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Chatbots in Business Evolution. In mathematics, a type of variation… | by Peter Michael | Jun, 2020

Peter Michael

In mathematics, a type of variation called direct variation describes ‘a simple relationship between two variables — such that we observe an increase of one variable when the other increases, or a decrease of the same when the other reduces’. This law works in business as well, wherein the population of the workforce determines the productivity of the company. However, recent development in artificial intelligence defies this law. In 2020, a business could have only a team of essential workers with a couple of well-utilized computers and do more than a larger company which has the help of its thousands of workers but without digital intervention or its innovative implementation whatsoever. The usefulness of computer technology in business has been paced recently in such a way that most businesses will not need to hire more workers in the future. Even now, we see large organizations displacing thousands of workers and replacing them with robots.

Smaller businesses and startups might not have the capacity to own industrial robots, but everyone has the opportunity of the chatbot technology available to them. Chatbots are a species of robots, which essentially are ‘software robots’ that can interact with humans in their common languages through text or audio chats. They interact as well with their [internet] environment, accessing resources from nodes across the digital globe and fetching data from the real world through sensors and detection tools such as computer vision, speech recognition, handwriting recognition and so on. The term ‘Chatbot’ was originally coined as ‘chatterbot’ by Michael Mauldin in 1994 in his bid to demonstrate conversational computer programs. However, a mathematician named Alan Turing was the first person who developed a computer program that could mimic or simulate human intelligence — this history is reflected in the movie “The Imitation Game, 2014”. This mathematician, Alan Turing, stamped his name on the chronicle of artificial intelligence and of the chatbot technology when he invented the ‘Turing Test’ in 1950, a method in artificial intelligence for determining whether or not a computer is capable of thinking like a human being.

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With the NLP technology, chatbots can also display emotional characteristics in their interactions (chatting) since it allows them to understand different insinuations in different users’ messages. Also consequential is their ability to infer a user’s mood by examining the tone in their speech or text replies. Apart from this intellectual and mild emotional intelligence, chatbots prove better than human customer service agents since they don’t have to interact with customers one at a time — they can chat with a very large number of people at the same time, as much as can access that particular node of the internet. Chatbots can be integrated into a vast array of platforms and devices, not limited to the web or mobile apps, but also in other digital devices like audio devices, such as is implemented in the Amazon Alexa. Even physical robots own their audibility and communication to their integrated chatbot software.

Like Amazon’s Alexa which was first launched in 2014 on the Amazon Echo, these software robots can be integrated into hardware systems to collect information from a tangible environment and to respond through that tangible environment, rather than having information dissemination only online, mostly through texts. This way, it becomes apparent how physical robots get their conversational intelligence.

In contrast to the mechanical implementation of the chatbot technology, most chatbots are based on the internet, interacting with people only at a particular portal to which they are deployed on the internet, though some chatbots have secondary functions of crawling the web into other portals and extracting useful data.

This discourse may become verbose if we were to continue contemplating the potentials and advantages of chatbots. Therefore, I will precisely highlight how this technology is built. Of course, knowing how it goes is more important than just keeping some couple of facts about chatbots. To this end, if you are an entrepreneur or a business enthusiast, you sure must have started wondering how you could employ this technology to sail your business aloft if you have not already started using it.

Much more like there are different programming languages with different lines of codes to write the same function, there are also a lot of artificial intelligence frameworks that can be used to build chatbots, although it all roots to traditional programming which can also be used. One advantage many people find using a framework rather than programming the whole thing is because the task could be very complex for a lot of programmers, and also impossible for the remaining people who don’t even know how to code nor have any idea about programming. Most frameworks don’t require any coding skill, the developer (you) will only have to learn about their environment and how their tools work. The most common chatbot development frameworks are Dialogflow (affiliated with the popular Google Assistant), Microsoft Bot Framework, Wit.ai, Pandorabots (used to build Mitsuku) — Mitsuku is the current winner of the Loebner Prize, an annual competition in artificial intelligence that awards prizes to the most human-like chatbot. Other frameworks are Snatchbot (a rather simple and decorative framework), Intercomm, Chatfuel (for building Facebook Messenger bots), Picky Assist (a simple messaging automation framework primarily integrated to WhatsApp), etc. No coding skills are required to start building chatbots with most of these frameworks, however, one would need to dedicate some time to learn how a particular framework works, and of course, there might be paid plans for premium access, but all of the frameworks are pretty much free at the basic level.

For the determined and critically practical people who always like to get to the root of things, who would rather build their chatbots totally independent of any third party platform or framework but would employ the scratch codes of programming languages; although it is quite more complex and difficult, an ingenious programmer could make a much more fantastic chatbot with fresh lines of code which were packaged and prepared by frameworks. The advantage of this is the absolute ownership and independence of the programmer to define the features of the chatbot if they could. For this method, the prevalent programming language, as in artificial intelligence generally, is Python. Others that could be used, but not commonly used nor as effective include Clojure and PHP. The disadvantage, however, is the difficulty in accessing third-party API and add-ons, apart from the other difficulty of deploying the chatbot to popular channels. So, frameworks also make it easy to get your chatbot across multiple channels, including websites and social media.

The future of chatbot technology is already becoming apparent as it has been one of the most outstanding applications of artificial intelligence that the present world has seen so far. In the greater future, even as it is becoming now, chatbots will be all over the internet crawling web pages one after the other and providing real-time information reports to their owners. All questions otherwise asked from search engines or searched from books and files will be answered immediately owners talk to their devices (chatbots). Of course, do we not already see this reality? The Google Assistant and Amazon’s Alexa among Internet of Things (IoT) explorers can manipulate other digital devices indoors and outdoors when users ask them. The Apple Siri can turn music on and off among the controls it is granted in the phone. Businesses which do not have this technology in its optimum will lose a lot of money hiring humans to attend to customers online, teach their staff basic stuff, fetch information from the database, or even market their products after when they will as well lack productivity as compared to the more digitally strategic companies. It is not too late to start if you have not started already.

Peter Michael,
University of Lagos, Nigeria.

SGC GI: 048 — Robotics/IoT/AI

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