The concept of AI, or an 'artificially intelligent' being, can be traced back to long before the first true computer. In the oldest known work of human literature, the Epic of Gilgamesh, a major recurring character was Enkidu - an artificial human crafted by the gods as a rival for the protagonist. This idea occurred again in Jewish folklore with the Golem - anthropomorphic beings crafted from mud and clay to resemble a human being but lacking a soul.
In our article on the 3 Types of AI
, we explain artificial intelligence is a branch of computer science which endeavours to replicate or simulate human intelligence in a machine, so machines can perform tasks which typically require human intelligence. Some programmable functions of AI systems include planning, learning, reasoning, problem solving, and decision making.
We categorise AI technologies
in several ways, including its capacity to mimic human characteristics, the technologies enabling human characteristics to be mimicked, real-world applications of these systems, and theories of the mind.
In this article we will discuss the extensive history of artificial intelligence.
Artificial intelligence was an idea explored heavily throughout the 20th Century, seen through the creation of pop culture icons such as the 'Tin Man' from the Wizard of Oz
, and the research conducted by scientists and mathematicians in the 1950's, who were familiarising themselves with the overall notion of artificial intelligence.
Around this time, a British computer scientist by the name of Alan Turing was exploring the concept of artificial intelligence and the mathematics behind it. Famously, in World War II he, along with his team, cracked the Enigma code
which was used by German forces to send secure messages. They did this through the creation of the Bombe Machine
, which laid the foundations for what we know today as machine learning.
Turing's end goal was to create a machine that could interact with humans without their knowledge; resulting in them winning the 'imitation game'. He wrote about this in a paper called Computing Machinery and Intelligence
, exploring the notion that if humans can draw on information and reason to solve problems and make decisions, why can't machines? This led him to explore the concept of building intelligent machines, and theories on how to test their intelligence and capabilities of thinking like a human being; a test that would come to be known as the Turing test
Now, although this concept was promising, Alan Turing hit a roadblock in the actual implementation of building and testing intelligent machines; as computers were largely unsophisticated, unable to store commands, and were also extraordinarily expensive to lease. As the theory of AI was so new, funding was unattainable without a proof of concept and backing from higher profile professionals. This leads us to the year 1955, when the term 'artificial intelligence' was officially coined for the Dartmouth College Artificial Intelligence Conference, held in the summer of 1956.
The first 'AI Winter' occurred for a very simple reason - computers were just not powerful enough yet to store the information needed to communicate intelligently, Hans Moravec, an MIT doctoral student of John McCarthy stated,
"...computers were still millions of times too weak to exhibit intelligence."
In the 1980's however, AI saw a resurgence as the British began funding the field again to compete with Japanese advancements in AI. These advancements included the Fifth Generation Computer Project
(FGCP), as well as developments being made to the tools and techniques in algorithmic design. During this time, major advances were also made in deep learning methods, which essentially authorised computers to use experience to learn. However, this reignition of the field was short-lived, and in 1987 to 1993 the second AI winter took place due to lack of funding and the market collapse of early model, general purpose computers. This lull eventually ended in the late 90's, with a shift that changed human and computer relationships forever.
Today, we are seeing constant development in the field of AI as computer systems become more advanced and 'intelligent'. Tech giants such as Google and Amazon, have been utilising machine learning to make constant advancements; processing thousands of terabytes of data on a daily basis to build predictive models of consumer behaviour, while simultaneously devoting immense resources to advancing AI as an academic field - with a particular focus on computer vision and natural language processing. From 2018, most universities have offered undergraduate coursework in artificial intelligence, and enrolments have consistently doubled year-on-year.
Advances in artificial intelligence show no signs of slowing down - the world is changing rapidly, and as we move even further into an era dominated by artificially intelligent technology, the more important the idea of bots and humans working side by side becomes.