一系列战略，以吸引汤森路透品牌的人才，包括管理公司所有关注职业的社交媒体账户。在Thomson Reuters工作之前，Ted曾是SmashFly的招聘营销专家。他第一次真正进入招聘营销是在2015 年，一家名为Happie的创业公司成为招聘营销实习生。
特德的重要提示：
提示＃1 - 招聘人员也可以成为招聘营销人员
有很多职业路径可以导致招聘营销。实践招聘经验也是非常好的。
“在Happie实习期间，我花时间积极招聘，”Ted解释道。“这种招聘经验为我后来的招聘营销职位提供了一些最有价值的见解。我学会了候选人如何思考，他们的痛点是什么以及如何在我的组织中出售它们。这些都是我今天工作的所有领域。“
提示＃2 - 继续发展自己的品牌和社交媒体
“接受Twitter，LinkedIn和Instagram，并开始积极主动，”Ted建议道。“你从0到300名追随者获得的技能与你在社交媒体营销中用于招聘的技能类型相同。
“我也建议你逐渐熟悉，如免费工具Canva [图形设计]，Crowdfire [社会战略]，和股票照片网站，如Picjumbo和Stockvault。这些工具将帮助您制作内容营销资产，如博客和社交帖子，这些对于招聘营销策略来说越来越有价值。内容营销吸引候选人并传达他们为什么应考虑加入贵公司。“
提示＃3 - 在申请工作时记住自己的候选人经历
“考虑激起你对公司兴趣的第一件事。注意那些让你对应用程序感到恼火的东西。如果你开始有意识地考虑自己的候选人经历，那么你会想出很多伟大的想法，你可以用它们来面试或为招聘营销角色定位。“
底线是有很多方法可以获得经验并成为招聘营销人员！来自任何专业或学术背景的人都可以在招聘营销方面有出色表现，如果他们花时间在社交媒体和内容营销方面发展相关技能，与业内人士建立联系并寻找导师，并发展他们的个人品牌。
最后，感谢所有受访者的时间和提示！我们希望这种洞察力对您有所帮助，我们很高兴您正在考虑成为一名招聘营销人员。这是一个令人兴奋的新职业，我们拥有的人才越多，我们就越能够向前发展并积极影响人才招聘行业！
以上有AI自动翻译。HRTechChina倾情呈现。
Interested in Recruitment Marketing and Employer Branding, but not sure how to drive your career in that direction? Look no further! We interviewed three professionals who have successfully created bright Recruitment Marketing careers to find out how they landed their first gig and how you can too.
Here are our interviewees and each of their top three tips to become a Recruitment Marketer:
Lane Sutton is a RallyRM Mentor and a Recruitment Marketing superstar. Lane discovered Recruitment Marketing at Sprinklr in 2015. Today, Lane supports Recruitment Marketing initiatives for Disney while finishing his degree. Lane works on content planning, strategy, as well as talent market research. Lane’s also a sought-after and highly regarded speaker, who has shared his insights at numerous Marketing and Talent Acquisition conferences.
Tip #1 – Marketers, jump right in!
Lane’s career initially started out in Marketing. His first internship was with HubSpot, where Lane boosted his social savvy. At Sprinklr, the team was keen to have Lane apply his social media marketing skills to their recruitment needs.
“I was hesitant about this at first,” admits Lane. “I didn’t know a thing about HR. However, I decided to jump in and caught on really quickly. Recruitment Marketing is basically all about applying the marketing tactics and strategies you already know to candidates instead of customers. If you come from a Marketing background, the transition isn’t hard.”
Tip #2 – Start networking
“Reach out to people already working in the space,” advises Lane. “Many will be willing to speak with you about their role, their career journey and the company they work for. You’ll get valuable info and build your network so people can start to think about you for future opportunities on their teams.”
One way to make a Recruitment Marketing connection and gain some insider intel is to apply to the RallyRM Mentor Program. The free program matches people who want to develop their Recruitment Marketing skills with mentors like Lane, who help others to grow their careers and confidently lead new strategies.
Tip #3 – Weave Recruitment Marketing work into your current role
“There are more and more entry level Recruitment Marketing jobs becoming available,” Lane says. “If your company doesn’t have someone doing Recruitment Marketing yet, this is your opportunity! Start taking on projects to build a case for developing a role like this at your organization.
