Human-Centered A.I. is the Future of Talent Management
Will A.I. eliminate my job?
It’s a clickbait title most of us are now familiar with.
In recent years we’ve been met with a wave of articles and soundbites — ranging from the realistic to apocalyptic — speculating as to whether A.I. will replace human jobs, take over the world, or otherwise render Us insignificant.
Tesla CEO Elon Musk has even gone so far as to suggest that the volume of jobs that will be lost due to automation will create the need for a universal basic income.
A fear of new technology, and of the impact that that technology will have upon the job market is not new.
Technological developments that arose during the Industrial Revolution created public fear of mass unemployment (a fear that ultimately proved to be unfounded given the large number of new jobs these technologies created).
Yet the narratives have never felt quite so existential before this moment.
So what is different about A.I. that has so captured the public interest, and it seems, fear?
It seems to lie in the idea that intelligent machines will not seek to supplement aspects of our existence, but rather, replace us entirely.
Computer Scientist Subhash Kak advocates for this idea with respect to the job market in his think piece for NBC News (a piece, it is worth noting, entitled “Will robots take your job?”). The reason A.I presents a greater threat to society as we know it, he argues, is “today’s A.I. technology aims to replacethe human mind,” not simply to make industries more efficient (my emphasis).
It would be naive to ignore the reality of Kak’s argument with respect to tasks requiring learning and judgement. A.I. is already replacing human decision-making in industries such as transportation and manufacturing.
But are all applications of A.I. really aiming to replace the human mind in the workplace? And should they?
There are other views — and other technological frameworks — to be had here.
“Human-Centered A.I.”
In opposition to A.I.’s “takeover” rhetoric exists a school of thought that explicitly acknowledges the benefit of partnership between humans and intelligent machines.
Fei-Fei Li, director of the Stanford Artificial Intelligence Lab, calls this approach “human-centered A.I.” — a framework for guiding the development of intelligent machines by human concerns.
At a high level, the goals of human-centered A.I. are as follows:
A.I. should aim to enhance human thought rather than replace it
A.I. should encompass the more nuanced and contextual aspects of human intellect, aided by outside fields such as psychology and sociology
The development of A.I. technology should be guided by a concern for its effect on humans
There are a number of cross-industry applications of A.I. that can be viewed within this partnership framework.
Take, for example, the development of robots used to reduce costs, time, and human-error during surgery, allowing doctors to focus on the more nuanced aspects of the surgical process. Or, developments of A.I. in agriculture, such as Blue River Technology’s “see and spray” technique for applying herbicide only where needed, saving farmers money on herbicide and delivering a more sustainable product to consumers.
But perhaps even more in contrast to the fear of a robot taking one’s job, is the increasing extent to which A.I. is being applied the field of talent management.
That is to say, A.I. is being used to actually improve the workplace and the worker experience, rather than replace the worker.
A.I. as a Tool for Improving the Workplace
In the past several years, we have seen an emergence of companies applying A.I. to problems in talent management. From Paradox.AI’s Olivia, to Beameryand Textio, its fair to say that A.I. is on HR’s radar in a way that it wasn’t 5 years ago.
What’s interesting about this trend is that unlike other industries with a stronghold in A.I., talent management has until recently been viewed almost exclusively as a “fuzzier” aspect of the business. It is an industry built on relationships, human connections, and emotional intelligence, and yet, it is being improved with A.I.
To be fair, up until now a majority of A.I. solutions for talent management have focused on the more tedious and error-prone tasks around candidate sourcing and evaluation (tedious + error-prone = a perfect opportunity for automation).
But there are also opportunities for A.I. to improve the post-hire aspects of the employee experience, and human-centric A.I. is the key.
As the marketing world has known for years, A.I. provides a unique opportunity for scaling a personalized experience. Why would you show me the same thing as everyone else, when I’m more likely to convert if you show me exactly what I want?
The same principles can be applied to the post-hire employee experience.
Employees have different skills sets and motivators. If my employer places me in an environment that is optimized for my skills and motivators, I’ll stay. If not, I’ll move on.
As the progression towards a digital workplace continues, companies also have more data about their human capital than ever before — who they are talking to, what they eat, when they’re online every day. WeWork is basing their business model around this data.
Human-centered A.I. can unleash this data to help talent leaders create a more personalized employee experience. It is in “fuzzier” domains like talent management where human-centered A.I. shines, not just for ethical reasons, but because it provides the best user experience.
At Cultivate, for example, we apply human-centered A.I. to personalize the leadership development experience for managers. Using digital communication data as a proxy for leadership behavior, we analyze and predict how managers’ actions are affecting their team, and offer suggestions for how to improve.
At no point do we attempt to stand in as a replacement for a manager, or a talent leader. Rather, like a real-life leadership coach, Cultivate offers tips and suggestions that a manager can choose to take, or not.
This is the kind of personal experience employees expect from their talent leaders, scaled with A.I. And it doesn’t need to stop at learning and development. A.I. also has high-potential to impact other aspects of the employee experience, from interviewing and on-boarding to performance reviews and off-boarding.
Looking Forward
There is no doubt that A.I. is changing the world — and the job market — as we know it.
