Artificial Intelligence: A Simplified Explainer

Original article was published on Artificial Intelligence on Medium

AI: A Simplified Explainer

Artificial intelligence is everywhere. It’s helping banks make loan decisions and helping doctors diagnose patients, it’s on our cell phones, autocompleting texts, it’s the algorithm recommending YouTube videos to watch after this one! AI already has a pretty huge impact on all of our lives. So people, understandably, have some polarized feelings about it.

Some of us imagine that AI will change the world in positive ways, it could end car accidents because we have self-driving cars, or it could give the elderly great, personalized care. Others worry that AI will lead to constant surveillance by a Big Brother government. Some say that automation will take all our jobs. Or the robots might try to kill us all. But when we interact with AI, that’s available like Siri it’s clear that those are still distant futures. Now to understand where artificial intelligence might be headed, and our role in the AI revolution, we have to understand how we got to where we are today.

Types of AI

If you know about artificial intelligence mostly from movies or books, AI probably seems like this vague label for any machine that can think like a human. Fiction writers like to imagine a more generalized AI, one that can answer any question we might have, and do anything a human can do. But that’s a rigid way to think about AI and it’s not super realistic. Sorry the Bot, you can’t do all that yet.

A machine is said to have artificial intelligence if it can interpret data, potentially learn from the data, and use that knowledge to adapt and achieve specific goals.

Even with this much more limited definition of artificial intelligence, AI still plays a huge role in our everyday lives. There are more obvious uses of AI, like Alexa or Roomba, which is the kind of like the AI from science fiction I guess.

But there are a ton of less obvious examples! When we buy something in an enormous store or online, we have one type of AI deciding which and how many items to stock. And as we scroll through Instagram, a unique type of AI picks ads to show us. AI helps determine how expensive our car insurance is, or whether we get approved for a loan. And AI even affects big life decisions. Like when you submit your college (or job) application AI might screen it before a human even sees it.

The way AI and automation are changing everything, from commerce to jobs, is like the Industrial Revolution in the 18th century. This change is global, some people are excited about it, and others are afraid of it. But either way, we all have the responsibility to understand AI and figure out what role AI will play in our lives.

History of AI

The AI revolution itself isn’t even that old. The term artificial intelligence didn’t even exist a century ago. It was coined in 1956 by a computer scientist named John McCarthy. He used it to name the “Dartmouth Summer Research Project on Artificial Intelligence.” Most people call it the “Dartmouth Conference” for short. Now, this was significantly more than a weekend where you listen to a few talks, and maybe go to a networking dinner. Back in the day, academics just got together to think for a while. The Dartmouth Conference lasted eight weeks and got a bunch of computer scientists, cognitive psychologists, and mathematicians to join forces.

Many of the concepts in AI, like artificial neural networks, were dreamed up and developed during this conference and in the few years that followed. But because these academics were optimistic about artificial intelligence, they may have oversold it a bit. For example, Marvin Minsky was a talented cognitive scientist who was part of the Dartmouth Conference. But he also had some ridiculously wrong predictions about technology, and specifically AI. In 1970, he claimed that in “three to eight years we will have a machine with the general intelligence of an average human being.” And, uh, sorry Marvin. We’re not even close to that now.

Scientists at the Dartmouth Conference seriously underestimated how much data and computing power an AI would need to solve complex, real-world problems. See, artificial intelligence doesn’t really “know” anything when it’s first created, kind of like a human baby. Babies use their senses to perceive the world and their bodies to interact with it, and they learn from the consequences of their actions.

Now, most kinds of artificial intelligence don’t have things like senses, a body, or a brain that can automatically judge a lot of distinct things as a human baby does. Modern AI systems are just programs in machines. So we need to give AI a lot of data. Plus, we have to label the data with whatever information the AI is trying to learn, like whether food tastes good to humans. And then, the AI needs a powerful enough computer to make sense of all the data.

AI Revolution

All of this just wasn’t available in 1956. Back then, an AI might tell the difference between a triangle and a circle, but it definitely couldn’t recognize my face in a photo! So until about 2010, the field was basically frozen in what’s called the AI Winter. Still there were a lot of changes in the last half a century that led us to the AI Revolution.

The AI Revolution didn’t begin with a single event, idea, or invention. We got to where we are today because of lots of small decisions, and two big developments in computing.

Moore’s Law: The Rise of Computing Power

  • The first development was a tremendous increase in computing power and how fast computers could process data.

During the Dartmouth Conference in 1956, the most advanced computer was the IBM 7090. It filled an entire room, stored data on giant cassette tapes, and took instructions using paper punch cards. Every second, the IBM 7090 could do about 200,000 operations. But if you tried to do that, it would take you 55 and a half hours! Assuming you did one operation per second and took no breaks. That was enough computing power to help with the U. S. Air Force’s Ballistic Missile Warning System. But AI needs to do a lot more computations with a lot more data.

The speed of a computer is linked to the number of transistors it has to do operations. Every two years or so since 1956, engineers have doubled the number of transistors that can fit in the same amount of space. So computers have gotten much faster. When the first iPhone was released in 2007, it could do about 400 million operations per second. But ten years later, Apple says the iPhone X’s processor can do about 600 billion operations per second. That’s like having the computing power of over a thousand original iPhones in your pocket. (For all the nerds out there, listen you’re right, it’s not quite that simple — we’re just talking about FLOPS here) And a modern supercomputer which does computational functions as the IBM 7090 did, can do over 30 quadrillion operations per second. To put it another way, a program that would take a modern supercomputer one second to compute would have taken the IBM 7090 4,753 years.

So computers had enough computing power to mimic certain brain functions with artificial intelligence around 2005, and that’s when the AI winter showed signs of thawing. But it doesn’t really matter if you have a powerful computer unless you also have a lot of data for it to munch on.

Web 2.0: The Rise of Social Media

  • The second development that kicked off the AI revolution is something that you’re using right now: the Internet and social media.

In the past 20 years, our world has become much more interconnected. Whether you Livestream from your phone, or just use a credit card, we’re all taking part in the modern world. Every time we upload a photo, click a link, tweet a hashtag, tweet without a hashtag, like a YouTube video, tag a friend on Facebook, argue on Reddit, post on TikTok [R. I. P. Vine], support a Kickstarter campaign, buy snacks on Amazon, call an Uber from a party, and ANYTHING, that generates data. Even when we do something that seems like it’s offline, like applying for a loan to buy a new car or using a passport at the airport those datasets end up in a bigger system.

Guiding the AI Revolution

The AI revolution is happening now because we have this wealth of data and the computing power to make sense of it. That we’re generating a bunch of data but don’t always know how, why, or if it’s being used by computer programs can of overwhelming. But we should learn how artificial intelligence works because it’s affecting our lives in huge ways. And that impact will only continue to grow. With knowledge, we can make small decisions that will help guide the AI revolution, instead of feeling like we’re riding a rollercoaster we didn’t sign up for. We’re creating the future of artificial intelligence together, every single day. Which I think is cool.