“For instance, if you’re a Recruiter or Recruitment Coordinator, you could ask your manager if you could try addressing and improving a particular candidate experience issue. If you’re in Marketing, you could connect with Talent Acquisition to see if you can help them improve their Careers content strategy.”
Lane says being able to show leadership the takeaways from your work could lead to the creation of your dream role – or at the very least it will help you to build up transferable experience that can give you an advantage when applying for a Recruitment Marketing role at another organization.
Delaney Rader is a Recruitment Marketing Specialist at Vanguard, where she manages the Careers blog by defining strategy, and sourcing and creating great content. Delaney attended the University of Arizona before joining Vanguard. During her time at the University of Arizona, Delaney worked as a Marketing Assistant for the Campus Recreation Department, while also interning with Vanguard’s Employer Brand & Recruitment Marketing team.
Delaney’s top tips:
Tip #1 – You might have hidden Recruitment Marketing experience
Reflecting back on her pre-Vanguard days, Delaney realizes that she had Recruitment Marketing experience before becoming a Recruitment Marketer.
“During college, I was part of a business fraternity,” explains Delaney. “I helped create and distribute flyers to recruit new members every year. I would encourage anyone who’s looking to start a career in Recruitment Marketing to think if they might have experience they could leverage to open a door for themselves.”
Tip #2 – Meet the team and pick their brains
“If you work for an organization that has a full Recruitment Marketing team or even one person who manages Recruitment Marketing, see if you can meet with them to ask questions and start learning. Put yourself on their radar so they know you’re interested in what they’re doing. Passion goes a long way, and they may think of you for their next opening!”
Tip #3 – Develop your skills and get your feet wet where you are
“Some of the key skills Recruitment Marketers need can be developed in a ton of ways,” points out Delaney. “Consider how you can improve your communication skills, as well as how you can gain any marketing experience. If you belong to a club or team, could you manage a social feed for them? Could you help with the website or volunteer to organize an event? These are all great skills and solid experience that can add up to help you evolve into an ideal Recruitment Marketing candidate over time.”
Ted Nehrbas is a Talent Brand Marketing Specialist with Thomson Reuters. In his current role, Ted executes on a range of strategies to attract talent to the Thomson Reuters brand, including managing all of the company’s careers-focused social media accounts. Prior to working at Thomson Reuters, Ted was a Recruitment Marketing Specialist with SmashFly. His first real foray into Recruitment Marketing was with a startup called Happie as a Recruitment Marketing Intern in 2015.
Ted’s top tips:
Tip #1 – Recruiters can also become Recruitment Marketers
There are many career paths that can lead to Recruitment Marketing. Hands-on recruiting experience is also excellent to have.
“During my internship at Happie, I spent time actively recruiting,” explains Ted. “That recruitment experience provided some of the most valuable insights for my later Recruitment Marketing roles. I learned how candidates think, what their pain points are, and how to sell them on my organization. These are all areas that inform my work today too.”
Tip #2 – Grow your own brand and social media following
“Get on Twitter, LinkedIn and Instagram, and start being active,” suggests Ted. “The skills you learn that take you from 0 to 300 followers are the same types of skills you’ll use in social media marketing for recruitment purposes.
“I’d also recommend getting familiar with free tools like Canva [for graphic design], Crowdfire [for social strategy], and stock photo sites like Picjumbo and Stockvault. These tools will help you produce content marketing assets, like blogs and social posts, which are becoming increasingly valuable for Recruitment Marketing strategy. Content marketing attracts candidates and communicates why they should consider joining your company.”
Tip #3 – Remember your own candidate experience when applying for jobs
“Consider the first thing that piqued your interest about a company. Note the things that irritated you about the application. If you start to consciously consider your own candidate experience, you’ll come up with tons of great ideas that you can use to get ahead when interviewing or positioning yourself for Recruitment Marketing roles.”
The bottom line is that there are many ways to gain experience and become a Recruitment Marketer! People from just about any professional or academic background can be great in Recruitment Marketing if they dedicate time to developing relevant skills in social media and content marketing, networking with people in the industry and finding a mentor, and developing their personal brand.
