Reconstructing work

Automation, artificial intelligence, and the essential role of humans

Some say that artificial intelligence threatens to automate away all the work that people do. But what if there's a way to rethink the concept of "work" that not only makes humans essential, but allows them to take fuller advantage of their uniquely human abilities?

Key take out from the report

Will pessimistic predictions of the rise of the robots come true? Will humans be made redundant by artificial intelligence (AI) and robots, unable to find work and left to face a future defined by an absence of jobs? Or will the optimists be right? Will historical norms reassert themselves and technology create more jobs than it destroys, resulting in new occupations that require new skills and knowledge and new ways of working?

This article shows us how with the advent of AI makes it possible—indeed, desirable—to reconceptualise work, not as a set of discrete tasks laid end to end in a predefined process, but as a collaborative problem-solving effort where humans define the problems, machines help find the solutions, and humans verify the acceptability of those solutions.

What issues does this address?

Human and machine intelligence are different in complementary, rather than conflicting ways. While they might solve the same problems, they approach these problems from different directions. Machines find highly complex tasks easy, but stumble over seemingly simple tasks that any human can do. While the two might use the same knowledge, how they use it is different. To realise the most from pairing human and machine, we need to focus on how the two interact, rather than on their individual capabilities.

Reframing work, changing the foundation of how we organise work from task to be done to problem to be solved might provide the opportunity to jump from the industrial productivity improvement S-curve to a post-industrial one. What drove us up the industrial S-curve was the incremental development of automation for more and more complex tasks. The path up the post-industrial S-curve might be the incremental development of automation for more and more complex behaviours. The challenge, though, is to create not just jobs, but good jobs that make the most of our human nature as creative problem identifiers. If we are to change the path we are on, if we are to choose the third option and construct work around problems whereby we can make the most of our own human abilities and those of the robots, then we need a conscious decision to engage in a similar dialogue.

How can Deloitte help you

The future of work is here! Are you ready? Our Human Capital specialists can help you prepare for it.

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