What is a chatbot?
A chatbot is a computer program designed to stimulate human conversation over the Internet. The ultimate aim of the chatbot initiative is to create a single program which would be completely indistinguishable from a human in conversation over the internet. Of course, such a huge goal is not easily achieved. After huge organizations trained a number of models on a large amount of data like Google, Amazon(Alexa) , these models were also unable to pass the Turing test which indicates scope for further development in this region.
What is the Turing Test?
Alan Turing had been a mathematician in the 1950s and is widely regarded as the father of computer. He published a paper in the 1950’s as a possible solution to the question, can machines think? In the said paper he brought points together to highlight the need for a Turing Test, a method wherein a human and a machine separated by a wall are brought to engage in conversation and if the human is unable to distinguish the fact that a machine lies on the other side of the conversation marks a successful instance of such a test for the machine.
However, since the publication of his ideas and the actual realization of the ability to make machines “think” has raised several questions. One of the more important ones being if the Turing Test is still valid considering the change in the field of machines and computers since Turing’s time. As of this date , no current machine learning model has been able to pass the Turing Test satisfactorily.
How does a chatbot work?
A chatbot works like a normal application with a backend database. Current chatbots understand human language by processing the words given to it into numerical strings which are then fed into a machine which learns from the numbers to respond to that question when faced with it again with an appropriate response. However, chatbots currently are unable to determine the intent behind a human conversation and are currently used in places where the response to be given and input to be taken can be roughly predicted to allow for better accuracy from the chatbot.
Chatbots are driven by automated rules, AI and NLP to deliver responses to different kinds of requests. Considering the intent constrained mentioned above a lot of chatbots are task -oriented. They are used for a specific task in a business which have a pretty basic need for customer support.
Data Driven chatbots are digital assistants in that they are more complicated and sophisticated than the task oriented version. They are also able to understand context and eventually learn from everyday patterns and behaviours to best suit the user .
Training a task oriented chatbot like a customer service bot is pretty straightforward. The chatbot would need logs of certain pre determined reponses to certain questions , and a log of previous such conversations. The chatbot model now learns on the data given to it and uses different mathematical techniques to determine which response to give.
Data driven chatbots are more personable and require a lot more intricate training wherein each section of the conversation would be able to consistently teach the machine about the habits it observes and learn to anticipate the habits in the future. Such self learning models are few in number all over the world and require a large amount of data from all relevant fields to train upon rather than a fixed size corpra on customer interaction.
Applications of Chatbots
Chatbots are frequently used in the IT industry to automate small tasks in the industry like password resets , company policy updates etc
On the service side they are used as an interface to guide the necessary users to the correct resource without having to go through a human representative on the other end of the phone enabling the chatbots to cater to multiple users at the same time , each with varied requests and action updates.
Chatbots on other platforms allow for the option to buy passes ,even the movie theatre has one to interact with in order to buy your tickets! .Each of these are examples of chatbots as used by consumers in their day to day life.
Living in the digital age we interact with more data on a daily basis as time passes on , further research into deciphering this data would allow for creation of better lifelike chatbots which may just be able to pass the Turing Test and which may finally be able to “think” on its own.