Bots are also used to buy up good seats for concerts, particularly by ticket brokers who resell the tickets.[12] Bots are employed against entertainment event-ticketing sites. The bots are used by ticket brokers to unfairly obtain the best seats for themselves while depriving the general public of also having a chance to obtain the good seats. The bot runs through the purchase process and obtains better seats by pulling as many seats back as it can.
ELIZA's key method of operation (copied by chatbot designers ever since) involves the recognition of clue words or phrases in the input, and the output of corresponding pre-prepared or pre-programmed responses that can move the conversation forward in an apparently meaningful way (e.g. by responding to any input that contains the word 'MOTHER' with 'TELL ME MORE ABOUT YOUR FAMILY').[10] Thus an illusion of understanding is generated, even though the processing involved has been merely superficial. ELIZA showed that such an illusion is surprisingly easy to generate, because human judges are so ready to give the benefit of the doubt when conversational responses are capable of being interpreted as "intelligent".
Tay, an AI chatbot that learns from previous interaction, caused major controversy due to it being targeted by internet trolls on Twitter. The bot was exploited, and after 16 hours began to send extremely offensive Tweets to users. This suggests that although the bot learnt effectively from experience, adequate protection was not put in place to prevent misuse.[55]
Conversable is the enterprise-class, SaaS platform that will build your bot with you. They work with a lot of Fortune 500 companies (they’re behind the Whole Foods, Pizza Hut, 7-11, and Dunkin Donuts bots, among others). They go beyond Facebook Messenger, and will make sure your conversations are happening across all channels, including voice-based ones (like, for instance, OnStar).
Used by marketers to script sequnces of messages, very similar to an Autoresponder sequence. Such sequences can be triggered by user opt-in or the use of keywords within user interactions. After a trigger occurs a sequnce of messages is delivered until the next anticipated user response. Each user response is used in the decision tree to help the chat bot navigate the response sequnces to deliver the correct response message.
Chatbots are used in a diverse fashion, across all verticals and on many different types of channel, e.g. websites, social messaging, etc. In business their application accelerated rapidly in 2019, leading Van Baker, research vice president at Gartner, to predict that: “By 2020, over 50% of medium to large enterprises will have deployed product chatbots."[17]
With an unprecedented increase in the number of people using messaging apps today, and the advancements in Artificial Intelligence, Machine Learning and Natural Language Processing (NLP) technologies, the rise of chat bots seems to have been inevitable. Research shows that the number of people using chat apps has surpassed the number of those using social networking apps, which is believable yet surprising!

Pop-culture references to Skynet and a forthcoming “war against the machines” are perhaps a little too common in articles about AI (including this one and Larry’s post about Google’s RankBrain tech), but they do raise somewhat uncomfortable questions about the unexpected side of developing increasingly sophisticated AI constructs – including seemingly harmless chatbots.
Streamchat is one of the most basic chatbot tools out there. It’s meant to be used for simple automations and autoresponders, like out-of-office replies or “We’ll get back to you as soon as we can!” messages, rather than for managing a broader workflow. It’s quick to implement and easy to start with if you’re just dipping your toes into the chatbot waters.