AI正在彻底改变打工人的工作方式,以下3种策略可以应用于日常工作

币界网Published on 2024-08-06Last updated on 2024-08-06

币界网报道:

尽管是企业领导,当前也很难明确人工智能(AI)的发展方向。

虽然领导者的任务是在企业中确定明确的AI用例和监管框架,但大多数老板仍在为AI的使用而绞尽脑汁。

假如你是企业老板,该如何面对突如其来的AI技术对员工的冲击

从一个企业家的角度出发,我们必须在坚定地立足于当下的同时展望未来——并认清AI技术对我们的商业模式、员工体验和用户的实际意义。

这是一项艰巨的任务,需要我们去适应和学习。坦诚面对我们的学习需求,是我们前进的最佳途径。

生成式AI在各行各业的快速引入,不仅在领导者之间,也在员工之间造成了巨大的技能差距,给我们所有人都带来了更大的压力,要求我们迅速提升知识基础,与时俱进。

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然而,这种演变并不是自然而然的:62%的员工表示,他们缺乏有效、安全地使用AI的技能,全球只有十分之一的员工认为自己掌握了所需的AI技能

作为领导者,弥合这一知识鸿沟是我们的当务之急。我们可以做很多事情来指导我们的组织应对各种变化,包括我们现在面临的人工智能。

但是,在AI时代,可持续的技能提升应该是什么样的呢?

下面是将人工智能技术应用于日常的三种策略:

01.为技能提升目标提供充足的资源

新一代AI技能提升既不是一次性的努力,也不是一蹴而就的事情。技术的复杂性和持续演进需要专门的教育途径、持续的学习机会和资金支持。

因此,作为领导者,我们需要为员工提供资源,让他们能够参与学习机会(如技能培训),参加LinkedIn等组织提供的第三方课程,或为需要的技能提升提供学费报销。我们还必须确保所有员工都能获得这些资源,无论员工的日常工作性质如何。

在此基础上,我们可以将记录和分享学习成果的机制制度化,包括建立和普及沟通渠道,激励员工分享反馈、共同学习和发现遗留难题。鼓励围绕学习开展交流和对话,并亲自参与这些讨论,往往能在整个组织中实现更大的创新

在一个公司,建议将学习和分享融合在一起,例如,每月就相关主题开展学习活动,并鼓励所有人同时参与。

具体来说,可以设定一个主题——比如AI,员工可以选择与个人职责相关的课程,学习新的AI技能,同时还可以加入“学习休息室”,与同事分享想法和挑战。

02.以身作则,带头学习

投入时间了解新兴的生成式AI解决方案及其对企业的影响。这样可以赢得员工的认同,并说明领导者对人工智能如何以实际方式改善运营的愿景。

领导者需要在花费大量时间提高自身技能的同时,也要寻找机会指导他人,让AI的使用成为工作中互动的日常。

此外,考虑举办以解决方案为重点的黑客松或其他有意思的挑战,以培养创造力、跨职能问题解决能力和协作能力。

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在可能的情况下,直接通过实际项目的在职实践来激励行动。员工往往身兼数职,因此,无论提升技能多么重要,都很难抽出时间。

在现有的工作量中注入新的学习计划,可以同时满足这两种需求,尤其是对于日程安排繁重的员工而言。

还要与员工进行沟通,比如定期征求团队的反馈意见,以确保满足他们不断变化的职业发展需求,与公司领导的坦诚对话具有重要意义,这可能是更多标准会议(如员工与经理的定期一对一会议)难以实现的。

03.通过正确的数据和技术投资支持技能提升

为了确保员工能够提升AI技能,为他们提供必要的技术、数据和基础设施是至关重要的。与领导者合作,数据管理和技术堆栈进行必要的改进,以支持AI目标的实现。

例如,在快速可靠的连接支持下,人工智能解决方案在数据丰富的环境中表现出色。不要因为数据问题、容量不足或安全问题而影响员工提升技能或推动创新的热情,尤其对于严重依赖数据和计算的行业,如医疗保健、金融、制造、网络基础设施和教育,应迅速采取行动。

随着时间的推移,持续迭代并努力确保AI技术基础设施始终能够胜任任务。新一代人工智能正在不断发展,要跟上这些变化的步伐,就需要采取多方面的方法来提高技能,让AI和数据与员工合作,而不是彼此成为对手

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生成式AI解决方案的影响可能会超越云计算,对我们的组织运营和发展产生更广泛、更持久的影响。

然而,只有当我们掌握了相关技术,并准备好让人工智能成为所有员工日常工作的一部分时,这一未来才会实现。

当前,有效、可持续地使用AI解决方案对一个组织来说是不可避免的,因此,在重视集体、持续学习的公司文化氛围中,通过灵活的AI培训计划来促进公司的成长也尤为关键

AI技能提升可能会让人感觉与一般的工作日常相去甚远,但这是领导者必须开始重视的一个点,因为人工智能有可能彻底改变我们目前的工作方式。

原文来源于:

https://venturebeat.com/ai/in-the-age-of-gen-ai-upskilling-learn-and-let-learn/

中文内容由元宇宙之心(MetaverseHub)团队编译,如需转载请联系我们。

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