What Does the Human-Machine Partnership Look Like in 2030?


Back in September, I wrote that when it comes to human progress we are at an incredibly interesting time. We’re at the dawn of the Internet of Everything, which already is having a dramatic impact on the way we live and the way we work – something reflected in our Digital Transformation Index.

But thinking past the dawn, what will that impact – and by extension the relationship between technology and society – look like in the future?

man wearing VR headset with Dell laptop and hologram of globe

In an effort to answer this question, we partnered with Institute for the Future (IFTF) to find out. We asked them to explore the relationship between society and technology – specifically how emerging technologies such as artificial intelligence (AI), robotics, virtual reality (VR), augmented reality (AR), and cloud computing will shape the future… and what that future might look like. What did IFTF find?

By 2030, IFTF believes we’ll have entered into the “Next Era of Human-Machine Partnerships”. What does that partnership look like? What stood out to me the most were two items. First, that we’ll all become “digital conductors” and second, that we’ll learn “in-the-moment.”

Let’s dig in a bit on these two ideas.

Be a Digital Conductor

What does it mean to be a “digital conductor?” It means to use technology as an extension of ourselves. Of course, we already do this today and have been doing so for quite some time. Think of all of the apps on your phone. You chose those apps and use them to do a ton of different things. Share pictures, text friends, shop for groceries, get directions, order taxis and prescriptions, and deposit checks just to name a few. Think about what kind of effort went into doing that before you had the app? It was a lot of work, a lot of time. But now you use those apps to ask software in the background to take care of all the work you used to do.

By 2030, you’ll still be making use of those apps – actually, quite a few more of them. But you won’t experience them quite in the same way you to do today. That’s because, by then, you could have a digital assistant that coordinates all of the tasks those apps manage – based on the outcomes you’re looking for. So, instead of hopping in your car and driving it from point A to point B, your digital assistant will ask you what destination you’d like to get to and when, and arrange for  transportation to pick you up. Your job is simply to get into the car. You don’t need to drive it. You don’t need to call up directions. You don’t even need to park it. Come to think of it, it won’t be your car you’re getting into… as you won’t need to own one. That begs another important question: what are you going to do with your garage in 2030?

…we’re going to need machines to crunch through it all and serve up the most important information for us to act on.

But being a digital conductor doesn’t stop at our personal lives – we’ll be digital conductors at work too. In the future, we’ll be able to offload even more work tasks onto software. Because in a society now driven by data, where more data is generated per second than any team of people could ever crunch through, we’re going to need machines to crunch through it all and serve up the most important information for us to act on. What might that look like? Take information security. By now we know that it’s not a matter of if a security breach will happen, but when. So rather than look for evidence of a breach that’s already happened – it makes sense to look for signs of a breach that’s about to happen. No human can possibly account for all the data – not even a small fraction. But a computer can. And it will be the job of the machine of the future to fully crunch that enormous amount of data to find evidence that a threat is looming – and then serve the information to humans, so they can apply context and judgement on what threats should be pursued. So, the focus for machines will be on preparing the right information – the focus for people will be on deciding what action to take.

Learn in the Moment

But what of the jobs of 2030? Are machines coming for all of them? No. And they can’t. Because the experts gathered by IFTF believe 85 percent of jobs that today’s learners will do in 2030 haven’t been invented yet! What IFTF is certain of is that by 2030, the ability to gain new knowledge will be valued more highly than the knowledge people already have. This means that “in-the-moment learning” will become critical.

What does it mean to learn in “in-the-moment”? Instead of undergoing training in the years before we enter the workforce – think college or a trade school – it means being able to learn what you need to do at the moment you need to do it. This struck a chord with me for three reasons. First, it reminded me of how Neo learned Kung Fu in The Matrix (admittedly, this takes it a step or two beyond the report). Second, I’ve long held that how we learn is undergoing dramatic change even today – lectures are on the way out, and things like MOOCs, Coursera, and Khan Academy have emerged to take their place. These new forums for learning are much more accessible, and at least in the case of Khan Academy can be accessed on-demand – which you could consider an early form of the “in-the-moment” learning.

“In-the-moment” learning also struck a chord because I believe AR will allow the “in-the-moment” style of learning to be fully realized. And if you attended Dell EMC World, you got a taste of what this might look like. There, I was joined on stage by Brian Mullins, CEO of DAQRI, where he showed a video in which a technician was using AR glasses – through the glasses, he was instructed on precisely how to assemble a piece of equipment – from how many screws to take, from which specific bin, and then where to install those screws into the piece of equipment. To borrow a phrase from William Gibson (who imagined a set of AR glasses remarkably similar to what we have today) the future is already here, it’s just not evenly distributed.

This is merely a taste of IFTF’s vision for the Next Era of the Human-Machine partnership. I encourage you to check out the full report here. In it you’ll not only find snapshots of the future, but also what you can do to best position yourself for it. What do you think about the next era of human-machine partnerships? Share your forecasts with me – I’d love to hear them.

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