Chatbots are still in their infancy stage, they are more useful for basic transactions rather than complex meaningful conversations.
By Aniketh Jain
With the recent boom in messaging apps and breakthroughs in artificial intelligence, chatbots are currently the buzzword in the industry. We were promised that chatbots would transform the way we interact with businesses and services, but the truth of the matter is that they are far from being intelligent. Still in their infancy stage, chatbots are more useful for basic transactions rather than complex meaningful conversations.
Today, many businesses are exploring the intimate ways technology has entwined itself in real life. Chatbots are fine examples; they are basically software packages powered by artificial intelligence, designed to perform specific tasks, where users can interact with, via a chat interface. Chatbots enable the end users to seamlessly interact with them through multiple platforms from one location. They also enable voice navigation on most internet aided devices like wearables, smartphones etc. Although many are developing chatbots on various platforms, most of them are not very sophisticated. This necessarily means that the primary investment in chatbots forms a stable curve with no further updates, since the technology rooted in needs cutting edge mechanisms to understand human pedagogy.
The technology is still in its nascent stages, and plain vanilla chatbots are rampant in the industry. These chatbots require value additions in understanding the user experience and hence, need to be more interactive with the inclusion of significant artificial intelligence. The aim is to build chatbots that automate tasks by understanding natural language inputs and field multifaceted requests. An intelligent chatbot uses machine learning to pick up on conversational cadences, enabling it to effectively mimic human conversations and react to written or spoken prompts to deliver a service.
Chatbots are touted as the future of customer service and communication. These next gen platforms will serve businesses with cost-effective benefits and aid in task automations. As tasks become more complex and challenging, the need for intelligent bots will gradually increase. It is intelligence that makes a complex conversation effortless and easy. Here are three critical dimensions that differentiate an intelligent one from a dumb bot:
Perception
Perception is where the chatbot understands what the user wants. A smart chatbot must make sense of the user’s intentions based on images and text to respond appropriately. Presently, chatbots lack the fluidity of natural human conversation. Take for instance a user booking a movie and asking the bot to “pick any Wednesday in the next three weeks”. A chatbot that can understand this will be perceived as more intelligent than the one that cannot. Intelligent perception also involves understanding other forms of inputs such as emoticons, images and gifs.
Machine Learning
Learning is an important trait of intelligence in chatbots. Using machine learning algorithms that are in tandem with human supervisors, chatbots can eventually cognize the human needs from past situations, learn from identical algorithms and perform better. However, quality of data and experience plays an important role as machine learning algorithms learn from such experiences and data that is made available to them. Therefore, developers should first collect enough data and then use machine learning algorithms to improve its performance.
Planning
This is the third dimension that defines chatbot’s intelligent behaviour. Planning is an internal task performed by it to decide how to carry out the task as requested by the user. To carry out a complex task, the chatbot requires the capability of finding the sequence of actions that will lead to a set goal. This sequence of actions leading to the accomplishment of a goal constitutes to form a plan. These plans include conversational actions such as informing, asking, acknowledging etc. With proper AI planning, chatbot can figure out the steps leading to the goal, by itself. This will simplify the development process greatly and can help in generating fluid, natural and meaningful conversations. Although, the use of AI planning has not been explored to a great extent, it holds much promise for the future of intelligent chatbots.
To conclude, chatbots can be made intelligent using machine learning, AI planning algorithms and natural language understanding. However, only with significant AI improvements, chatbots can gear up to face more user-centric, complex tasks. This necessarily means that the primary investment in chatbots forms a stable curve with no further updates, since the technology rooted in needs cutting edge mechanisms to understand human pedagogy.
Aniket Jain is CEO & CO-founder of Solutions Infini
