Google Vs Chatbots: finding the common ground

In the last decade, most of the best artificial intelligence (AI) was built on the back of natural language processing or neuro-linguistic programming (NLP). While many people consider AI to be something of a future technology, the truth is that they’ve interacted with AI and NLP in their everyday lives. The most common example is AI chatbot.

Let’s Talk About NLP

NLP is a field of computer science, artificial intelligence, and computational linguistics that looks to make sense of human language by carefully analysing the interactions between computers and human (natural) languages in order to effectively deduce what we are asking and communicate back to us with a correct answer.

The end goal for NLP and AI is to make this communication so intuitive and spontaneous that we don’t realise we’re talking to a computer.

Every day, when you type a query into a little single-line text box with Google written on top of sparse white webpage, Google is processing your natural language in an attempt to understand what you’re looking for before presenting your search results. Every time you click on a result, Google’s AI takes note and optimises future results.

Leveraging AI for Conversation

Chatbots are real life implementation of Conversational AI, which is one of two forms of AI: Transformational and Conversational. Chatbots works in much the same way as Google search does. Each question or query that a person asks the bot takes it as a mini “Google search” and provides more or less, the first search result. But, real challenge lies here as for a Google search, a human gets to select the most appropriate result but for a chat, the chat bot must select it.

Usually, the first result in a Google search is not the best possible answer and human tends to look for other search results to find the right answer of question in hand. For a chatbot to always provide the best answer, it would always have to select the correct “first result”. Keeping the current AI and NLP technologies in perspective, building such high performing AI chatbot is extremely difficult.

Building responsible chatbots

Scope of search engine like Google is almost endless since it has no inherent end game, while the scope of a chatbot is far narrower. Chatbots have a specific purpose for being built, for example, to sell you a product or provide the answer of frequently asked questions (FAQs). According to Gartner, chatbots will power 85% of all customer service interactions by the year 2020. In fact, the average person will soon have more conversations with bots than with their spouse. A large part of the aforementioned quantity of chatbots comes from how easy it is to build one as compared to a full fledged search engine like Google.

Fortunately, there is a way to build and implement an effective AI chatbot:

1. Data is important:

The first, and maybe most important component is data. Real-time conversation is not a child’s play to comprehend for a non-human. Not only are there questions being asked, but there are also further questions related to the original question and possible follow-up questions related to answers received. Here, time becomes an important factor which is needed to compile and analyse data in the form of answers to the questions that are being asked.

2. Human intervention

Now, to bring AI to the next level human intervention is required. Rather than pointing AI chatbots solely at the customer, human can act as intermediaries between the bot and the customer. This way, we can ensure that the “first result” is always the best possible answer because human intervention determines whether to communicate the bot’s answer directly to the customer or not.

If the human representative adjudges the answer to be valid response, it can be pushed along to the customer. If the answer is incorrect or invalid, the human representative can change, improve or discard the answer-manually providing a more suitable answer to the customer. This method is equally beneficial to both human representatives and customer in the following manner and helps artificial intelligence move forward in a responsible way:

. First, customer enjoys and appreciates the positive experience when their issue gets resolved in a more efficient and timely manner

. Second, the AI chatbot is continuously being fine-tuned by knowledgeable human representatives who are well accustomed to handle customer inquiries


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