Gartner Hype Cycle: 5 key emerging trends

TechRepublic's Karen Roby talks with a Gartner analyst about tech trends, including advanced AI analytics, sensing immobility, and more. He also discusses deepfakes and low-Earth orbit satellites.

Gartner Hype Cycle: 5 key emerging trends TechRepublic's Karen Roby talks with a Gartner analyst about tech trends, including advanced AI analytics, sensing immobility, and more. He also discusses deepfakes and low-Earth orbit satellites.

TechRepublic's Karen Roby talks with Gartner Analyst, Brian Burke, about the Gartner Hype Cycle and emerging tech trends. The following is an edited transcript of their interview.

Brian Burke: The hype cycle for emerging technologies is one of the key hype cycles that Gartner produces. And just to give you an idea of what a hype cycle is, it's really how we track technologies that are emerging in the marketplace and how those technologies are evolving based on the hype that they're seeing in the press. So, we have technologies that are introduced often in labs, and the press gets very excited about them. We see some use cases for those technologies, some early successes. And typically, as the technology's being over-hyped as it's going up to the peak of inflated expectations, this is typically where technology is presumed to be able to sing and dance and wash the floors.

But then, we find out that the technology isn't actually useful for all those things. Can't sing, can't dance or wash the floors, and it goes into the trough of disillusionment. And then, once we find what are the actual use cases, how technology can be applied and can be applied consistently, we move up to the plateau of productivity as organizations start to apply those technologies in a repeatable way. So, that's the hype cycles, and that's how they work. It's a method we've used for more than a dozen years to track technologies as they go through their life cycles.

Karen Roby: There are always things that we have such great expectations for, Brian, and it doesn't always turn out the way that we may hope. And then sometimes, things come out in a very different way, and it can be a good thing. So, break some of this down for us here, starting with the technology, the trends that you see people are going to be excited about and have great potential.

Brian Burke: Well, as we put together the hype cycle for emerging technologies, and to mention, this is an aggregation of all of the technologies that we're tracking at Gartner. That's more than 2,000 trends in technologies. And so we're aggregating what we believe are the most impactful for organizations over the next five to 10 years, and that's how we put together the hype cycle for emerging technologies, one of 125 cycles that we put together. And as we aggregated these technologies into the hype cycle for emerging technologies, we saw that there were five key trends that were emerging that we wanted to highlight. And so those are advanced artificial intelligence analytics, which of course we're hearing a lot about, how artificial intelligence is being applied to virtually everything these days. Augmented humans, which is really about how technology is augmenting humans both cognitively and physically and how those technologies are evolving.

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Digital ecosystems is really about how business ecosystems, which have existed for a long time, are becoming more digital, which is reducing friction in those ecosystems. So, exchanging with our partners, customers, suppliers, and those kinds of things. The next trend is post-classical communications and compute, which is an advancement in technology, and it's a step-change in advancement. So, we've had Moore's law for 30 years that has predicted improvements in technologies. And what we're seeing is a step-change in how technologies are improving. We're highlighting some of those. And finally, sensing immobility. Sensing immobility has a lot to do with things like drones and autonomous vehicles and those kinds of things where it's the underlying technologies that are enabling those, are around sensing the environment, managing movement in that environment, manipulating objects in that environment, and that's using some of the same core underlying technologies.

Karen Roby: Talk about the fears a lot of people have and for a good reason for some when it comes to artificial intelligence, the impact on the workforce and how things may or may not change for us humans.

Brian Burke: Well, there's certainly a lot of fear out there around artificial intelligence, and it's going to have an impact, but I think that people misinterpret the impact that it's going to have. So, one of the trends that we talk about is augmented intelligence. And in augmented intelligence, what we're seeing is that we've got a human centric approach to how artificial intelligence is going to be applied. Artificial intelligence today is useful for very narrow task-based kinds of work. And so what we see is that artificial intelligence is going to be used for task automation, but it's not going to be used for job automation. And so we're not going to see people so much displaced from the workforce. What we'll see is the shift from tasks, particularly repetitive tasks, where they're going to be done more by computers and robots and things like that. And that'll free up time for the humans in the loop to provide the more creative thinking that's required for those jobs.

So, I think it is important to recognize that artificial intelligence is going to have a significant impact, but it's not going to displace jobs directly. It will augment people in jobs and free up their time to do more interesting things and the repetitive task of doing it today.

Karen Roby: One of the things we were talking about here just a few minutes ago before we started recording this is deep fakes, and we hear so much about that and in the news and people don't understand the technology that's actually behind it and what else it can do. 

Brian Burke: Well, the technology behind deep fakes is called generative adversarial networks. And basically, a generative adversarial network is two algorithms that are dueling. So, we have a generator, and a generator is an algorithm that generates something. In the case of deep fakes and images, it's generating, let's say, a person that doesn't exist. The discriminator then evaluates that generated image and says, "Does this look like a real person or not?" That goes back and forth, back and forth, and back and forth until the generator generates an image that the discriminator can't determine is not a real person if we're looking at those cases. And so that's the basic technology behind that. So, there's been a lot of fear and uncertainty and doubt around deep fakes and how they're going to influence politics and those kinds of things, and those are real fears, but I think that it's important that we also look at what are the potential positive commercial impacts for these technologies. Because at its core, if you have an algorithm that can generate something novel based on what it knows about, say, what a cat looks like, what a dog looks like, what a person looks like, it can also generate something novel or something useful.

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So, generate novel marketing copy, for example, or generate synthetic data. So, that's data that appears like real data, but because it's synthetic data, it's generated, there's no risk of having personal information loss, or we can generate things like drug compounds, pharmaceuticals to target specific diseases. And so there are tremendous implications for generative adversarial networks right now. Unfortunately, all the press is around deep fakes, and I understand why, but I think that there's tremendous opportunities to leverage this technology for good and commercial purposes.

Karen Roby: Unfortunately, we don't always hear the positive, right, the good stuff on the other side of it. It's just the negative that we tend to focus on. So, Brian, before we let you go here, anything here in this list that you especially are excited about or interested in of what we're looking forward to?

Brian Burke: Well, I think that one of the technologies that I'm personally excited about, it's called low earth orbit satellites. Now, low earth orbit satellites, LEO satellites are different in that they are very close to the earth as opposed to the fixed stationary satellites that we have today. And that has a couple of advantages. So, one of the advantages is that it will enable high-speed data transfers with low latency. So, that is going to enable us to have alternative communications, particularly in remote areas for things like realtime operation of drones and those kinds of things.

But actually, what I'm more personally excited about is that right now, 48% of the homes in the world do not have adequate access or do not have access to the internet. And what low earth orbit satellites promise to provide is global internet coverage at a reasonable price and, of course, with low latency, so it's fast as broadband. And so, I'm personally excited about opening up this digital virtual world that we all live into the other 48% of the world that doesn't have cost-effective access to it today.

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