Lastly, thanks to all of our interviewees for their time and tips! We hope the insight is helpful and we’re excited that you’re considering becoming a Recruitment Marketer. This is an exciting new profession and the more amazing talent we have, the more we can Rally forward and positively impact the Talent Acquisition industry!
观点
2018年02月16日
观点
“人员分析现在可以成为战略性竞争优势”
工业工程师弗雷德里克泰勒在1911年发表了他的报告“ 科学管理”，该报告研究了钢厂工厂工人的流动和行为，从而开始了这一趋势。此后，公司已经部署了数千次参与调查，研究了最高领导者的特征，对留存率和营业额进行了无数次评估，并建立了大量的人力资源数据仓库。所有这些努力都是为了弄清楚“我们能做些什么来让我们的人们获得更多收益？”
那么现在这个域被称为人们的分析，它已经成为一个快速增长的核心业务举措。一项题为“ 高影响力人物分析 ”的研究报告由Deloitte在去年11月由Bersin完成，发现69％的大型组织拥有人员分析团队，并积极构建与人员相关数据的综合存储。
为什么增长和为什么业务势在必行？几个技术和商业因素相互碰撞使这个话题变得如此重要。
首先，组织拥有比以往更多的与人员相关的数据。由于办公生产力工具，员工证章阅读器，脉搏调查，集成的企业资源规划系统和工作中的监控设备的激增，公司拥有大量关于员工的详细数据。
公司现在知道人们与谁交流，他们的地点和旅行时间表，工资，工作经历和培训计划。内置于电子邮件平台中的组织网络分析的新工具可以告诉正在与谁交流的领导者，用于音频和面部识别的新工具识别谁处于压力之下，以及摄像机和热传感器甚至可以确定人们在他们身上花费了多少时间书桌。
可以认为，这些信息大部分都是保密和私密的，但大多数员工并不介意获取这些数据的组织，只要他们知道正在改进他们的工作体验，正如2015年会议委员会的研究所显示的那样，Big数据并不意味着大 哥哥。虽然从5月25日起可执行的欧盟通用数据保护条例标准将会将隐私权和治理责任放在人力资源部门，但雇主正在加紧处理这些数据并小心处理这些数据。
其次，作为获得所有这些数据的结果，公司现在可以学习重要而有力的事情。不仅高管们被迫就多元化，性别薪酬公平和营业额等议题进行报告，而且他们现在还可以使用人员分析来了解生产力，技能差距和长期趋势，这些可能会威胁或创造业务风险。
例如，一个组织发现欺诈和盗窃事件是“具有传染性”，导致同一楼层的其他员工在一定距离内出现类似的不良行为。另一种方法是使用情绪分析软件来衡量组织中的“情绪”，并根据他们的沟通模式来识别具有高风险项目的团队。
许多组织现在都在研究营业额，甚至可以通过监测电子邮件和社交网络行为来预测它，从而使管理人员能够在辞职前指导高绩效员工。组织现在使用分析和人工智能或人工智能来解码职位描述，识别造成偏倚招聘池的单词和短语，并防止性别和种族多样性。制造商使用人员分析来识别可能发生事故的员工，而咨询公司可以预测哪些人可能会因过多的旅行而被烧毁，而汽车公司现在知道为什么某些团队按时完成项目，而其他人则总是迟到。
因此，人工智能进入领域，给予它更多的权力和规模。一个新的基于人工智能的分析工具会向管理人员发送匿名电子邮件，询问简单问题以评估管理技能。通过其精心设计的算法，它为管理人员提供了一套无需赘述的建议，并在短短三个月内将管理效率提高了8％。
据Sierra-Cedar 2017人力资源系统调查显示，对于人力资源部门而言，人员分析现在是公司希望替换或升级人力资源软件的首要原因。
但对于首席执行官，首席财务官和首席运营官来说，这更重要。当一个销售团队落后于其配额实现或者商店的销售数字落后时，为什么领导者不会问“我们可能能够解决的团队中的人员，实践和管理者有什么不同？”或者甚至更大问题是“如果我们想通过收购德国的某家公司来发展我们的业务，文化和组织的影响会是什么？”这些关键的战略问题都可以通过人员分析来解决。
这门学科的历史是战术性的，有点神秘。多年来，工业心理学家领导了这项工作，主要关注员工敬业度和营业额。然而，今天，该行业正在采取新的行动，将其精力重新集中在运营，销售，风险和绩效指标上。技术工具在这里，公司已经有人工智能工程师准备以强大而有预见性的方式分析数据。分析人士表示，这个领域将会持续增长，请记住，对于大多数企业而言，劳动力成本是资产负债表中最大和最可控制的支出。
底线很明显：人们的分析现在可以成为战略竞争优势。专注于这一领域的公司可以出租，淘汰和淘汰竞争对手。
以上由AI自动翻译。
Fredrick Taylor, an industrial engineer, started this trend in 1911 when he published his report Scientific Management, which studied the movement and behaviour of factory workers in steel mills. Since then companies have deployed thousands of engagement surveys, studied the characteristics of top leaders, done countless reviews of retention and turnover, and built massive human resources data warehouses. All in an effort to figure out “what can we do to get more out of our people?”
