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Chatbots 101 by V-Soft Consulting Chatbots 101 | V-Soft Consulting

Chatbots are all the rage. They exist for social media, websites, stores, and even business to business conversations. Chances are you’ve spoken to one, but may not have even realized it. Chatbots are taking over the Internet, saving companies hundreds of hours and manpower. In this eBook we will explore the world of chatbots, how they came to be, and what they are capable of. Chatbots 101 | V-Soft Consulting

Table of Contents » What is a Chatbot? » The History of Chatbots » How Do Chatbots Work? » How Can Chatbots Help Businesses? » About the Author Chatbots 101 | V-Soft Consulting

What is a Chatbot? To put it simply, chatbots are computer applications powered by artificial intelligence to communicate with you. They are designed to mimic natural human conversation via an online chat interface, SMS, and sometimes, even voice chat. Despite being designed for human consumption, chatbots are also capable of communicating and gathering information from other chatbots. There are many different names for chatbots: chatterbots, talkbots, bots, chatterboxes, artificial conversation entities (ACE), and virtual assistants. They are available for dozens of tasks, such as helping answer any legal questions you may have, being a personal therapist, or helping you keep your calendar organized. There are also some as useless as the one designed to represent a popular seasonal drink from your favorite coffee shop. Most chatbots are preset to understand a specific range of keywords and respond with the correct input. It’s more of a complex “If this, then that” situation – if the user mentions “e-mail setup”, then send user “how to set up your e-mail guide”. However, there are some that are much more complex and actually learn from conversations they have with other users. What is Artificial Intelligence? Much like how it sounds, artificial intelligence is when a computer simulates humanlike intelligence. For a computer to be considered intelligent, it must be capable of learning, reasoning, recognition, and correcting errors. It is not, however, the Hollywood interpretation of robots that are virtually human (Such as Marvin the Paranoid Android from Hitchhiker’s Guide to the Galaxy or C-3PO from Star Wars). That is still purely science fiction and we are quite a long way off; it’s very likely to not happen within our lifetime. 1 Chatbots 101 | V-Soft Consulting

In order for a machine to act or behave like a human, they require a great deal of information about many different situations, items, categories, and relations for them to connect each occurrence to one another in a method that is called knowledge engineering. It includes groups of complex information compiled into a knowledge base and linked through building, maintaining, and using the information. Types of Artificial Intelligence There are many different categorizations of artificial intelligence, but some of the most well-known are: » Strong AI: Strong AI is when the machine involved is developed to simulate human behavior and cognitive abilities, as well as the ability to reason and learn. This is what people typically think of when they think of AI: robots that can respond to questions, solve problems, or perform complex tasks. This type of AI is adaptive and has opportunities to expand. » Weak AI: Weak AI is when a machine is designed to carry out a specific task – such as working an assembly line, or playing chess against a master chess player. It is incapable of self-improvement, so it will only be good at what it’s programmed to do, nothing more. Machine Learning Machine Learning is a form of artificial intelligence that provides machines the capability to learn and understand concepts without being programmed specifically for that purpose. It utilizes things like Deep Learning – essentially, predictive analytics – and different algorithms for data to be logged and input into the device’s knowledge base. 2 Chatbots 101 | V-Soft Consulting

Machine learning algorithms are typically classified into three broad categories, depending on the information available to the machine in question. These are: » Supervised Learning: Where data is essentially labeled and described to the machine in order for it to detect and sort the new information. » Unsupervised Learning: Information is not specified or labeled in any way, but may be sorted in reference to their similarities or differences. » Reinforcement Learning: The machine is given a specific goal to follow through with, followed by a review and providing feedback, whether positive or negative. Natural Language Processing Natural Language Processing is where a machine is capable of understanding the way a human speaks naturally. This is a very complex and challenging task for computers to comprehend, as they are very precise whereas human speech is not. Things like slang, metaphors, contractions, and other variables can result in the machine not correctly understanding requests. Natural Language Processing (NLP) utilizes machine learning and other forms of artificial intelligence to “learn” the way their users speak, using assessments to correctly identify the user’s request. It requires a considerable amount of programming, analytics, the understanding of semantics and syntax, segmentation, and tagging to function as expected. Consider this: you’re hungry and have a craving for duck. You message a local chatbot and ask for “good places with duck” – the bot quickly churns out several restaurants in your area that have duck on the menu. This would not be possible without Natural Language Processing (You’d likely get a confused bot that wouldn’t be able to process your request). 3 Chatbots 101 | V-Soft Consulting

In fact, chances are you’ve already used Natural Language Processing today. Things like Google’s predictive searches, your phone’s auto correct/auto complete, or even spam detectors utilize Natural Language Processing. The Turing Test The Turing Test was developed by an English computer scientist by the name of Alan Turing in 1950. It is a controversial test designed to test the ability of a machine to exhibit intelligent, humanlike behavior. To pass the test, the machine’s replies would have to be indistinguishable from a human in a five-minute test. Turing predicted that by the year 2000, machines would be able to fool 30% of human judges, but this feat took much longer than anticipated. As of 2017 no machines have truly passed the Turing Test, but there have been claims that a chatterbot by the name of Eugene Goostman passed the test in 2014 by fooling 33% of the judges involved into believing he was a human being. The test was not intended to test a machine’s intelligence, only that a machine behaves and acts like a human being would when faced with the same situations. As not all human behavior is intelligent, the Turing Test would also test for behaviors like lying, making typing mistakes, or responding to insults. Another reason that intelligence is omitted from the test is that machines are far more likely to solve complex mathematical problems that would be impossible (or nearly impossible) for a human to solve. The History of Chatbots The idea of creating a machine that had humanlike thought processes has been around for centuries. Scientists, philosophers, and even sculptors were fascinated by the idea of a humanistic automaton capable of thought. 4 Chatbots 101 | V-Soft Consulting

Author Samuel Butler first wrote the idea of a mechanical consciousness in his 1872 science fiction novel, Erewhon. Despite the interest and fascination on the subject, it was not until 1966 when any form of artificial intelligence really took form: ELIZA. ELIZA Generally recognized as the first actual chatbot, ELIZA was developed by Joseph Weizenbaum. Named after Eliza Doolittle, a working- class character in the play Pygmalion, ELIZA was meant to emulate a Rogerian psychotherapist. It was capable of answering basic questions and asking for users to elaborate on their discussions. For example, if you told ELIZA that you were sad, it would respond with “Why are you sad?” inciting a further discussion and urging you to continue. Unfortunately, the program was not more involved than this, unable to understand the conversations it was having. ELIZA was a groundbreaking invention despite its lack of “real” intelligence. Despite only being capable of using pattern matching and substitution methodology to form new sentences, ELIZA would receive an overwhelming response of positivity for its “human-like” conversations; even Weizenbaum’s secretary was taken by the program. It inspired dozens of other chatbots both serious and comedic. A.L.I.C.E. One of the chatbots inspired by ELIZA was A.L.I.C.E (Artificial Linguistic Internet Computer Entity), also known as Alicebot. Alicebot was the brainchild of robotics professor Richard Wallace, officially going live in 1995. Alicebot uses AIML (Artificial Intelligence Markup Language), a programming language that describes a class of data objects (called AIML objects) and partially describes the behavior of computer programs that process them. Essentially, it will have a list of categories to discuss with the user – most bots have around 45,000 different topics to choose from – and choose the most “accurate” response for the discussion. 5 Chatbots 101 | V-Soft Consulting

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