Let’s be clear once and for all what AI really is and what it stands for. After reading one misrepresentation after another, let us be clear about where the line between machine learning and other buzzwords starts and where it ends.

A.I. has become such a buzzword, it seems almost every business is engaged with it, or is wants to be in the near future, without completely understanding what it is. Companies are even approaching consultants and tech companies stating they want A.I. without having a clear vision as to what it is supposed to do. After interviewing an intern at Microsoft and MSc student in Artificial Intelligence, even she stated she believes it has become an enormous hype. She continues “People tend to forget it is still statistics and math models, it is not a magic answer to any problem. Everything would still need to be build and programmed.”

Even so, all large companies seem to be investing and experimenting with it, hoping to be the new leader in the market. Hereby, they seem to fuel that new trend and bubble called A.I. One must note however, this works in their favour. A study conducted in 2015 by Jurriaan Nijholt et al. concludes “that even without needing to adopt the practice, merely using buzzwords that are in fashion can lead to companies being overvalued.” Even though they focused on buzzwords such as big data and outsourcing, one can expect this to apply to A.I. as well. So once and for all, lets define the buzzword and try to take away the “buzz” around it.

As one of the founding researchers and professors on A.I. has defined it, “Artificial Intelligence is that activity devoted to making machines intelligent and intelligence is that quality that enables an entity to function appropriately and with foresight of its environment.” This differs from machine learning in a sense that machine learning is a type of A.I. focused solely on enabling computers to use observed data to evolve new behaviours that have not been explicitly programmed. Thus, shortly stated, A.I. consists of unprompted information and mimicking human thinking, whereas machine learning focuses more on prompted information. This concept is further clarified in the picture shown.

Thus, A.I. is not the answer to everything. It does however contain the newest technology and provides many opportunities. By encompassing machine learning and data science, A.I. will have a significant effect on the future, but if it is significant progress or a bubble burst, we will have to wait and see.