Well now this domain is called people analytics and it has become a fast-growing, core-business initiative. A study, entitled High-Impact People Analytics and completed last November by Bersin by Deloitte, found that 69 per cent of large organisations have a people analytics team and are actively building an integrated store of people-related data.
Why the growth and why the business imperative? Several technical and business factors have collided to make this topic so important.
Firstly, organisations have more people-related data than ever before. Thanks to the proliferation of office productivity tools, employee badge readers, pulse surveys, integrated enterprise resource planning systems and monitoring devices at work, companies have vast amounts of detailed data about their people.
Companies now know who people are communicating with, their location and travel schedules, their salary, job history and training plans. New tools for organisational network analysis, built into email platforms, can tell leaders who is communicating with whom, new tools for audio and facial recognition identify who is under stress, and video cameras and heat sensors can even identify how much time people spend at their desks.
It could be argued that much of this information is confidential and private, but most employees don’t mind organisations capturing this data, as long as they know it is being done to improve their work experience, as shown in 2015 Conference Board research, Big Data Doesn’t Mean Big Brother. While European Union General Data Protection Regulation standards, enforceable from May 25, will put the burden of privacy and governance on HR departments, employers are stepping up to this and treating such data with great care.
Secondly, as a result of having access to all this data, companies can now learn important and powerful things. Not only are executives being forced to report on topics such as diversity, gender pay equity and turnover, but they can also now use people analytics to understand productivity, skills gaps and long-term trends that might threaten or create risk in their business.
One organisation, for example, found incidents of fraud and theft were “contagious”, causing similar bad behaviour among other employees on the same floor within a certain distance. Another is using sentiment analysis software to measure “mood” in the organisation and can identify teams with high-risk projects just from the patterns of their communication.
Many organisations now study turnover and can even predict it before it occurs by monitoring email and social network behaviour, enabling managers to coach high performers before they resign. Organisations now use analytics and artificial intelligence or AI to decode job descriptions, identifying words and phrases that create biased recruitment pools and prevent gender and racial diversity. Manufacturers use people analytics to identify workers who are likely to have accidents, while consulting firms can predict who is likely to be burnt out from too much travel and automotive companies now know why certain teams get projects done on time when others are always late.
AI is, therefore, entering the domain, giving it even more power and scale. A new AI-based people analytics tool sends anonymous emails to a manager’s peers asking simple questions to assess managerial skills. Through its carefully designed algorithms, it gives managers an unthreatening set of recommendations and has improved managerial effectiveness by 8 per cent in only three months.
For human resources departments, people analytics is now the number-one reason companies want to replace or upgrade their HR software, according to the Sierra-Cedar 2017 HR Systems Survey.
But for chief executives, chief financial officers and chief operating officers, it’s even more important. When a sales team is behind its quota attainment or a store’s sales numbers fall behind, why wouldn’t a leader ask “what’s different about the people, practices and managers at those teams that we may be able to address?” Or an even bigger question is “if we want to grow our business by acquiring a given company in Germany, what will the cultural and organisational impact be?” These critical strategic questions can all be answered by people analytics.
The history of this discipline is tactical and somewhat arcane. For years industrial psychologists led the effort and focused primarily on employee engagement and turnover. Today, however, the industry is taking on a new light, refocusing its energy on operational, sales, risk and performance measures. The technology tools are here and companies have AI engineers ready to analyse the data in a powerful and predictive way. And analysts say this domain will grow for years to come; remember that for most businesses, labour costs are the largest and most controllable expense on the balance sheet.
