Judgment Day? Why you don’t have to fear machine learning


Machine learning is a type of artificial intelligence that helps computers learn without having to be programmed by a person. The goal is to get computers to learn in a similar manner to humans.

On August 29th, 1997, the artificial intelligence program Skynet became self-aware at 2:14 a.m. Eastern time. Judgment Day they called it. From that moment on, the human race was destined to become extinct because the machines saw humans as obsolete. The machines chose to wage a war on the human race in order to destroy them. Luckily, this guy Kyle from the year 2029 traveled back in time, changed history, and here we are, safe and sound.

Fortunately, the only artificial intelligence (AI) that you need to worry about these days is if the coffee maker will have espresso ready by the time you get out of the shower. Our “smart” appliances don’t have sophisticated AI programs such as Skynet on them; however, they do utilize something a little similar called “machine learning.”

What is machine learning?

The goal of machine learning is to get computers to learn in a similar manner to humans. Machine learning is a type of artificial intelligence that helps computers learn without having to be programmed by a person. These computers are programmed in a way that focuses on data that they receive on a regular basis. This data can then help the machine “learn” what preferences are and adjust itself accordingly.

A simple example of machine learning is found on social media platforms. You may notice that some of the ads seem to have been made just for you. That’s because the service is actually looking at data about you and trying to predict what you will be interested in. This is done in a few ways, such as examining website cookies to determine what sites you have visited in the past to help draw a conclusion of what may be of interest to you in the future. The more the algorithm learns about you, the more it can fine-tune itself to learn your “likes” and even “dislikes.”

Machine learning makes “things” smart

Nowadays, anything from a security camera to a toaster can connect; however, not everything is smart, or has the capability to learn. The main reason why a device is made smart is to provide the user more convenience. From a thermostat knowing that you prefer to turn on your heating to 23 degrees at 2 p.m. on the weekends (and automatically does so for you), to your lights coming on every night at 6 p.m. in your living room, these devices are learning all about you. Using a variety of sensors, user input, and any other data the machine can access, it will constantly analyze it against previously collected data in order to make itself smarter.

What about all that data?

Smart home hubs, thermostats, lighting systems, and even coffee makers all collect data on your habits and patterns of usage. Voice-controlled devices actually record what you say to them and then store those recordings in the cloud. This is only to help make the machine smarter — to get to know you better — like your very own digital best friend. While the prospect of all of that personal data about you being out there may seem like a frightening notion, it doesn’t have to be — there are so many ways to use all of this new technology, and to do so safely as well.

Make sure you do your due diligence when buying a “smart” product. Research the manufacturer online to make sure they are reputable and well known. Look at the privacy policy to see how they handle your personal data. Read online reviews of the product in order to spot less than favorable experiences.

The way of the future

According to Gartner,1 machine learning is #1 on the list of the top 10 strategic technology trends for 2018, closely followed by intelligent apps and intelligent things. This just goes to show us these devices aren’t going away any time soon.

This is an exciting time to be alive — although we don’t have flying cars just yet, we do have robots that do the vacuuming for us. Learning about all this new technology can seem daunting, but it doesn’t have to be.

1 https://www.gartner.com/doc/3471559

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