Businesses will have different goals when it comes to their use of artificial intelligence, which is why there are a range of AI training courses which will inform users of the capabilities and limitations of existing AI tools and what is possible in the future.
However, for many companies, the primary use of an AI tool will be as part of a robust customer service system, with a chatbot simulating a conversation with an end user.
The advantage for the customer is that they get the tailored experience they would receive from a human operator, whilst a business would save money by limiting their dedicated customer service staff, ensuring that everyone they employ is working for the proactive betterment of a business.
The principle behind chatbots is based on a technological concept known as the Turing test, which tests a chatbot or other form of AI communication tool to see if it is indistinguishable from a human.
The test itself, which creator Alan Turing described as the “imitation game”, is not meant to answer the question of whether AI systems have the capability to think, but whether they can answer in a way that is indistinguishable from a human being.
There are various types of Turing tests, but there are two classic versions that were used for decades to test early and somewhat rudimentary AI systems.
The first was based on a party game, where a human and a computer are asked questions by a human judge, who then has to guess which response was provided by the computer.
An alternative test has a judge converse with either a human or a computer system for a given length of time and has to guess which is which.
It is ultimately focused on the outcomes, as what matters for a chatbot is not necessarily whether it can actually think and have a conscious mind but whether it can behave as if it has one and provide answers useful and sensitive to a customer using the system.