The bottom line is clear: people analytics can now become a strategic competitive advantage. Companies that focus in this area can out-hire, out-manage and out-perform their competitors.
数字助理已经来临，未来已来！乔治亚理工学院的计算机教授助理居然是一个机器人作者： 本·惠特福德 ben whitford
乔治亚理工学院2016年计算机科学课程的学生在学期结束时得到了一个惊喜：据透露，他们的助教之一，一个友善但心胸狭隘的年轻女性Jill Watson，是一个机器人。
学生们从来没有见过沃森，但觉得他们认识她。在这个学期里，她发了数百个询问，发布到班级的数字公告板上，提供作业提示，领导在线讨论，赢得了她快速，有益的回应。但与其他助教不同，沃森实际上是一个“聊天机器人” - 由Ashok Goel教授创建的虚拟助手，以减轻他的助手的压力。
一位学生在大曝光后说：“我惊呆了。“就在我想提名吉尔·沃森为杰出的助教，”另一个声明。
Goel的老师 - 机器人提供了世界工作场所可能的未来的一瞥。比利·梅塞尔（Bill Meisel）说，戈尔曾经帮助学生和同事们很容易地适应人力资源部门的需求，为员工提供不折不扣的，定制化的，实际上即时的支持。工作场所。
“移动设备或网站上的员工可以使用自然语言聊天机器人，这可以自动解决员工问题，而不会迫使员工通过材料来查找答案或需要专业人员的时间。”他说。
迈塞尔不只是理论。由于苹果，亚马逊，微软等科技巨头以及众多小公司的努力，机器人在工作场所的殖民化进展顺利。Forrester 在2017年报告说，有41％的企业已经在使用或开发AI工具; 预计三年后，至少有8.43亿企业用户在工作场所使用数字助理。
许多数字助理专注于消费者，有些比游戏改变者更具噱头 - 例如，Taco Bell的“Tacobot”让Slack用户通过聊天机器人订购午餐，但仍然需要人来接订单。不过，对于面向销售和服务的机器人来说，未来是光明的：到Gartner报告预测，到2020年，客户将处理85％的业务交易，而不会与人进行交互。
“数据民主”
随着技术的发展，机器人有望成为企业围绕人力资源乃至管理职能进行战略规划的一部分。ADP创新实验室高级副总裁罗伯托·马西罗（Roberto Masiero）说，这有可能成为一种民主化的力量，让员工可以无障碍地获取信息，帮助他们更聪明地工作，充分利用机会。
ADP自己的聊天机器人，它在内部使用，并且正在与合作伙伴机构的约2000名员工进行测试，可以发出提醒，提供职业提示，并为员工提供24/7全天候的人力资源信息。Masiero说：“它成为一个推动者。“它创造了以前不存在的数据民主。”
而且，ADP不仅看到了以企业为中心的数字助理的巨大潜力。微软和亚马逊都在努力将语音助手带到工作场所，希望工作人员有一天会使用Cortana或Alexa来管理他们的日历，处理待办事项列表并执行一些工作职能。
其他公司正在开发更专业的工具。Voicera最近推出了一个名叫Eva的语音操作数字助手，可以在会议中记录笔记，并根据所听到的讨论发送提醒。IBM正在利用人工智能来提高人才管理水平，并表示“未来每个员工都有自己的导师”。
机器人还可以在上手和训练中扮演重要角色。一个海军项目发现，接受数字辅导人员接受信息技术培训的新兵后来比刚接受培训的新兵有更好的表现，经过七周的培训后，他们的表现可以达到与具有三年在职经验的专家相匹敌的水平。
要对AI可能带来的失望做好准备
不过，并不是每个人都对AI技术的乌托邦的承诺感到兴奋。一个HR.com调查发现，人力资源专业人士无论是“深恶痛绝”，“不喜欢”或“89％的有关于AI通过在工作场所有所保留”。
即使前人关注人工智能潜力的前GOOGLE人力资源总监拉兹洛·博克（Laszlo Bock）也表示，由于商界人士对技术的迅速接受，他有点害怕。他说：“这是你第一次站在高位跳水的感觉：你知道你可能不会堕落，但你也有点害怕。
博克说，人工智能有很多方式可以使工作场所变得更好，并使员工“更快乐，更有效率”，现在正在领导一家名叫胡姆的创业公司，以改善工作为目标，“通过科学，机器学习和一点点爱“。但也有很多情况下，人工智能可以疏远工人，加强现有的机构偏见或妨碍人的互动，使良好的领导成为可能。
