In 1956, Professor John McCarthy and colleagues coined the term “artificial intelligence” – AI – as “the science and engineering of making intelligent machines.” They were describing machines that can think like people and replicate human intelligence by learning and problem-solving.
AI uses symbolic reasoning and substantial computing power to make predictions, recommendations, and decisions. It has many applications and the potential to transform our lives. Examples of everyday AI include wearable fitness trackers, chatbots, spam filters, playlists, and facial recognition systems.
Machine Learning is a subfield of AI that enables computers to learn without being explicitly programmed. These computers learn directly from data, consuming vast amounts of information and logic.
Deep Learning is an advanced form of Machine Learning that uses Artificial Neural Networks. These networks are modeled on the structure of the human brain and identify the relationships between words and phrases in huge amounts of data. Deep Learning has produced technical breakthroughs in fields such as medical imaging and weather-forecasting.
Generative AI is an evolved form of Deep Learning. This type of AI uses more elaborate neural networks called Large Language Models to examine even greater amounts of data and perform complex tasks. Using Generative AI, computers can create new text, data, images, and video. This can, arguably, make it easier for us to do things such as write, learn, and create.
Some people believe that AI will transform the economy. Others believe it will reshape society. But many people are unaware of how AI is already used in everyday life. Given the enormous – and largely unknown – implications of AI for society and the planet, we’d be wise to examine the many ethical concerns the creation and application of AI raises.