The term artificial intelligence refers to computer programs that mimic human behavior and decision-making. It encompasses a wide range of technologies, including traditional AI that uses programmed rules and algorithms to analyze data and make predictions or decisions, as well as machine learning that allows software to learn from past experience without explicit programming. The field also includes generative AI, which creates new content like text, images, music and video, and speech recognition and generation. While AI is often associated with sentient robots such as Star Trek’s Data or Terminator’s T-800, most of the AI that exists today is much more modest and serves a variety of functions.
The invention of programmable computers in the 1940s sparked imaginations about creating intelligent machines. In 1950, Alan Turing proposed the “Turing Test,” a way to determine if a machine could exhibit intelligence indistinguishable from a human’s. John McCarthy coined the term artificial intelligence in 1956 at the first-ever AI conference, and in 1957, Frank Rosenblatt built the Perceptron, the world’s first neural network.
Over the next 50 years, AI became increasingly ubiquitous in our daily lives — from customer service chatbots and document validation to accelerating drug discovery and optimizing supply chains. It’s now helping professionals save time by automating mundane tasks, freeing them up to tackle more challenging projects. In health care, it’s revolutionizing diagnostics and treatment by detecting patterns that humans cannot. In entertainment, generative AI is used to compose music and create stunning visual art. And in the workforce, AI-powered robots are taking on dangerous, repetitive and tedious jobs, keeping employees safe and increasing productivity. But with such power comes the need for increased scrutiny and regulation.