By Peggy Smedley, Editorial Director and President of Specialty Publishing Co.
It’s a New Year and a blank slate. I love the feeling of starting fresh each January and talking about what tech trends we may see in the coming year. It’s not just me—everyone likes to predict what’s coming next. It’s all about getting ahead of the next big thing. And sometimes these predictions are really wrong. In fact, my team and I started looking up predictions gone badly, and the Google search results are just funny. (Take a look at this list to have a laugh.)
So many of the predictions on Forbes’ list are hilariously incorrect, but my favorite one might be the inventor of the cellphone, Marty Cooper—who I actually interviewed several years ago on my own radio broadcast, The Peggy Smedley Show—saying cellular phones won’t replace wireline phones. Marty is a genius, and so are many of the other people who have made these terrible predictions. The problem is that here in the present, we’re too shortsighted to see how society will change as a result of various awesome inventions, innovations, and innovators.
It may be our nature to look ahead and get excited about the possibilities, but, frankly, if I tried to predict what we’d see in 2070, I’d honestly be wrong. It’s just that simple. And yet, fear not, I think here’s something I’ve noticed that may help us get a handle on what’s coming in the future: Everything is cyclical. Almost everything new is actually something old becoming new again. Sometimes, all we need to do to see what’s ahead is look backward.
It’s an interesting idea, right?
Here’s what I mean. Remember Dictaphones? Voice recognition and virtual assistants are a huge trend right now, but if you consider what a voice-activated virtual assistant is at its core, it’s like an automated Dictaphone. Instead of dictating words or instructions into a device for you or someone else to play back later, voice-assistant devices will actually do what you’re asking it, or them to do in realtime.
Here’s another. Uber and Lyft, to me, are reminiscent of calling for a driver back in the day … it’s just the high-tech version of a chauffeur. And, maybe, a few decades out, we won’t be calling for cars at all, but maybe helicopters or some other form of transportation that can be hailed on demand, perhaps by using a voice-assistant device. Even on a big-picture level, Big Data to me is like Dick Tracy 2.0. It gives us the data—the sourcing, tracking, tracing data—that we want and need. It’s like hiring a private investigator to tell us everything we need to know about our businesses.
If everything is cyclical and new things are just old things repackaged in new ways, it makes one think a little differently about trends. If we shorten the timeframe and look at the next decade, it’s a little more feasible to be specific. For example, here’s what I expect to happen in the near future:
Automation is going to change the way humans work. It’s going to revolutionize the physical workplace, change the nature of most jobs, and create a new normal in which humans and machines work together in new and different ways. The jobs available to humans will be different than they are today. This has happened before in our history as a species, and it will happen again.
As a result of this shift, there won’t be any more jobs that require repetitive work. All jobs that a machine can do will be handled by machines, but unlike today, that will be completely normal and expected. Humans won’t want these jobs anyway, because there will be many more jobs that require human ingenuity. Entirely new job categories will arise from the changes automation brings to the workplace.
Innovations in AI (artificial intelligence) will drive automation. AI will be able to do things that we are mostly just dreaming about today, like drive planes, trains, and automobiles. Ideally, AI technologies will act as an impartial judge to help humans in decisionmaking—and this will be true in so many situations, from ruling in the court of law to sorting through candidate resumes for job postings.
One huge and important discussion that we’ll be having in the next several years is about AI and ethics. We’ve already been talking about this, but we really haven’t seen anything yet. The discussion will intensify, and the stakes will be raised tenfold as these technologies become commercialized and viable in the real world.
A ton has already been said about AVs (autonomous vehicles), but my two cents is that in the next decade, a lot of the problems we currently have with AVs will be solved … but not all of them. I think we’ll solve the technology problems before we clear the societal and regulatory hurdles. For instance, we will need to change people’s perceptions about what driving should be like, and we’ll need to figure out how to regulate these machines and who to hold responsible in the event of an accident.
Two more technologies that will really impact the tech industry’s path are 5G (which we’ll see a lot more of in the next five years) and edge computing. Many technologies that we’re only scratching the surface with, like AR (augmented reality) and VR (virtual reality), will really benefit from the efficiencies that come from next-gen wireless technologies and edge architectures.
Last but not least, 2020 is kicking off a decade that will be driven by enterprises’ quest to achieve sustainability. Not a lot of companies are really talking about it yet, but I think organizations big and small are searching for answers to the question of sustainability. They’re asking: How do we respond to internal and external pressures for sustainable products and operations? How do we jump ahead of the curve so that we’re positioning ourselves proactively instead of reactively?
The companies that answer these questions sooner rather than later will be leaps and bounds ahead of those that don’t. Certainly by 2050, but probably sooner, the former group will rule the roost and the latter group may not even be around to wallow in their regrets. My question though is who will be around in 2050 to tell me if I was right or wrong or if what is old is new again? I guess that's what makes predictions so interesting.