人工智能正在改变人力资源工作方式
新技术和人工智能可用于提高绩效评估,开放招生和员工发展。
New technologies and artificial intelligence can be used to improve performance appraisals, open enrollment and employee development.
作者:Alexander Alonso,SHRM-SCP
像“终结者”电影中看到的那些机器的兴起可能会给我们灌输对人工智能(AI)和自动化的健康恐惧,但明智的人力资源专业人员会关注当今的发展如何能够产生积极的变化 - 即更高的效率在日常运营中和更好的员工体验。
现代技术(从简化流程的应用程序到改善通讯的机器人)正在改变我们的工作方式,这并不奇怪。然而,令人震惊的是,他们扩散到工作场所的速度很快。
以下是三个已被企业完全接受的AI示例,它们正在改变我们实践HR的方式:
众包和性能数据。为了更好地评估,商业思想领导者鼓励使用来自各种来源的及时数据。例如GloboForce这样一家员工识别软件供应商,声称众包信息比传统的评估方法能够以更定期的间隔提供更全面的性能图片。
乍一看,这可能看起来很直观。但是许多人力资源专业人士对这种软件在考虑到大量信息的性能数据流方面的准确性持怀疑态度。例如,会议结束后,Karma Notes向与会者询问个人作为团队成员的有效性。令人生畏的是,应用程序在每次会议后提出了这个问题。更重要的是,这个过程引发了人们提供反馈动机的问题。有些可能是由隐藏的议程驱动的。这项技术正在得到进一步完善,以收集与截止日期和预算有关的信息。近100家财富1000强公司正在试用这种众包的表演系统。这比以往任何时候都更加重视人力资源专业人员,以更好地理解数据管理和分析,
机器人和福利问题。如果你像大多数人力资源从业人员一样,只需要在开放的招生季节中生存下去,你很高兴。但那些幸运地通过人力资源信息系统(HRIS)来利用人工智能的人通常并没有那么糟糕。例如,今天的一些基于HRIS的聊天机器人可以自动回复员工的福利问题,并为您的员工量身定制解决方案。这意味着您花费更少的时间进行查询。虽然这些工具从来都不是完美的,但大多数使用的是一种AI,它使得信息交付非常可定制。要充分利用这一点,您必须建立真正动态的面向消费者的问答数据库,以反映您的员工和他们的偏好。
算法和学习偏好。近年来,我们看到了无数支持学习和发展活动的技术的兴起。其中最有趣的是使用AI来创建交互式测试和评估以匹配考生的个人学习风格和参与度的应用程序。与Lumosity的互动式大脑游戏类似,这些工具可在用户学习时产生无数的数据点,包括他们的步伐和学习风格。对于人力资源部门来说,这些创新突出了对员工发展的定制学习路径和数据驱动方法的需求。
很明显,人工智能在人力资源中的作用越来越大,这代表了您通过数据实现价值的机会。有些人会哭,“机器正在接管!”事实是,机器已经在这里。我们需要确定如何最好地使用它们。
SHRM-SCP的Alexander Alonso是SHRM知识发展高级副总裁。
以上由AI翻译完成,仅供你参考。HRTechChina倾情奉献,转载请注明HRTechChina
以下为英文原文:
The rise of machines like those seen in the “Terminator” movies may instill in us a healthy fear of artificial intelligence (AI) and automation, but wise HR professionals will focus on how today’s developments can give rise to positive changes—namely, greater efficiency in day-to-day operations and a better employee experience.
It’s no surprise that modern technologies—from process-streamlining apps to communication-improving bots—are altering the way we work. What is shocking, however, is the fast pace of their diffusion into the workplace.
Here are three examples of AI that have been fully accepted in businesses today and are changing the way we practice HR:
Crowdsourcing and performance data. For better appraisals, business thought leaders encourage the use of timely data from a wide array of sources. Companies such as GloboForce, an employee recognition software provider, claim that crowdsourced information provides more-holistic pictures of performance at more-regular intervals than traditional appraisal methods.
At first glance, that may seem intuitive. But many HR professionals are skeptical about the accuracy of such software with regard to performance data flow, which takes into account large volumes of information. For instance, after a meeting, Karma Notes asks fellow attendees about an individual’s effectiveness as a team player. What’s daunting is that the app poses this question after every meeting. What’s more, the process raises questions about people’s motivations for providing feedback. Some may be driven by a hidden agenda. The technology is being further refined to gather information related to deadlines and budgets, too. Almost 100 Fortune 1000 companies are piloting this type of crowdsourced performance system. More than ever, that puts the onus on HR professionals to better understand data management and analytics, and to account for relationship dynamics when interpreting such records.
Bots and benefits questions. If you’re like most HR practitioners, you’re happy just to survive open enrollment season. But those fortunate enough to leverage AI via their HR information systems (HRIS) usually don’t have it so bad. Some of today’s HRIS-based chatbots, for example, can automatically reply to employees’ benefits questions with answers tailored to your workforce. That means you spend less time fielding inquiries. While these tools are never perfect, most use a form of AI that makes information delivery extremely customizable. To take full advantage of that, you must build truly dynamic, consumer-oriented Q&A databases that reflect your workers and their preferences.
Algorithms and learning preferences. In recent years, we’ve seen the rise of countless technologies that support learning and development activities. Among the most interesting are apps that use AI to create interactive tests and assessments to match test takers’ personal learning styles and engagement levels. Similar to Lumosity’s interactive brain games, these tools generate countless data points about users as they learn, including their pace and learning style. For HR, such innovations highlight the need for customized learning paths and data-driven approaches to employee development.
It’s clear that AI’s increasing role in HR represents an opportunity for you to drive value through data. Some would cry, “The machines are taking over!” The truth is that the machines are already here. It’s up to us to define how best to use them.
Alexander Alonso, SHRM-SCP, is senior vice president for knowledge development at SHRM.