Human–Machine Collaboration in the Workforce of the Future

By now we’ve all heard about how artificial intelligence (AI), machine learning (ML), and automation are changing the digital workforce. Many are afraid of what that change could represent for their jobs and relevancy in the workforce.

Perhaps some fear that age or culture will prevent them from adapting to the technologies and workforce of the future. Others may fear that a robot will be able to do their job better than them, making them irrelevant.

But that fear is misplaced. Change has always been present for workers, and while the advent of AI and ML technologies is ushering change in quickly, history has shown us that we don’t need to fear this change. Harvard Business Review reports that an analysis of 1,500 companies implementing AI within their organizations found “the companies that had humans and machines working alongside each other had the greatest success.” In fact, they found that those companies that tried to simply replace humans with machines outright only experienced short-term gains.

So let’s take a look at how humans and machines can collaborate, as well as steps companies can take to facilitate true human-machine collaboration.

Human-in-The-Loop Processes

HBR says humans need to do three important things for machines: “They must train machines to perform certain tasks; explain the outcomes of those tasks, especially when the results are counterintuitive or controversial; and sustain the responsible use of machines (by, for example, preventing robots from harming humans).”

What this human-in-the-loop process looks like is that no single task will be entirely completed by a machine or a human working on their own; instead, every task will have a human and machine working on shared responsibilities. With AI taking on the role of ‘helper’ rather than replacement, successful machine-human collaboration with tomorrow’s digital workforce will be central to the future of work.

As we begin to transition to the workplace of the future, training will play an important role, where data from subsequent actions, aided by human oversight, is used to improve the model. (For example, when ML models in your email inbox, watch every message that you mark as spam or rescue from junk to discover new patterns and reduce the frequency of these errors in the future.)

The Hyperscience platform, as another example, uses cutting-edge, machine learning techniques to know when to involve humans in the loop. When the machine is unsure of its transcription, it sends the field to supervisors to review and resolve. Those responses help fine-tune the underlying models to drive higher automation performance. For businesses, this means less human involvement, greater automation, and more time to focus on value-add activities that drive the business forward.

Your Workforce of the Future

These aren’t just hypotheticals — embracing AI will directly benefit your workforce. 57 percent of workers think that a greater degree of AI and automation would boost productivity. Research by Gartner reveals that, “By 2022, one in five workers engaged in mostly non-routine tasks will rely on AI to do a job.”

But what can organizations do to enable machine-human collaboration? There are a few steps companies can take as technologies, roles, and responsibilities change, allowing them to be able to adapt and change with it.

  • Change how we talk about machine-human collaboration. Yazad Dalal, Head of HCM Strategy, EMEA at Oracle says “we need a paradigm shift in how we even talk about these changes.” Instead of focusing on the changes and jobs that may be automated, talk about new skills that will allow employees to work smarter and utilize the machines to make their jobs more efficient.
  • Reimagine business processes. Key to this is to help employees develop the skills they need to effectively collaborate with machines. HBR calls these “fusion skills” – learning to delegate tasks to machines, training machines to perform better, and ensuring the machines are being used responsibly and ethically.
  • Develop an automation center of excellence. This will act as an epicenter where a company executes, builds, and controls its greater long-term automation strategy.

Applying AI to routine work will see human-machine collaboration perform more effectively than if either worked alone.

The AI revolution won’t happen overnight. Digital transformation is a gradual process. There will be a lot of ground work and preparation we can employ today to be ready to optimize and fully access the potential benefits of AI and automation. Stay tuned for more ‘future of work’ blog posts to see what your company needs to do to prepare.

Credits

Design: Chen Nergal

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