Let’s imagine two near-identical scenarios. In both scenarios you go online to a service provider – for example, a utility company – open up a live chat service, ask a question, and receive an answer. Both cases take exactly the same amount of time and give exactly the same information. The only difference is that in the first case (call it Case A) you were talking to a person, while in Case B you were interacting with an artificially intelligent chatbot.
The question is, does it make any difference?
The Turing Test
The Turing test is one of the most famous thought experiments in philosophy. In fact, it is one of the most referenced papers in academia. The pioneering computer scientist, Alan Turing, posed a simple test called the Imitation Game. (His life was dramatised in the multi-award winning biopic The Imitation Game) In this test, there are 3 subjects. We will call them Alice, Bernard, and Charlie. Alice cannot see either of the other two, so must ask questions to both Bernard and Charlie via written notes which are passed through the door to two separate rooms. Both Bernard and Charlie must answer these questions, and then write out their responses, giving them back to Alice. However, there is a twist: either Bernard or Charlie may in fact be an artificially intelligent computer that is communicating to Alice through a human. It is up to Alice to try to figure out which, if any, of the other subjects is actually a non-human. The purpose of this is to answer a fundamental question ‘Can computers think?’. However, Turing recognised that this was a fairly impossible question because we can never agree on what it means to ‘think’ in any meaningful way. Instead, the Imitation Game example seeks to answer the more simple question ‘Are there imaginable digital computers which would do well in the imitation game?’ Turing thought that there were, and he has been proved right if perhaps a little optimistic. In 1950 he wrote, “I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted.” The key to Turing’s test is that it does not disadvantage the computer by its inability to “win a beauty pageant”, or the human by their inability to perform quick mathematics. Instead it is a judgement on the ability for a computer to appear indistinguishable from a human. This is mostly discussed in terms of linguistics, but can be applied to AI of almost any function.
We are now nearing the age that Turing imagined, where machines could be made indistinguishable from humans, and we can run our own Turing Test on AI to find out how well they can mimic human behaviour. Many chatbots have a whole range of responses programmed into them that seem irrelevant to their function, but ultimately these are often a way of trying to prevent a human being fully aware that they are talking to a bot. Alternatively some bots are programmed to make light of the fact that they are bots, for example, Siri will make jokes, or explicitly reference that it is a bot, whereas some AI chatbots will try and hide it.
Computers are very good at fulfilling highly specific tasks, and so there are some tasks where it can be naturally difficult to know whether you are interacting with a bot or a human. Chess master Gary Kasparov claimed that IBM’s Deep Blue, a computer designed to beat him at chess, showed ‘elements of deep intelligence and creativity’. This suggested that humans were actually manipulating the play of the computer, rather than using existing code. While an expert like Kasparov might be able to identify subtleties in chess-playing, most of us are not sufficiently knowledgeable to subject a chess computer to a Turing test. On the other hand, almost all humans are experts in language. We’re extremely skilled in interpreting language and understanding phrases even when there are errors in the formulation of a sentence, (syntactic) or in word choice (semantic). Computers are currently far less good at this, and it takes a lot of time and money to get them up to scratch. The Loebner Prize, awarded to the most convincing chatbot, uses a series of questions to assess the ability of a bot to replicate human function. What is interesting is that many of the questions it asks are very easy for humans to understand and respond to, but extremely difficult for bots. This can range to something as simple as “How many letters are in the word ‘abracadabra’” or “If a chicken roosts with a fox they may be eaten. What may be eaten?”. As bots continue to use machine learning to fine-tune their responses this will undoubtedly improve, but it is a good demonstration of the current limitations of the technology.
AI Customer Service Chatbots and User Experience
When it comes to customer service there is a question about what service we want to receive. From a user’s perspective we want to get the most salient information, as quickly as possible, so that we can solve whatever problem we had and get on with the rest of our day. We all know how annoying it can be to be stuck on hold listening to a tinny rendition of Bach! However, when it comes to AI chatbots there seems to be a certain squeamishness about using them that goes deeper than any faults they might currently have. Going back to our original problem of Case A and Case B, some people might still say that it does matter if one of them is a bot and one a human, even if you cannot tell the difference. Part of this may be that they want an authentic ‘human’ experience, which they feel a bot cannot deliver. Even when AI technology is perfectly capable of replicating human interaction with things like jokes and dialect matching, some people still prefer to talk to a human. Another reason for that some people are anxious about the roll-out of AI is that they might feel they cannot be sure who they are talking to. This is especially true of cases where we might be asked to hand over sensitive information and data, and as customers it is important that we know who we are talking to. Customers tend to be cautious, particularly with new and unfamiliar technology, so many people will need to be given peace of mind when it comes to being sure that a bot they are talking to is secure.
Should customer service chatbots appear human?