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EdgeNetworksExpert Speak Machine-human collaboration: Is this the key to future HR success?

Machine-human collaboration: Is this the key to future HR success?

A recent report from Accenture reveals that business success will depend on ongoing collaboration between people and technology to drive efficiencies and innovation. Further, the report indicates that three quarters of companies believe that intelligent technology is vital to give them a competitive edge – and over half believe that human-machine collaboration is important for strategy.

Impact of automation on jobs
To some this means the writing is on the wall; while others debate on scale or timing of worker displacement, or the net impact on jobs of automation and digitization in the longer term.

The literature seems to show there is no consensus about the scale or timing of worker displacement, or the net impact on jobs of automation yet. McKinsey itself argues that while 49% of jobs will be subject to some degree of automation, just 5% will be fully replaced anytime soon. In most scenarios, automation will take over repetitive tasks, rather than entire jobs.

Collaboration instances
As in most successful partnerships or collaborations, each side brings to the table abilities what the other lacks. The result is complementary skills blended to use the strengths of both types of intelligence, and even physical capabilities, to fill in other’s weaknesses. The following examples of successful machine-human collaboration show how it can be a win-win:

  • The computer game Foldit uses machine-human collaboration, in addition to collaboration between humans, to fold simulated proteins. The folding is an attempt to understand how real-world proteins involved in the causes of human disease are formed. In the game, a player acts on a protein structure with manual and AI-driven operations. The AI is used where it excels, and humans are left to areas where their intuition and imagination let them exceed machines.
  • Two novice chess players in partnership with an AI system running on three PCs won against a field of supercomputers and grandmasters. The human-AI team also created a new class of chess in the process, which they called centaur chess.
  • In 2014 a Japanese venture capital firm, Knowledge Ventures, elected an AI system to its board of directors, putting machine-human collaboration at the highest levels of business.

AI meets HR
Moving beyond chatbots, today the C-suite is keenly exploring a wide range of applications for AI in improving the employee experience. Some of the most compelling relate to the areas of development, training, collaboration and teaming. Here we share some potential use cases:

Build new skills
By applying data analysis and AI, employers will be able to tailor data-laden intelligent and personalized career plans and training programs. These plans will be mapped exactly to the individual’s personality and approach to learning, based on insights and correlations that can only be achieved by machine analysis at scale.

Enable collaboration
Machine-scale data analysis can also be applied to the wider employee experience by ensuring that people are placed in teams that will work well together and collaborate effectively. As the workforce becomes more fluid to better leverage gig and contract workers to help meet skills shortages, effective teaming will become critical. The future workforce will be liquid: teams will come together ad hoc as required and be expected to be productive immediately. By suggesting team structures and hierarchies, Artificial Intelligence will prove as an essential enabler for this transformation.

Engage employees
Advanced sentiment analysis technologies are using NLP (natural language processing), text analysis, biometrics and other evolving technologies to go beyond outdated ways of assessing employee experience and seeking deeper insights into behaviors and motivations of employees. Sentiment analysis could also be used to foresee when an employee is getting unmotivated or uninterested in their work; the AI could then provide data-based recommendations on actions to boost the employee’s engagement levels.

About the author:
Arjun Pratap is an entrepreneur, the founder and CEO of HR tech start-up, EdGE Networks. EdGE offers nextgen solutions for talent acquisition and workforce management by harnessing artificial intelligence and data science.

 

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