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Open the Pod Bay Doors, Hal: AI is Here (But It’s Not Taking Over)

If we take a moment to think about the references we’ve seen and heard about Artificial Intelligence, most of them come with a warning: the robots are going to take over.

Whether it’s books or movies, our imaginations have gone wild wondering what will come with the rise of the machines. Will there be a robot army? Or an insidious intelligence that orchestrates a malicious takeover?

I remember reading A Wrinkle in Time when I was in school and watching 2001: A Space Odyssey, wondering whether technology can be trusted. And I wasn’t alone. This uncertainty has only gotten more prevalent as our creative tools have evolved to deliver more accurate representations of the magic that’s in our heads. But the reality is, Artificial Intelligence isn’t here to replace humans; it’s here to give us our lives back.

Instead of joining the fray wondering about the imminent takeover, let’s dive into a few examples of what artificial intelligence is actually designed to do:

Pattern Recognition:

Whether it’s something mundane like expense reports or life-altering like identifying adverse reactions to a new medicine, one of the greatest advantages that comes with machine learning is the ability to find patterns in large sets of data.

Let’s take a relatively “small” data set by today’s standards with a million data points. For a human to interpret that much data, we would have to create a graphical representation –  like a chart – to see if we can find statistical anomalies, and possibly even reduce the data set into averages in order to find a pattern. Because we are human, we can sometimes fool ourselves into finding a pattern that doesn’t exist or miss one that does based on what points are omitted. Computers have no such limitation – they can look at every single data point individually and then make endless calculations to find patterns.

Scale:

In addition to ingesting large quantities of data, another core benefit of artificial intelligence is scale. Once a pattern is identified, it’s much easier to develop intelligence around intended responses.

Take customer support for example. Think about the chat programs embedded within many of the websites we visit when we need an answer. Before artificial intelligence, this type of interaction required a team of people to respond to each individual inquiry. This quickly became a scale issue and created a long lag in getting real-time support. But with artificial intelligence, responses to common questions that come up over and over can be pre-programmed to deliver necessary answers much faster – and with fewer people focused on doing just that.

Speed:

Now businesses can scale to support many more customers, they also need to do it faster than ever before. Real-time data is no longer a nicety – it’s critical to adapting modern business.

Technology delivers the ability to modify the pricing on electronic shelf labels, provide supplemental data for making a stock purchase or sale, or even help to identify cancer. Instead of waiting weeks to hear about that diagnosis, it can happen in minutes. Crucial results and data interpretation delivered in near real-time is something only a computer can do.

So now that patterns that might have taken us weeks to identify happen in seconds, across a much broader set of information and output, at a much faster rate – what does this really mean to us?

One of the things I love most about being in networking is that it isn’t just about creating the next faster switch port or building a newer access point with the latest chipset – it’s about connecting things together:

  • Connecting doctors to a patient coming in on a life flight before it’s even fully on the landing pad.
  • Connecting facial recognition cameras to a geofence, alerting security if an unknown face enters the school campus.
  • Connecting customers to the product they want even if it’s not in that physical location.

It’s about connecting people to technology in order to improve human experiences – and those connections are only possible if we can scale our networks to meet the demands of these new experiences. This is the beauty of AI. If we can build a network that is self-learning, self-healing, self-securing, and self-optimizing, it gives us the ability to deliver those connections.

The possibilities are endless –but the computers don’t dream up those possibilities, we do. We can only spend time dreaming when we are freed from the mundane tasks that can be replaced with AI. I think it means that at the end of the day, the machines aren’t replacing our humanity – they’re giving us time to be human.

What connections do you dream of? Share the possibilities with us on Twitter at @ExtremeNetworks and connect beyond the network!

This blog was originally authored by VP of Product Marketing, Abby Strong.

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