How Does a Chatbot Learn?
You browse a website for any of your online transaction or service needs, then all of sudden you see a screen popup with a message like this, “Hi, how may I help you?” so you type in your concerns and within seconds you receive a convenient non-traditional customer service which guides you through your transactions. This is a simple example of a chatbot in service, but how is this possible?
In this article, I will break down,
•What a chatbot is and the technology behind chatbots
•What is the learning process of this A. I (Artificial Intelligence)
•The different types of chatbots available
• The significance of knowing the learning process of chatbots
•The benefits of having chatbots- for website owners or any service providers
Chatbot, the juxtaposition of ‘chat’ and ‘robot’ is simply what it means robots-computerized machines that converse with you. It is a computer science technology that has become a rapidly rising phenomenon in this complex world of Artificial Intelligence and it doesn’t seem like it’s going to slow down any time soon.
It has been an effective alternative and substitutes to the traditional customer services and other platforms that used to utilize humans as virtual assistants.
Table of contents
⦿ What is a chatbot?
⦿ Brief history recap on development of chatbots
⦿ How does a chatbot learn?
i. Chatbot Architecture
ii. Types of chatbots
iii. The learning processes
⦿ Chatbot Applications
⦿ Significance and benefits of chatbots
What is a chatbot?
To use a more technical language, chatbots are software agents that serve as natural language user interfaces for data and service providers (‘The Return of the Chatbots’, Dale, R, 2016). Simply put, a chatbot is an artificial intelligence (AI) program that can simulate human conversations and interactions, it mimics through a learning process that facilitates the aspect of replicating human interaction with data.
Chatbots do that by utilizing the cutting-edge computer science technology of natural language processing, machine learning, and other sophisticated programs which I will discuss furthermore in this article.
In addition, as you analyze the various roles and functions of the chatbots, you will come to realize that chatbots are basically simulations that can understand and process human language, then respond and interact with humans while simultaneously performing a specific allocated task.
Brief History recap on the development of chatbots?
The history of chatbots dates as back as half a century ago in 1966, when the first chatbot ever was created by Joseph Weizenbaum, who named it “Eliza”. However, even way before Eliza was created, the idea of creating machines that can think and process information like humans already existed.
It was Alan Turing who asked the famous question “Can machines think like Humans?”, later on, the Turing test was developed to basically screen machines whether or not they possess the ability to mimic an indistinguishable intelligent behavior of a human. Since Eliza, the world of chatbots has been developing very rapidly, so has the technology behind chatbots and AI becoming more advanced and complex.
Today a google chatbot could call a restaurant and make a booking for you. There was a time when you can ask Apple’s Siri (chatbot) to tell you only what time was, today you can ask her to guess what music is playing at the background or even ask her what she thinks about a certain photo.
A brief timeline of notable chatbots:
• 1996- Eliza
• 2001- Smarter Child
• 2010- Siri
• 2012- Google Now
How does a chatbot learn?
i. Chatbot Architecture
In the attempt to try being less technical, this is basically an overview of the structure of the chatbot learning process and interactions. Regardless of the different types of chatbots, this shows the common elements involved in the flow of information and data utilized in the process of a functioning chatbot. Obviously, Siri works differently from Amazon’s Alexa and both differ from Microsoft’s Cortana, however here is just a “birds-eye view” of how a chatbot functions.
○ Chat window- The section where the interaction is going on, opening a browser, or talking with google on your phone, are all examples of sessions and chat windows. An active session is when a chatbot is activated in an interaction with the person.
If the person is not responding the chatbot will then follow up with a template of questions as it assesses the situation.
○ Interface- this is not a user interface but basically a bridge between the NLP model and the chat session. Here is where the NLP codes its output either in a form of text or voice back to the chat window for the user.
○ Natural Language Processing Model- It’s basically a kind of language model built using machine learning algorithms, to which it has the in-built programming to understand questions and also possesses the ability to utilize stored data to give answers.
○ Application Data Base- The Application DB host details, which then sends to the NLP so that it can use the interface to provide answers for the user.
○ Data/Corpus- Corpus is basically used when dealing with chatbots which can be used interchangeably with data or dictionary. It simply means some sort of repository or reservoir of data. it is the training data need for the chatbot to learn.
ii. Types of chatbots
It is to your advantage to know the different types of chatbots available. The first and the most important types of chatbots are; text-based chatbots and voice-based chatbots. Maybe you’ve been online trying to purchase a product on one of those online shops and you come to a popup that allows for the interaction that is an example of text-based chatbots. Voice-based chatbots can be such as Alexa or Siri.
The other types of chatbots are the ones that are designed to use approaches such as rule-based and self-learning. Rule-based chatbots are the ones programmed especially to answer questions based on a certain rule on which it has trained. Rule-based chatbots utilize a tree-like flow or known as a decision tree instead of A. I and that is possible by using guiding questions to narrow down to specific answers.
On the other hand, the self-learning A. I chatbots utilize the strand of the machine learning model to learn new things and assess situations and give you the answer that you’re looking for.
iii. The learning processes
The learning process of chatbots is quite sophisticated and challenging but can be understood. The process of learning is built into the chatbot by utilizing combinations of multiple programming platforms such as machine learning (a certain branch of computer science) which has algorithms that is utilized by chatbots to formulate answers and also pre-defined scripts (responses that are already programmed).
When the chatbot doesn’t know what to do during the conversation, it will either deflect the conversation or pass the conversation to the human operator however during that process the chatbot tries to learn as well.
The fascinating part of the learning process is similar to the human aspect of learning. The chatbot learns over time due to the multiple interactions it has engaged in, thus gradually but progressively gaining scope and relevance.
It is important that you know about the types of chatbots discussed earlier as it comes in handy in evaluating their learning process, how they store and retrieve data and whether they are powered by AI or just utilizing certain programing structures like decision trees.
Natural Language Processing is key, as it taps into Natural Language Understanding (bots comprehend the user's request), Machine Learning (bots analyze and determines the most correct response), and Natural Language Generation (bots responds in a human-like format)
The complexity of the chatbots is defined by how sophisticated their underlying software is and the data it is able to access. How relevant the chatbot depends on the type of data it is connected to. If the data is insufficient it will result in the chatbot being irrelevant and not useful.
Chatbots are developed not only to display and measure the advancement of technology but more significantly for conveniences, to help fast-track transactions while promoting ease of accessibility. There are more than hundreds of chatbot applications today, here’s a few of them:
• Email distributer- manage your emails, spam, etc…
• Entertainment assistant- bring to you sports, music
• Help desk assistant- manage your Hotel Bookings, purchasing…
• Home assistant- air-conditioning, WIFI
• Phone assistant- google assistant, Siri
• Operations assistant- more and technical aspects
Significance and Benefits of Chatbots
Chatbots are rapidly increasing the way we interact with software these days. They have become the promising alternative to virtual assistants and customer services. For instance, today Many e-commerce companies are using chatbots to improve customer experience.
Here are some benefits of having chatbots:
• Provide great business opportunities for both small and large companies
• Availability- Chatbots are always available
• Enables faster customer services
• Management of customer requests
• Enables conversational Marketing
• Promotes the ease of accessibility whatever the platforms are
Our world is moving more and more toward the trend of chatbots as the substitute for human services and assistance. This trend creates more opportunities and less time usage, giving freedom to the users across different platforms. Chatbots have proven to be very beneficial, for now, the future looks very promising with this technology of machine agents.