Chatbots are not a recent development. They are simulations which can understand human language, process it and interact back with humans while performing specific tasks. For example, a chatbot can be employed as a helpdesk executive. The first chatbot was created by Joseph Wiesenbaum in 1966, named Eliza. It all started when Alan Turing published an article named “Computer Machinery and Intelligence”, and raised an intriguing question, “Can machine think?”, and ever since, we have seen multiple chatbots surpassing their predecessors to be more naturally conversant and technologically advanced. These advancements have led us to an era where conversations with chatbots have become as normal and natural as with another human.
Identifying opportunities for an Artificial Intelligence chatbot
The first step is to identify the opportunity or the challenge to decide on the purpose and utility of the chatbot. To understand the best application of Bot to the company framework, you will have to think about the tasks that can be automated and augmented through Artificial Intelligence Solutions. For each type of activity, the respective artificial intelligence solution broadly falls under two categories: “Data Complexity” or “Work Complexity”. These two categories can be further broken down to 4 analytics models namely, Efficiency, Expert, Effectiveness, and Innovation.
Types of Chatbots
There are many types of chatbots available, a few of them can be majorly classified as follows:
- Text-based chatbot: In a text-based chatbot, a bot answers the user’s questions via text interface.
- Voice-based chatbot: In a voice or speech-based chatbot, a bot answers the user’s questions via a human voice interface.
There are mainly two approaches used to design the chatbots, described as follows:
- In a Rule-based approach, a bot answers questions based on some rules on which it is trained on. The rules defined can be very simple to very complex. The bots can handle simple queries but fail to manage complex ones.
- Self-learning bots are the ones that use some Machine Learning-based approaches and are definitely more efficient than rule-based bots. These bots can be further classified in two types: Retrieval Based or Generative.
There are many types of chatbots available depending on the complexity, a few of them can be majorly classified as follows:
- Traditional chatbot: Traditional chatbots are driven by system and automation, mainly through scripts with minimal functionality and the ability to maintain only system context.
- Current chatbot: Current chatbots are driven by back and forth communication between the system and humans. They have the ability to maintain both system and task contexts.
- Future chatbot: Future chatbots can communicate at multiple levels with automation at the system level. They have the ability to maintain the system, task, and people contexts. There is a possibility of introduction of master bots and eventually a bot OS.