Today you will no longer surprise anyone with a messenger chatbot. It wasn’t long ago either chats and other ways of communicating online were available only in a person-to-person format. Nowadays, using a chatbot is the new norm. Still, do they deliver good enough results? Do you often come across a bot that cannot correctly answer your question?
Conducting small research even among your friends or acquaintances, you most probably get the feedback that they are not happy with the answers of the bots.
Let’s face it – even the big companies can’t build assistants capable of surrogating the communication with a human.
Of course, some chatbots are already approaching the level where it is difficult to tell the difference between a bot and a human in answering frequently asked questions.
The latest example of a chatbot able to answer most FAQs (plus even some complex science-related questions) is A digital version of Albert Einstein. This bot synthesized voice has been recreated using AI voice cloning technology basing on audio recordings of the famous scientist’s actual voice.
We’ve already tried to talk to Albert, of course. He is terrific at answering pre-programmed questions or queries he was trained to react to. Still, when we asked him a relatively simple question – ‘What is a chatbot?’ – he couldn’t be able to answer. Albert asked to reformulate the question!
Why have chatbots not mastered all kinds of questions and answers for the correct interaction with a person yet? The answer is simple. Almost all classic algorithms do not use artificial intelligence at their core and do not self-learn, and if they learn at the expense of their developer, then it is ineffective.
And what about the AI-powered Einstein? Why didn’t he manage to answer our question using his AI power? Here’s what Alforithmic’s (Digital Einstein’s creators) COO Matt Lehmann told:
“For now, the erudite-sounding interactive Digital Einstein chatbot still has enough of a lag to give the game away. Its makers are also clearly labeling their creation in the hopes of selling their vision of AI-driven social commerce to other businesses”, says Techcruch.com.
Most chatbot solutions offered on the market create the illusion of a human-like bot/robot and are not one. People build scripts for answering questions in such chatbots, and these scripts are basic (rule-based) ones. That is the root of most bots stuck when a user asks them a question that is not covered by their rules. Of course, a human specialist would see inconsistencies in the script and correct them, but that is not the ultimate solution.
Still, we acknowledge that ‘so many men, so many minds’, – people might ask non-standard questions using pidgin, making typos or trivial mistakes in wording or sentence structure. Chatbots can’t manage that and then stuck, suggesting to connect a user with a live person (if such a case was initially covered by their rules).
How to fix, update, improve and achieve correct chatbot-user communication? The answer is in creating more comprehensive AI algorithms. A self-learning neural network can simultaneously iterate over many options, including options with correcting grammatical errors, pidgin, and typos for a better understanding of a user. Thus, if an AI-powered bot can understand users’ intentions correctly, then it can answer their questions no worse than any human does. Again, that is relevant if the neural network has access to a database of questions and answers and generates the correct reply.
What’s next in the AI chatbots industry?
The best AI-driven chatbots, including text and voice assistants, can self-learn not only from the experience of directly interacting with users but also from Google, Bing, and other search engine databases. They constantly evolve, improving their performance.
In the future, of course, AI-powered chatbots will become more advanced, but now they are more like kids who aren’t always able to understand your questions. They only lack a little thing for their rapid development – quantum brains.
Of course, with the emergence of quantum computers and computing, we will all see a tremendous leap in the chatbots quality, significantly improved with rapid computational processes. Meanwhile, we’ve got Alexa, Siri, Cortana, Einstein, and their slow self-learning algorithms based on traditional computing.
How to keep pace and stay on top with your chatbot?
Today, there are varied approaches and algorithms that can (within the framework of existing technologies) achieve a good result and set AI self-learning algorithms. Still, things will always bump against the number of allocated resources and the speed of data processing that developers are ready to invest in AI algorithm and its further self-learning process.
Specialists from Google, Microsoft, and other corporate giants understand that and invest in their services enough to keep their AI-based chatbots developing and self-learning, transforming for quantum computing and new user models and customer requests.
What should companies do to keep that pace even without having corporate giants’ resources? Struggle to improve their services, fix bugs, and win with knowing their customers better!
On the one hand, as an example, messenger or web-based chatbots can significantly reduce human resources involved, cutting the company’s costs. On the other hand, the company can lose customers if they do not receive answers to their questions and requests. That is the common case in mid-sized and even in large companies, pointing to the gap – their savings on automation technologies can bring them losses at any time, both financial and reputational.
To stay on top and claim their place in the digital present and future, companies need to take care of their customers, building automated services – relevant in terms of current demand and upcoming trends.
Do companies need to take care of the high-quality automation of communication between the company and the client today? Certainly, and you also need to realize that there is no point in investing in outdated solutions. AI-powered chatbots can cover both basic and more advanced user inquiries, thus, start your communication automation with them.