Artificial Intelligence

Artificial Intelligence (AI) is a branch of computer science that involves creating intelligent machines that can perform tasks that –used to– require human intelligence to accomplish. It is a field that encompasses several subfields, including: machine learning, natural language processing, computer vision, and robotics. It is a way to make machines work smarter and more efficiently –like a robot brain that can think, learn, and solve problems all on its own. The ultimate goal of AI is to create machines that can perform complex tasks accurately, and autonomously (without the need for human intervention).

How Long Has Artificial Intelligence Been Around?

AI isn’t new. It existed long before ChatGPT started writing our college papers for us. Bringing together the functions of organic beings and machines truly started in the 1950s (as soon as computers could store information). Today, artificial intelligence is woven into the fabric of our lives.

Everyday Examples of Artificial Intelligence

Artificial Intelligence and Machine Learning systems permeate every industry and are fueling important features in myriads of software products. Here are a few examples of AI systems that you may interact with in your everyday life:

• Facial Recognition: every time you unlock your phone with your face.
• Recommender Systems: when Netflix recommends your next show or when Amazon recommends something to add to your cart.
• Self Driving Cars: Tesla, Waymo, Uber, Cruise, etc. Even features like self-parking, lane-assist, adaptive cruise control, etc. are likely using machine learning to keep you safe.
• Siri and Alexa: partly voice-to-text transcription plus other software that responds to the transcribed text.
• Email Spam Filters: no, they're not perfect, but they're pretty good –even though spammers are continually evolving their tactics.
• Fraud Detection: you know, when your bank calls you because they see a funny credit card transaction? That, but not only for credit cards.
• Optical Character Recognition: your phone can read text in pictures you've taken now. Huge companies exist just to digitize historical documents and make them available online.
• Predictive Text: autocorrect on your phone is one example, even though you don't say "duck" as often as it thinks you do.
• Healthcare Diagnosis: diagnosing diseases, reading x-rays, analyzing your blood work, processing electronic medical records, drug discovery, etc. –AI is all over in healthcare.
• Customer Support Chatbots: are not all created equal.
• Language Translation: Is getting very good lately. Google Translate is so much smarter than it was 10 years ago.

This list could go on and on, but you get the idea. It's everywhere.

Subsets of Artificial Intelligence:

Machine Learning

Machine learning involves creating algorithms that can learn from data and make predictions or decisions based on that data. Early machine learning scientists were interested in teaching machines to imitate the way humans learn. Today, machine learning algorithms are trained on large datasets and can identify patterns and relationships that would be difficult or impossible for a human to identify. These algorithms can then be used to make predictions or decisions in new situations based on what they have learned from the data. An example might be an algorithm that studies the patterns of your purchases over time and alerts your bank about possible fraud when it sees something unusual in your spending patterns.

Natural Language Processing

Natural language processing is the field of Artificial Intelligence that deals with the interaction between computers and humans using natural language. This includes tasks such as speech recognition, language translation, and sentiment analysis. Natural language processing has applications in many areas, such as customer service, language learning, hiring processes, and predictive text. Your email spam filter is a great example of how natural language processing works to benefit you. The model looks for common words and phrases used in other spammy emails to flag emails in your inbox to identify them and remove them, saving you lots of time and annoyance. When you ask Alexa to turn on a timer, or your kids drive you crazy asking Siri to tell them knock-knock jokes, that is natural language processing hard at work.

Computer Vision

Computer vision is a subfield of artificial intelligence that involves creating algorithms that can analyze and interpret visual data, such as images and videos. Computer vision has applications from healthcare to manufacturing. Facial recognition is one example of computer vision. The photos app on your phone can pick out all of your photos of Uncle George, even if he’s wearing a sombrero. Computer vision has identified different data points as it has mapped out his face: the distance between his eyes, the shape of his upper lip, and more. Now, any time that combination of data points exists in a photo, facial recognition software knows this is a photo of Uncle George. Self-driving cars depend on computer vision to understand the difference between a stop sign and a yield sign (something humans still kind of have trouble with).

Robotics

Of course, robotics is also a great example of artificial intelligence, and it is an area that has fascinated humans since the dawn of the space age. The advantages of having a machine take over your most mind-numbing, boring tasks (like writing college papers) and do them autonomously has obvious advantages. Robotics integrates various AI technologies, such as machine learning and computer vision, into physical machines that can perform tasks like assembling cars, exploring space, or making a sandwich for you.

Risks Versus Rewards

AI has the potential to transform nearly aspect of human life in the coming decades. While there are concerns about negative unintended consequences, including artificial intelligence eliminating paid jobs for human beings, as well as concerns over privacy, data scientists are working to mitigate these problems. Social and ethical considerations will become more and more important as the use of artificial intelligence becomes more widespread.