2016: A Year of Advances and a Few Reality Checks

Reflection in rear view mirror of businesswoman driving car

Before 2016 disappears from view, it’s worth pausing to sum up where all that happened in our fields of interest got us. Sure, there were a lot of stories about robots (killing us, replacing us, filling all kinds of unmet needs for us…) in the past 12 months.

Beyond the hype though, there are some clear takeaways to keep in mind as 2017 kicks into gear.

#1: Robots are forcing us to think about the definition of work. From white collar jobs to farming and customer service we saw robots move into a broader range of categories. Gaining skills, dexterity and the human abilities in touch and sense make it more and more possible for robots to work directly with humans.

Still, the robot workforce is more a novelty than a reality. People are still doing jobs they should not be doing. And while the concept of “guaranteed income” (since we won’t have to work one day) might appeal to some, most of us realize that to be human is to have purpose and for more than not, purpose means work. Navigating the “new” model for work needs to be as much a part of the discussion and investment as is the technological innovation that is forcing us to re-examine who does what.

#2: Artificial intelligence (AI) has been around for decades, but the non-rules-based form of AI is still a very nascent field…at least as far it goes in replacing the human brain with a machine. If you believed the coverage of AI in 2016, you might expect that machines are advanced enough to try legal cases, teach graduate level physics and run the world. More realistically, machines today can be “trained”, for example, to recognize a cat after being shown an image of cat thousands of times – but unlike humans, machines can’t extend that “knowledge” to differentiate between a cat and a penguin until you show it another thousand images of penguins. That means that when presented with an “unknown” scenario – something the machine hasn’t seen before – it can’t determine what action is necessary – which is a very human trait.

So while Google’s AlphaGame won at Go in 2016, when it comes to navigating real-world situations, robots aren’t replacing human cognition yet.

#3 Manufacturing is the new black. Well before the election and its focus on bringing manufacturing jobs to the US as the silver bullet for fixing the economy, expectations were high around the digital transformation of manufacturing. More and more, there’s honest talk about the 300,000+ jobs that are currently unfulfilled and the need for a new model for cultivating the skills needed to work in smart factories. The spotlight on manufacturing isn’t likely to fade, creating a real window of opportunity for the sector’s revitalization.

While robots and advances in cognitive automation got a fair share of attention in 2016, we’ve got work to do to make the most of the innovation that will continue to evolve. As we roll up our sleeves to work with companies around the world on transforming their operations with smart, collaborative robots in the coming year, we’re looking for ways to make all the promise real. If you’ve got an experience to share about this journey, tweet me @jim_lawton.

Originally published on Forbes.