If there is a question that keeps popping up again and again amongst our clients, it is: what is Artificial Intelligence (AI)? Depending on who you ask you will get a different answer. The reason is simple, AI has its roots from multiple sources, including the scientific community, popular culture, and even geography plays a role. If you ask the scientific community in the USA you might get that AI was invented by the military (DARPA) in the 1950’s. Work in emulating human neurons dates back even further. Either way our modern western understanding of what is AI has been heavily influenced by popular culture such as Hal in 2001 Space Odyssey (60’s), Skynet in Terminator (80’s), and more recently from modern TV series such as A.L.I.E. from The 100 (Netflix). On the other hand cultures in Asia have had a different starting point for defining what is AI. For example in Japan there is a culture/folklore surrounding “Tsukumogami” where inanimate objects may possess souls. Even a rock may be considered to be intelligent. This has led to a different understanding of AI and a much broader acceptance of things as intelligent.
In Western culture we have devised scientific methods such as the famous Turing test which seeks to determine if a system exhibits intelligent behaviour under the idea that if it looks and acts intelligently, then it might as well be intelligent. Are there then any rules on when something can or cannot be an AI? One of the big recent notions has been data-based intelligence, popularized by artificial neural networks where millions of neurons are trained to perform intelligent functions. Earlier work saw the use of layered rule-based systems (subsumption architectures) where even simple interations of rules (E.g. if-then-else) gave rise to complicated interations. Recently, the notion of hiveminds where crowd-sourcing is used for decision-making, ideation, etc can probably also be called AI even though in the end it relies on real human brains.
This gives rise to another question, how intelligent does a system or object need to be to be called an AI? Hiveminds have been shown to provide super-human level intelligence, likewise many deep learning systems show super-human performance in highly specific operations like image recognition. On the other hand most people will quickly point out that modern AI’s like Amazon Alexa and Microsoft Cortana are pretty dumb (most were also built around rule-based systems). The answer is that AI’s probably do not need to be very smart if they attempt to mimic human behaviour.
Moving on to the scientific community, you will see throughout the internet Venn diagrams and Onion diagrams where Artificial Intelligence is tried to be described in terms of being an umbrella for machine learning tools (deep learning, optimization), or in terms of applications (expert systems, robotics, etc) or as a subset of various fields (like psychology, mathematics, etc). Especially the tools part has been a bit difficult and boils down to what should an AI be able to do to be called an AI? Most AI systems today do not learn anything on-the-fly. They are in essence “programmed” once and then can only do that one thing. Experts are then needed to “reprogram” (AKA train) for new tasks). So systems that can more quickly learn and do it on-the-fly are clearly the next step for AI’s. Current research in reinforcement learning and transfer learning are two such areas that seek to alleviate this obvious short-coming.
We hope this helped you get a better understanding of what AI is and inspired you to learn more.
// Sensomind Team