The Untold Story of AI’s ‘Chatty’ Evolution


The Gist

  • Historical context. ELIZA, released in 1966, pioneered chatbot technology, using pattern-matching to simulate conversation and paving the way for future natural language systems.
  • Evolutionary path. Chatbots evolved from simple rule-based systems to AI-powered, voice-activated personal assistants and generative AI chatbots capable of full-fledged conversations.
  • Challenges ahead. Despite advancements, AI chatbots face issues like the proliferation of disinformation, regulatory hurdles and public sentiment favoring human customer service over AI.

The first chatbot is generally considered to be ELIZA, created by Joseph Weizenbaum at MIT and released in 1966. ELIZA simulated conversation by using pattern matching and substitution methodology, which gave the illusion of understanding. It would rephrase user inputs as questions or statements, tricking some users into believing they were chatting with a real human. The era of chatbots had begun, and over the years, chatbots have evolved to the point where they are able to have full-fledged, existentialist conversations. Let’s examine the evolution of chatbots, from early primitive bots to today’s advanced conversational and generative AI, and explore how they are currently being used across a variety of domains.

Rule-Based Chatbots

ELIZA was one of the earliest primitive chatbots. Named for the lead character in George Bernard Shaw’s Pygmalion, ELIZA simulated conversation using basic natural language processing (NLP). Most of ELIZA’s language capabilities came from individual “scripts.” The most famous script, DOCTOR, engaged users with open-ended questions and responses reminiscent of an empathic psychologist like Carl Rogers. With just simple pattern-matching rules, and no real understanding of emotion, ELIZA could sometimes pass as human. Despite its limitations, this breakthrough program paved the way for the natural language systems we use today.


Mike King, chief marketing officer at AIPRM, an AI prompt marketplace, told CMSWire that we should take a moment to appreciate the sheer brilliance of ELIZA. “In a world of punch cards and bulky mainframes, this chatbot was nothing short of revolutionary. While ELIZA may have been a simple pattern-matching mechanism, it set the stage for what was to come. Imagine, back in 1966, having a digital entity rephrasing your words and throwing them back as questions. It was the beginning of a new dawn.”

Other rule-based chatbots soon followed. In 1972, psychiatrist Kenneth Colby created the next influential chatbot, Parry, at Stanford University. Parry was groundbreaking for attempting to simulate a person with paranoid schizophrenia.



In 1988, Rollo Carpenter, a British programmer, began working on Jabberwacky, which was designed to replicate normal human conversation in an enjoyable, amusing and natural way. It became available on the web in 1997 and went on to win the Loebner Prize — an annual AI competition designed to find computer programs considered to be the most human-like. In 2008, Carpenter launched Cleverbot, a chatbot that used machine learning (ML) to have conversations with humans.


In 1995, Richard Wallace developed A.L.I.C.E., which won the Loebner Prize three times for the most humanlike chatbot. However, it failed the Turing test, which evaluates a machine’s ability to exhibit intelligent conversation indistinguishable from a human.


In 2001, AOL debuted SmarterChild, a chatbot that users could interact with on AOL Instant Messenger. SmarterChild could look up information, play games and have basic conversations with users.


Personal Assistant Bots

Apple’s Siri, released in 2011, pioneered the concept of conversational virtual assistants on phones. Siri demonstrated the potential for AI-powered, voice-controlled assistants that could understand natural language requests. Amazon Alexa made its debut in 2015, two years after Amazon acquired a Polish speech synthesizer named Ivona. It is now part of the Amazon Echo Dot, Echo Studio, Echo smart speaker and Amazon Tap speakers. 

Google launched its Google Assistant for Android phones in 2016. Not to be left behind, Microsoft introduced its own assistant called Cortana. The launch of these tech giants’ virtual assistants marked a turning point in making conversational AI a mainstream and expected feature on smartphones.

Conversational AI Chatbots

Conversational chatbots started out being rule-based, meaning that they relied on scripted rules and templates to construct responses. Today, conversational chatbots use AI and neural networks to be able to create better responses. In 2017, Eugenia Kuyda created Replika, an app that creates AI companions capable of personalized conversations that learn about users over time. Replika was described in an article as “the app that’s trying to replicate you.”



The “Replika AI Agent” that powers the chatbot was trained on billions of lines of dialogue to learn nuanced patterns in human conversation. Replika uses these neural networks and ML algorithms to analyze chat contexts and continually improve its responses based on feedback from users rating its replies. 

Unlike rigidly scripted chatbots that rely on keywords, Replika aims to engage users in an emotional, human-like way by understanding the full meaning of conversational turns. While some common small-talk responses may be scripted, Replika generates unique, personalized replies using AI rather than just predefined templates. 

Generative AI Chatbots

Since the release of Open AI’s ChatGPT in November 2022, generative AI has been in the news practically every day. Not long after the release of ChatGPT, both Google and Microsoft announced their own generative AI chatbots, namely Google Bard and Microsoft Bing

Generative AI has come to be a huge business commodity with extremely rapid growth. GlobalData’s Generative AI Growth Analysis forecasts the global generative AI market size to grow from $10.16 billion in 2022 to $103.74 billion by 2030. Additionally, the use of generative AI chatbots for customer service has exponentially grown due to high consumer demand for speed and convenience when interacting with customer service. An August 2023 LivePerson survey revealed that not only do consumers hate traditional Interactive voice response (IVR) systems, 57% of those polled would rather do a load of laundry than interact with an IVR — and 41% would rather clean a toilet. 

Microsoft collaborated with Open AI to upgrade their Bing search engine and introduce a generative AI chatbot that was built on the same technology as ChatGPT. Users can chat with Bing about practically any topic, or they can use the chatbot to search the web.

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