Malicious chatbots are frequently used to fill chat rooms with spam and advertisements, by mimicking human behavior and conversations or to entice people into revealing personal information, such as bank account numbers. They are commonly found on Yahoo! Messenger, Windows Live Messenger, AOL Instant Messenger and other instant messaging protocols. There has also been a published report of a chatbot used in a fake personal ad on a dating service's website.[55]
AI-driven automation in each of these areas can streamline how enterprises train, manage, and work with seasonal, temporary, part-time, and full-time employees. However, it is important to consider the challenges surrounding information security, legal boundaries, extensibility, and audit logging when making the decision to get started using bots for HR.

NBC Politics Bot allowed users to engage with the conversational agent via Facebook to identify breaking news topics that would be of interest to the network’s various audience demographics. After beginning the initial interaction, the bot provided users with customized news results (prioritizing video content, a move that undoubtedly made Facebook happy) based on their preferences.

Reports of political interferences in recent elections, including the 2016 US and 2017 UK general elections,[3] have set the notion of botting being more prevalent because of the ethics that is challenged between the bot’s design and the bot’s designer. According to Emilio Ferrara, a computer scientist from the University of Southern California reporting on Communications of the ACM,[4] the lack of resources available to implement fact-checking and information verification results in the large volumes of false reports and claims made on these bots in social media platforms. In the case of Twitter, most of these bots are programmed with searching filter capabilities that target key words and phrases that reflect in favor and against political agendas and retweet them. While the attention of bots is programmed to spread unverified information throughout the social media platform,[5] it is a challenge that programmers face in the wake of a hostile political climate. Binary functions are designated to the programs and using an Application Program interface embedded in the social media website executes the functions tasked. The Bot Effect is what Ferrera reports as when the socialization of bots and human users creates a vulnerability to the leaking of personal information and polarizing influences outside the ethics of the bot’s code. According to Guillory Kramer in his study, he observes the behavior of emotionally volatile users and the impact the bots have on the users, altering the perception of reality.
Sometimes it is hard to discover if a conversational partner on the other end is a real person or a chatbot. In fact, it is getting harder as technology progresses. A well-known way to measure the chatbot intelligence in a more or less objective manner is the so-called Turing Test. This test determines how well a chatbot is capable of appearing like a real person by giving responses indistinguishable from a human’s response.
These are just the basic versions of intelligent chatbots. There are many more intelligent chatbots out there which provide a much more smarter approach to responding to queries. Since the process of making a intelligent chatbot is not a big task, most of us can achieve it with the most basic technical knowledge. Many of which will be very extremely helpful in the service industry and also help provide a better customer experience.
Social networking bots are sets of algorithms that take on the duties of repetitive sets of instructions in order to establish a service or connection among social networking users. Various designs of networking bots vary from chat bots, algorithms designed to converse with a human user, to social bots, algorithms designed to mimic human behaviors to converse with behavioral patterns similar to that of a human user. The history of social botting can be traced back to Alan Turing in the 1950s and his vision of designing sets of instructional code that passes the Turing test. From 1964 to 1966, ELIZA, a natural language processing computer program created by Joseph Weizenbaum, is an early indicator of artificial intelligence algorithms that inspired computer programmers to design tasked programs that can match behavior patterns to their sets of instruction. As a result, natural language processing has become an influencing factor to the development of artificial intelligence and social bots as innovative technological advancements are made alongside the progression of the mass spreading of information and thought on social media websites.
However, the revelations didn’t stop there. The researchers also learned that the bots had become remarkably sophisticated negotiators in a short period of time, with one bot even attempting to mislead a researcher by demonstrating interest in a particular item so it could gain crucial negotiating leverage at a later stage by willingly “sacrificing” the item in which it had feigned interest, indicating a remarkable level of premeditation and strategic “thinking.”
The bot (which also offers users the opportunity to chat with your friendly neighborhood Spiderman) isn’t a true conversational agent, in the sense that the bot’s responses are currently a little limited; this isn’t a truly “freestyle” chatbot. For example, in the conversation above, the bot didn’t recognize the reply as a valid response – kind of a bummer if you’re hoping for an immersive experience.
Have you ever dreamed about creating your own chat bot that asks users a few simple questions and, based on human replies, creates new questions to continue the conversation, possibly an endless conversation? Have you thought about putting this chat bot on your Facebook page? Nothing simpler than creating a chat bot by reading and following this step-by-step guide Writing your first Facebook chat bot in PHP using Jaxl library written by a PHP developer Abhinav Singh.

A rapidly growing, benign, form of internet bot is the chatbot. From 2016, when Facebook Messenger allowed developers to place chatbots on their platform there has been an exponential growth of their use on that forum alone. 30,000 bots were created for Messenger in the first six months, rising to 100,000 by September 2017.[8] Avi Ben Ezra, CTO of SnatchBot, told Forbes that evidence from the use of their chatbot building platform pointed to a near future saving of millions of hours of human labour as 'live chat' on websites was replaced with bots.[9]
The term Chatbot is closely related to chat bot and chatterbot. Chatterbot is more popular in relation to chatbot who talk a lot, and is not necessary very intelligent in processing the user answers. Chat bot is used by technical people who consider the word ‘bot’ as a normal term for ‘robotised actions’, and for them ‘chat bot’ is a special kind of bot. The term Chatbot is actually the most popular amongst these three terms and has the broadest meaning.
The “stand-alone” application, where the chatbot runs on a single computer, integrates mostly some sort of system interface, allowing your chatbot to control certain aspects and functions of your computer, such as playing media files, or retrieving documents. It usually also has a graphical component built in, as well, in the form of an avatar (often female) that enhances interaction, thus improving user’s experience.
Chatbots could be used as weapons on the social networks such as Twitter or Facebook. An entity or individuals could design create a countless number of chatbots to harass people. They could even try to track how successful their harassment is by using machine-learning-based methods to sharpen their strategies and counteract harassment detection tools.
The “stand-alone” application, where the chatbot runs on a single computer, integrates mostly some sort of system interface, allowing your chatbot to control certain aspects and functions of your computer, such as playing media files, or retrieving documents. It usually also has a graphical component built in, as well, in the form of an avatar (often female) that enhances interaction, thus improving user’s experience.
A representative example of a chat bot is A.L.I.C.E., brought to artificial life in 1995 by Richard Wallace. The A.L.I.C.E. bot participated in numerous competitions related to natural language processing evaluation and obtained many honors and awards, and it is also worth mentioning that this chat bot won the Loebner Prize contest at least three times, it was also part of the top 10 at Chatterbox competition, and won the best character/personality chat bot contest.
The classic historic early chatbots are ELIZA (1966) and PARRY (1972).[10][11][12][13] More recent notable programs include A.L.I.C.E., Jabberwacky and D.U.D.E (Agence Nationale de la Recherche and CNRS 2006). While ELIZA and PARRY were used exclusively to simulate typed conversation, many chatbots now include functional features such as games and web searching abilities. In 1984, a book called The Policeman's Beard is Half Constructed was published, allegedly written by the chatbot Racter (though the program as released would not have been capable of doing so).[14]