What is Artificial Intelligence?

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Let's Talk Science
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Learn about the fast-moving field of artificial intelligence and what it means in your life.

To be able to define artificial intelligence, or AI, you need to first define what intelligence is. You might think that it means being smart. But intelligence is far more than doing well on tests. 

Intelligence is complicated. Scientists who study intelligence still have many questions to answer. Are animals intelligent? How are imagination and memory linked to intelligence? Does the size of your brain have anything to do with your intelligence?

There are many different definitions of AI out there. In general they include the idea that AI is about the theory and development of computer systems that can do tasks that normally require human intelligence. These include things like recognizing images and speech and making decisions.

This backgrounder will help you understand more about AI.

General and Narrow Artificial Intelligence

There are two main kinds of artificial intelligence. We call these Artificial General Intelligence and Artificial Narrow Intelligence. It is important to understand the difference between the two.

Artificial General Intelligence

The goal of Artificial General Intelligence (AGI) is to be equal to human intelligence. Many robotic engineers have managed to create human-like robots. But those robots don’t have intelligence equal to humans yet. 

AGI is what you usually see in books and movies that take place in a dystopian future. Some examples of this are the Terminator and the Matrix movies. It is not quite AGI, but rather superintelligence. Superintelligence is the idea that machines could someday be smarter than humans. But many experts think it is not a threat we should worry about anytime soon. 

To develop AGI, scientists look at what we know about human intelligence. They try to understand things like how we learn, or how creativity works. To do this they use things like digital models to copy human behaviours. Brain research can also help AI developers and vice versa. AGI can help brain researchers understand the brain better!

Artificial Narrow Intelligence

Artificial Narrow intelligence (ANI) is AI we can experience right now. Sometimes this is also called weak AI. This type of AI lets machines perform actions and make decisions in limited situations. Self-driving cars and virtual assistants are examples of narrow ANI.

AI at the grocery store
People using AI for personalized shopping recommendations and to pay for products (Source: elenabs via iStockphoto).

A Brief History of Artificial intelligence

The term “artificial intelligence” was first used in 1955. Then they thought that general AI would be possible in a few years. But the technology needed to research AI was not ready. 

Here are just a few of the major milestones in artificial intelligence:

AI timeline
AI timeline (Let’s Talk Science using image by Visual Generation via iStockphoto).
  • 1943: A model for an artificial neuron based on human neurons is created. 
  • 1950: Computer scientist Alan Turing creates a test for machine intelligence. He called it “the imitation game.” It is now known as the “Turing Test.”
  • 1956: The phrase Artificial Intelligence was first published by computer scientists.
  • 1957: Frank Rosenblatt invents the perceptron. It is the first computer neural network based on the human brain.
  • 1964: The first chatbot, Eliza, holds conversations with humans. 
  • 1970s-1980s: 'AI Winter', a period where research mostly stopped
  • 1973: The Canadian Society for Computational Studies of Intelligence is founded. This is now called the Canadian Artificial Intelligence Association. It is located at Western University.
  • 1995: AltaVista is the first search engine to use natural language processing.
  • 1997: IBM's Deep Blue is the first computer to beat a chess champion. It defeats Russian grandmaster Garry Kasparov.
  • 1999: Sony launches a robot pet dog named AiBO. It’s skills and personality develop over time. 
  • 2002: iRobot launches the Roomba® floor-vacuuming robot.
  • 2011: Apple integrates Siri, an intelligent virtual assistant, into the iPhone 4S
  • 2011: IBM's Watson computer wins at the TV game show Jeopardy. This proved it could understand complex human language, because questions included word play.
  • 2014: Some experts think computer "chatbot" Eugene Goostman has passed the Turing Test.
  • 2014: Google's self-driving car passes the Nevada state self-driving car test.
  • 2017: Creation of the Pan-Canadian Artificial Intelligence Strategy, a first in the world. 

Humans and Computers working together

“Human in the loop” AI is a way to combine the strengths of computers and humans. A computer's strength is its computing speed. Humans will never be able to do calculations as fast as computers. Human strengths include creativity and critical thinking. Humans have the ability to look at a problem from different points of view. 

This means humans have many important roles besides building AI tools. For example, a human engineer can take part in testing an airplane’s safety mechanism. People responsible for hiring can make sure AI hiring tools are fair. And medical experts can help make sure an AI tool is accurate for all patients

Artificial Intelligence Opportunities

AI is a great tool. It can help us find solutions to many problems. This is true in any area where we use data, which is almost everywhere!

AI opportunities
AI has potential for many opportunities including those in healthcare, disaster relief and refugee (Source: Visual Generation via iStockphoto).

