Is Your Chatbot Intelligent Enough to Understand Your Customers?
As chatbots move into complex territories, raising the intelligence quotient becomes more difficult. What's the model for an intelligent chatbot and how to build one?
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Every chatbot claims to be artificially intelligent, but are they actually intelligent enough to understand humans? To provide a human touch to customers? Chatbots should be intelligent enough. The crux is not the chatbot; rather, it is the intelligence quotient of the chatbot that can bring the human touch. But how to determine if your chatbot is intelligent? Let's see how.
As chatbots move into complex territories, raising the intelligence quotient becomes increasingly difficult. Does the chatbot meet our user's request? What is the model for an intelligent chatbot and how to build one?
Does the Chatbot Know What the User Wants?
A chatbot is intelligent when it becomes aware of user needs. For instance, let's consider the case of a chatbot helping a user book a room in a hotel. The user is prompted to give out the date the user has in mind to book the room. So far, so good — until the query, Are premium rooms available? comes from the user. Now, the Artificial Intelligence chatbot must understand this specific user need to provide a relevant answer. An intelligent chatbot will understand the language nuances to give a convincing answer.
How Do We Determine If a Chatbot Is Intelligent?
The AI chatbot comes with the ability to fix a goal and work autonomously to achieve that goal. This is easier said than done, though identifying the goal for a specific situation is in itself a hurdle to cross. The chatbot adheres to a three-step process for realizing the goal. It is the sense-think-act cycle that can define the intelligence of a chatbot. An AI chatbot goes through this cycle to make progress towards predefined goals autonomously.
Ability to Sense
For an AI chatbot, sensing the environment where it resides is a prerequisite to getting the information required to perform a task. The chatbot finds it easier to listen to what the user says than to sense what is being conveyed by the user.
Sharp to Think
In simple terms, the chatbot must convert information received from a user into an understandable format and store it in a knowledge base. An AI chatbot makes a decision by leveraging the pre-existing knowledge that it acquires continuously. Based on this decision, the chatbot takes action to achieve pre-defined goals. Use neural networks in Machine Learning to make the chatbot think and take actions depending on the request placed by the user.
Quick to Act
As the thought cycle goes through, the chatbot knows the action it has to take to respond to a user. Now, the chatbot has to act. The chatbot must now type out the reply to a specific query raised by the user. Typing out a sentence is relatively easy for a chatbot when compared to responding via its audio or video capabilities. For an audio or video chatbot, responding to the user appropriately becomes difficult in the way it has to sound like a human.
Published at DZone with permission of Kruti Patel. See the original article here.
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