博克说：“通过让人类与人交谈，你能够深入了解你的组织。“在大多数聊天机器人中，你失去了这种洞察力和知识。”
问题的一部分是，“人工智能”这个词有些用词不当 - 即使是最复杂的数字助理，也没有什么是真正聪明的，也没有什么是自我意识的。这意味着一个机器人所表现出来的任何人类或移情终究都是空洞的。
这不一定总是一件坏事，因为从工作场所交互中去除人为因素可能会使员工更容易谈论敏感问题。例如，DARPA的计算机科学家发现，当人们认为他们正在与一个没有灵魂的聊天机器人而不是一个人工监控的系统交谈时，人们更可能向一个人工智能治疗师开放。
这导致心理学家发展Woebot，一个数字助理，检查精神健康患者的福利，并获得比人类倾向于接受的弗兰克反应。其他数字助理专门讨论报废问题，给终端病人一个安全的空间来找出他们的选择。“当人们进行这种谈话的时候，很难做出不公正的判断。所以，有些人可能会发现，聊聊这些关于他们想法的聊天机会会更容易一些，“来自”对话项目“的罗斯玛丽·劳埃德牧师，一个报废的慈善机构，告诉”新科学家“。
寻找减轻风险的方法
博克说，更大的担忧是人工智能系统容易扩大设计者和用户的有意识或无意识的偏见。Bock指出，微软在2016年推出了一个Twitter聊天机器人，它利用机器学习磨练了基于与真人相互作用的会话技巧 - 在24小时之内，Twitter用户已经训练了机器人鹦鹉种族主义的可怕看法，迫使微软取消这个插件。
这是一个极端的例子，但是所有的AI系统都依靠现实世界的数据进行训练，所以从本质上来说，这往往会加强现状。加入基于用户反馈的微调算法的特性，认知技术也容易加强机构偏见，即使它们提供了一个客观性的单调。
Bock警告说：“如果你现在所做的只是对现有数据进行培训，那么你将会建立复制已经存在的偏差的系统，并将其扩展到新的领域。“大多数组织正在采用机器学习的方法，将使问题变得更糟，而不是更好。”
IBM的高管咨询合作伙伴Dave Millner说，这样的问题可以计划和避免，但是只有管理者知道他们在做什么。不幸的是，人工智能系统的潜力与管理者对技术的理解之间存在着令人不安的差距。
HR.com的调查发现，大多数人力资源专业人士认为人工智能将在未来五年被广泛应用于其组织中，70％的受访者表示聊天机器人将成为员工获取人力资源信息的重要途径，一半以上的人表示，直接从电脑，没有人力老板的参与。
但是，只有8％的人力资源专业人员相信他们理解AI技术。Millner说，这种野心和无知的结合是危险的，因为它可以防止管理者以清醒的眼光看待AI。“有早期的采用者，这很好，”Millner说。“但是仍然有很多的无知，缺乏对它能做什么的知识和理解，更重要的是它不能做到。”
Millner说，需要的是一个更为深思熟虑的方法，从教育开始，最终实施被充分理解的系统，以避免偏见和其他潜在的隐患。“当然，这是一个风险，”他说。“但是，如果以适当的方式引入测试和试点，并不断学习，那么就可以减轻这些风险。”
长期观点：“积极正面”
博克还说，工作场所人工智能可以是一个福音，如果它负责任地处理。博克说：“从长远来看，这将是一个净利好。“但在短期/中期，这一切都取决于建立这些系统的人的价值观和观点。”
Bock说，对于决策者来说，并不是说AI最好避免。关键是要认识到潜在的奖励风险和意识。他说：“这是一个巨大的机会。“接下来的三到五年里，有一个关于如何善用这项技术的公司将会粉碎它，而且绝对会赢。有很大的好处。“
博克说，与其将工作场所的数字助理视为节省资金的技术，而不能将人力交互的需求自动化，公司应该将其视为增强人类决策的手段，并让管理人员有更多时间完成困难但重要的任务建立关系和培养员工。
他说：“基本上我是一个乐观主义者。“一点点机器学习可以帮助我们成为更好的领导者。”
本文由AI自动翻译，仅供参考。下列为英文版本。
Students in a 2016 computer science course at Georgia Tech got a surprise as the semester was wrapping up: It was revealed that one of their teaching assistants, a friendly but serious-minded young woman named Jill Watson, was a robot.