Industries will be disrupted. Jobs will be lost, new jobs will be created, some jobs will never be replaced.
Ethical dilemmas will be raised. They already are.
The degree of difference between aspects of human intellect and intelligent machines will become smaller.
However, with careful consideration for A.I. design that creates a sense of partnership between humans and intelligent machines, A.I. isn’t a force to be feared in the workplace, but embraced.
作者:玛格丽特托马兹祖克
About Cultivate
Cultivate helps companies leverage their digital communication data with A.I. to extract important organizational learning and unleash leadership potential.
For more information on what we are doing at Cultivate, check out our website.
英文也比较简单理解,就不翻译了~
自动化趋势和2020年的招聘职能来源/李笛Steven
合作者/领励 LinLead
传统的招聘职能将转变为更加个性化、顾问导向的职能,进而呼唤一系列不同的技能。
01
RPA:招聘流程自动化/机器人流程自动化
流程自动化早就是制造业和企业流程的一部分了。现在影响到了招聘。
最近,《首席信息官杂志》(CIO Journal)的一篇文章提到,这一市场规模,有望从2013年的1.83千万美金跃升到2020年的49亿8千万美金。
简历存储、提取、查询的自动化曾是最开始的应用,还有一些其他类型的报告。
申请人追踪工具曾是这个领域的先锋应用,随后与候选人关系管理(candidate relationship management - CRM)工具、筛选和测评工具相整合。
最近,人工智能和机器学习已经引发了聊天机器人的开发和应用,用于响应候选人问询,并指引他们完成职位匹配、评测和职位申请等流程。
在下面图表1中,考虑到需求强度和预算可行性,我列出了我认为,在2020以前实现自动化的招聘环节各自的可能性。
总体来说,很大一部分的招聘流程将被自动化——并且已经在一小撮公司中获得到了应用。
然而,现实中就算有招聘流程中应用了自动化,大部分来说,(这个)自动化成分只占招聘活动的极小部分。
这些职能容易受到崛起中的RPO(recruitment process outsourcing )外包机构的负面影响,要知道,后者已经投入重金到自动化(领域),并做到了比客户内部更低成本的运作。
图表2显示了我对截止2025年前,在先进公司和RPO外包机构中,自动化可能达到的最高程度的判断。
02
有关人工智能、机器学习和预测性分析的应用增长
自动化的应用增加,得益于人工智能领域里日益取得的巨大进步。
人工智能正在增强或者强化招聘官使用的工具的效力,包括测评流程、视频面试和聊天机器人。
在未来3年中,所有的软件都将增加一定程度的人工智能功能。
现有、可商用的聊天机器人和智能助手包括:Impress, Wade & Wendy, Olivia, Mya, Karen, JobPal和Ari。可能我遗漏了不少,并在以周为单位更新(我的统计)。
这些全都在使用人工智能和机器学习(技术),来不断完善他们的表现。
在今天来说,这是可行的,即,在人工智能的助力下,(人们)通过目标营销(targeted marketing)和个性化讯息发现和触达潜在候选人。
然后,与这些潜在候选人的互动,接着将由聊天机器人接手,再(吸引潜在候选人)进入到筛选和匹配环节,直至职位推荐(环节)。
与原来借助绩效和其他数据分析来改善工作的招聘官来说,这些工具将更少受到偏见的影响,稳定性更佳。
招聘官的职责将变为作出(招聘)决定,或者指导用人经理作出(招聘)决定。
与传统的招聘技能相比,影响和倾听技巧,以及营建组织内外及与潜在候选人的关系的能力,将变得更加有价值。
03
重新设计招聘职能
“如果继续从事招聘工作,招聘官的首要角色,将是教练、顾问和导师,同时协助候选人和用人经理。”
其他职能,诸如薪酬、福利、考勤、法务、合规等,已经高度自动化,或者已经实现了外包。
员工关系和其他更加人际化的职能将较少的受到人工智能的影响,尽管这些职能也会从中受益。
人力资源职能中,招聘却将是受人工智能影响最大的。招聘官的技能需要变化,适合这个职能的人选类型也需要作出变化。
技巧、岗位知识和招募技能再也不那么重要了。传统的招聘职能将转变为更加个性化、顾问导向的职能,进而呼唤一系列不同的技能。
科层制将会弱化,这一职能将分散到各种业务活动之中,不再由单一领导负责。运营活动将越来越自动化,对人工干预的需要越来越少。
在某个时点,所有组织级软件,将通过集中化的模式,(向员工)提供行政支持。
欢迎来到人工智能支撑的未来世界。
*本文原作为英文,由原作者(作者简介见后)授权我们翻译为中文,取为现名。点击“阅读原文”,可以查询英文原作。
We thank the author Kevin Wheeler (see more below) granting us to translate and publish this article. you may click the button at the bottom "Read more" for the link to the original edition Originally Published on LinkedIn, on June 1, 2017 in English.
About Kevin Wheeler
Kevin Wheeler是知名的人力资源专家和未来学者,是全球广受欢迎的演讲嘉宾。他还推动一间智囊机构的工作,专注研究将对人才和工作带来直接影响的趋势和问题。