What do we actually mean when we call something "AI"?

The term Artificial Intelligence was coined by John McCarthy and since then it has become one of the most widely used terms in technology. Today, almost everything related to automation, prediction, generation or recognition is being called AI. It has also become a very common marketing term, where companies use "AI" to make their products look more advanced or intelligent.

But what actually is AI?

Emily Bender and other researchers used the term "Stochastic Parrot" to describe large language models. The basic idea is that these systems are stochastic models which learn from huge amounts of data and predict what word, token, character or piece of information is likely to come next. The systems are extremely complex, but at the same time the basic principle is still based on probabilities and patterns learned from data.

In a way, AI can also be seen as a container for many different things. It can contain text, symbols, pictures, speech and other types of information, as well as generative and recognition systems. We use the same word "AI" for many completely different systems.

The output of these systems is defined by statistics and algorithms. This brings up one of the biggest questions in this whole discussion: is there actually intelligence in these systems, or are we simply interpreting the output as intelligence because it looks intelligent to us?

This is where anthropomorphising becomes important. Anthropomorphising means giving human traits, emotions, behaviours or intentions to something that is not human. With AI, we often say things like "the AI wants to help", "the AI understands me", "the AI decided this" or "the AI knows what I mean". But does the system actually have an intention, or are we just giving it one because it communicates with us in a human-like way?

This can create a misconception that the system itself has intentions, feelings or understanding when it may simply be producing an output based on patterns and probabilities.