The students had never met Watson, but felt they knew her. Over the course of the semester she had fielded hundreds of inquiries posted to the class’ digital bulletin board, offering homework tips, leading online discussions and winning praise for her quick, helpful responses. But unlike the other teaching assistants, Watson was actually a “chatbot” — a virtual assistant created by Professior Ashok Goel to reduce the strain on his human helpers.
“I was flabbergasted,” one student said after the big reveal. “Just when I wanted to nominate Jill Watson as an outstanding TA,” another declared.
Goel’s teacher-bot offers a glimpse of a possible future for the world’s workplaces. The same techniques Goel used to help students and colleagues could easily be adapted to the needs of a human resources division, offering unflagging, customized and virtually instant support to employees, says Bill Meisel, a consultant who has researched the rise of digital assistants in the workplace.
“A natural-language chatbot, available to employees on mobile devices or a website, could automate much of the burden of answering employee questions without forcing the employee to wade through material to find the answers or require the time of an HR professional,” he says.
Meisel isn’t just theorizing. Thanks to the efforts of tech giants like Apple, Amazon and Microsoft, along with a host of smaller companies, the robotic colonization of the workplace is well underway. Forrester reported in 2017 that 41 percent of businesses were already using or developing AI tools; three years from now at least 843 million enterprise users are expected to be using digital assistants in the workplace.
Many digital assistants focus on the consumer, and some are more gimmick than game-changer — Taco Bell’s “Tacobot,” for instance, lets Slack users order lunch via a chatbot, but still requires a human to pick up the order. Still, the future is bright for sales- and service-oriented bots: By 2020, a Gartner report predicts, customers will handle 85 percent of their dealings with businesses without interacting with a human.
‘A Democracy of Data’
As technologies evolve, bots are expected to become a bigger part of companies’ strategic planning around HR and even management functions. That has the potential to be a democratizing force by giving employees frictionless access to information and helping them to work smarter and make the most of opportunities, says Roberto Masiero, senior vice president of ADP Innovation Labs.
ADP’s own chatbots, which it uses internally and is testing with around 2,000 employees at partner organizations, can issue reminders, offer career tips and provide workers with access to HR information on a 24/7 basis. “It becomes an enabler,” Masiero says. “It creates a democracy of data that didn’t exist before.”
And it’s not just ADP that sees enormous potential for enterprise-focused digital assistants. Microsoft and Amazon are both fighting to bring voice-operated assistants into the workplace, in the hope that workers will one day use Cortana or Alexa to manage their calendars, handle to-do lists and carry out some job functions.
Other companies are developing more specialized tools. Voicera recently launched a voice-operated digital assistant called Eva that can take notes during meetings and send reminders based on the discussions it overhears. And IBM is using AI to improve talent management, saying it envisions a future in which “every employee has a personal mentor.”
Bots could also have a big role to play in onboarding and training. A Navy project found that recruits who received IT training from a digital tutor subsequently outperformed human-trained recruits, and after seven weeks of training could perform at a level that matched that of an specialist with three years of on-the-job experience.
Bracing for a Potential Belly-Flop
Still, not everyone’s excited about the promised AI-powered techno-utopia. An HR.com survey found that 89 percent of HR professionals either “detest,” “dislike” or “have some reservations” about AI adoption in the workplace.
Even former Google HR chief Laszlo Bock, who is upbeat overall about AI’s potential, says he’s a little freaked out by the business community’s rapid embrace of the technology. “It’s the feeling when you stand on top of a high dive for the first time: You know you probably won’t belly-flop, but you’re also a little terrified,” he says.