In medicine, AI is being used in research. It can help researchers fight cancer or search for vaccinesSome doctors use AI diagnostic tools to help identify illnesses faster. In agriculture, AI can help farmers detect pests and diseases in plants. It can also help to reduce food waste

AI can provide much-needed tools to help us protect the environment. AI can use satellite images and data to help scientists predict what might happen. For example, AI can be used to identify where forest fires could happen, before they start. We can also use AI to predict other natural disasters. It can even be used to understand and protect endangered species as well as protect ecosystems from invasive species.

Did you know?

In 2018, Canadian researchers won the AM Turing Award. It is like the "Nobel Prize of Computing". This has led to the creation of many AI research centers across Canada. And many people now consider Canada the place to be for AI development.

Artificial Intelligence Concerns

Should we be afraid that artificial intelligence might develop beyond human intelligence? Or that it could become a threat to humans? Experts have been debating these issues for a long time. Some people only see AI’s potential for innovation and problem-solving. Others, like Elon Musk and Bill Gates, think that AI could be dangerous. They think humans should be very careful about how they develop and use it. That’s why governments are now working to create regulations for AI. These rules will make sure people develop AI applications with human well-being first.

Jobs

AI is already changing the job market. Robots controlled by AI are doing many things that humans used to do. And people are beginning to worry that they will be replaced by machines. During the industrial revolution, people worried about the same thing. 

Some experts predict that AI will make some jobs obsolete, but it will also create more jobs. Some of them call this the fourth industrial revolution. This change will mainly affect jobs that involve manual labour. But it will also affect office jobs where people make routine decisions. We can automate these tasks with AI systems.

Robotic systems
Robots using AI will do tasks instead of, as well as with, humans (Source: Visual Generation via iStockphoto).

Fairness

AI can solve many problems, but it can also create problems. AI is developing so quickly that some problems are only discovered when a technology is already in use. Like with all new technologies, we can’t always predict how it can go wrong. This is why it’s important for more people to better understand how AI works. 

We also need people to follow situations closely when new AI tools are used. This is particularly important as AI is used more and more in areas where it affects people’s lives directly. This is the case for uses in justice, medicine and banking systems. For example, a set of medical data needs to represent the characteristics of a population. These include things like age, gender and ethnicity. If it does not, then this data cannot be used to make predictions for the whole population. It is important that the tools used don’t create or increase existing inequalities. Experts are already working on this problem. It is also important that people of all backgrounds have access to education in the AI domains. This will help to make sure diversity is better addressed in the future.

In conclusion...

The field of AI is especially important for young people. Its impact on your lives will only increase. But becoming more familiar with AI does not have to mean taking computer science classes. You can learn about AI in many different ways. 

To make sure you prepare for a future with AI, we encourage you to learn more about where AI applications exist. You can start by reading more of our backgrounders on this topic, in the Learn More section.

We may not know exactly what the future holds, but we can be pretty sure that AI will play an important role. And many scientists in Canada are working hard to figure out how humans and machines can build a better world together. Will you join them?

 

Learn More

What is Machine Learning? 

This backgrounder from Let’s Talk Science explains how computers can learn through three different types of machine learning. 

AI and Personal Vehicles

This backgrounder from Let’s Talk Science explains how artificial intelligence is integrated into the vehicles that we drive. 

AI and Human-Computer Communication

This backgrounder from Let’s Talk Science explains how artificial intelligence and machine learning help us communicate with computers. 

AI and Computer Vision

This backgrounder from Let’s Talk Science explains how computers see and learn to recognize objects and human faces. 

What The Kids’ Game “Telephone” Taught Microsoft About Biased AI (2017)

This article by Fast Company illustrates the five types of bias that can be found in machine learning applications.

Myths and Facts About Superintelligent AI (2017)

This video from minutephysics (4:13 min.) discusses common misconceptions and true facts about superintelligence.

The Turing test: Can a computer pass for a human? (2016)

This video by TED-Ed (4:42 min.) explains how the Turing Test was used to evaluate if computers have human-equivalent intelligence.

How Snapchat's filters work (2016)

This video by Vox (5:07 min.) explains how visual recognition works, including Snapchat's filters.

References

Chui, M., Chung, R. and van Heteren A. (2019, January 21) Using AI to help achieve Sustainable Development Goals. United Nations Development Program.

Granville, V. (2017, January 2) Difference between Machine Learning, Data Science, AI, Deep Learning, and Statistics. Data Science Central.

Hello Future. How AI can help reduce inequalities (2019) 

Maini, V. (2017, August 19) Machine Learning for Humans. Medium.com

Stark, L. and Zenon W. Pylyshyn. (2020, March 10). Artificial Intelligence (AI) in Canada. The Canadian Encyclopedia.

Timelines Wiki. Timeline of machine learning. (2020).

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