There are many ways in which AI could make the workplace better and make employees “happier and more productive,” says Bock, who is now leading a startup called Humu with a goal of improving work “through science, machine learning, and a little bit of love.” But there are also plenty of scenarios in which artificial intelligence could alienate workers, reinforce existing institutional biases or impede the human interactions that make good leadership possible.
“You gain a lot of insight into your organization by having human beings talk to people,” Bock says. “In most chatbots, you lose that insight and knowledge.”
Part of the problem is that the term “artificial intelligence” is something of a misnomer — there’s nothing truly intelligent, and certainly nothing self-aware, about even the most sophisticated digital assistants. That means any humanity or empathy manifested by a bot ultimately rings hollow.
That’s not necessarily always a bad thing, because removing the human element from workplace interactions might make it easier for employees to talk about sensitive issues. Computer scientists at DARPA, for instance, found people were more likely to open up to an AI-powered therapist when they believed they were talking to a soulless chatbot rather than to a human-supervised system.
That led psychologists to develop Woebot, a digital assistant that checks in on mental health patients’ wellbeing and that gets franker responses than humans tend to receive. Other digital assistants specialize in discussing end-of-life issues, giving terminal patients a safe space to figure out their options. “It’s hard for humans to be nonjudgmental when they’re having these kinds of conversations. So some people might find it easier to talk to a chatbot about their thoughts,” the Rev. Rosemary Lloyd from The Conversation Project, an end-of-life charity, told New Scientist.
Finding Ways to Mitigate Risks
A bigger concern, Bock says, is that AI systems are prone to amplifying the conscious or unconscious biases of their designers and users. Bock notes that Microsoft launched a Twitter chatbot in 2016 that used machine learning to hone its conversational skills based on interactions with real people — and within 24 hours Twitter users had trained the bot to parrot horrendously racist views, forcing Microsoft to pull the plug.
That’s an extreme example, but all AI systems rely on real-world data for their training and so by their nature tend to reinforce the status quo. Add in features that fine-tune algorithms based on user feedback and it’s all too easy for cognitive technologies to reinforce institutional biases, even as they offer a veneer of objectivity.
“If all you’re doing is training on existing data, you’ll build systems that replicate the bias that already exists, and expand it into new arenas,” Bock warns. “The approach most organizations are taking to applying machine learning today will make problems of bias worse, not better.”
Such problems can be planned for and avoided, but only if managers know what they’re doing, says Dave Millner, an executive consulting partner with IBM. Unfortunately, there’s a troubling gap between the perceived potential of AI systems and managers’ understanding of the technology.
The HR.com survey found that most HR professionals believe AI will be widely used in their organizations over the next five years, with 70 percent saying chatbots will become an important way for employees to access HR information and more than half saying workers will take orders directly from computers, without the involvement of human bosses.
However, just 8 percent of HR professionals are confident that they understand AI technologies. That combination of ambition and ignorance is dangerous, Millner says, because it can prevent managers from engaging with AI in a clear-eyed way. “There are early adopters, and that’s great,” Millner says. “But there’s still a lot of ignorance, a lack of knowledge and understanding about what it can do and, more importantly, what it can’t do.”
Millner says what is needed is a more considered approach that begins with education and culminates in the implementation of well-understood systems that are designed to avoid bias and other potential pitfalls. “It’s a risk, of course,” he says. “But if it’s introduced in an appropriate way, with testing and piloting and continual learning, then you can mitigate those risks.”
The Long-Term View: ‘A Net Positive’
Bock also says workplace AI can be a boon if it’s handled responsibly. “In the long term it’s going to be a net positive,” Bock says. “But in the short/medium term it all depends on the values and perspectives of the people building these systems.”
The takeaway for decision-makers isn’t that AI is best avoided, Bock says. The key is to be cognizant of the risks and mindful in reaching for the potential rewards. “It’s a huge opportunity,” he says. “There’s a window in the next three to five years where the companies that are thoughtful about using this technology well are going to crush it, and absolutely win. There’s a huge amount of upside.”
Rather than viewing digital assistants in the workplace as money-saving technologies that can automate away the need for human interaction, Bock says, companies should see them as a means to augment human decision making and to give managers more time for the difficult but important tasks of building relationships and nurturing their employees.
“Fundamentally I’m an optimist,” he says. “A little machine learning can go a long way toward helping us be better leaders.”
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