Chatbots? New? You haven't met ELIZA
Posted: Tue Dec 17, 2024 7:28 am
By Dr Richard Benjamins, VP for External Positioning and Big Data for Social Good at LUCA.
Artificial Intelligence is a hot topic at the moment. We definitely live in the AI summer, as opposed to the AI winter of the 1970s when AI research suffered a decline in interest and funding due to undelivered expectations. Today, AI is back in, and chatbots in particular are at the centre of every analysts attention.
Facebook has recently launched a platform for developing chatbots, Google launched Allo, IBM has Watson, and there are of course Siri and Cortana. There are also hundreds of start-ups building their own chatbots such as you can see in this post from Venture Radar.
Chatbots are able to hold conversations with people in a relatively "natural way". The business promise of chatbots is that they are able to automate human interaction, which is one of the biggest cost factors to organizations (for example, in customer service).
So what's the history of AI? The first of what is now called a "chatbot" was ELIZA, a computer program written by Joseph Weizenbaum at the MIT AI Lab in 1964-1966. ELIZA simulated a Rogerian psychotherapist which people interacted with through typing. ELIZA was able to fool many people by convincing them that they were speaking with a real person, rather sms gateway finland than a computer program. This also generated one of the first discussions on passing the Turing Test: building a computer program whose output humans judge as coming from another human. Eliza has been implemented thousands of times by students of AI courses (including myself), and there are still online implementations available. But how does ELIZA work?
Conversation with Eliza Figure 1: Example of a conversation with Eliza
Basically, ELIZA is a rule-based system using pattern matching. The program reads the input from the command line and then parses the sentence looking for relevant keywords. When it finds a keyword, it plays back an appropriate answer to the user, often in the form of a new question ( the Rogerian approach). And this repeats all the time. When ELIZA cannot make sense of the input, it returns a general answer such as "Tell me more about X" (where X matches a word from the user's input), or "What do you mean by that?" Moreover, ELIZA has stored several alternative formulations for the same answer, so it doesn't repeat itself all the time.
Artificial Intelligence is a hot topic at the moment. We definitely live in the AI summer, as opposed to the AI winter of the 1970s when AI research suffered a decline in interest and funding due to undelivered expectations. Today, AI is back in, and chatbots in particular are at the centre of every analysts attention.
Facebook has recently launched a platform for developing chatbots, Google launched Allo, IBM has Watson, and there are of course Siri and Cortana. There are also hundreds of start-ups building their own chatbots such as you can see in this post from Venture Radar.
Chatbots are able to hold conversations with people in a relatively "natural way". The business promise of chatbots is that they are able to automate human interaction, which is one of the biggest cost factors to organizations (for example, in customer service).
So what's the history of AI? The first of what is now called a "chatbot" was ELIZA, a computer program written by Joseph Weizenbaum at the MIT AI Lab in 1964-1966. ELIZA simulated a Rogerian psychotherapist which people interacted with through typing. ELIZA was able to fool many people by convincing them that they were speaking with a real person, rather sms gateway finland than a computer program. This also generated one of the first discussions on passing the Turing Test: building a computer program whose output humans judge as coming from another human. Eliza has been implemented thousands of times by students of AI courses (including myself), and there are still online implementations available. But how does ELIZA work?
Conversation with Eliza Figure 1: Example of a conversation with Eliza
Basically, ELIZA is a rule-based system using pattern matching. The program reads the input from the command line and then parses the sentence looking for relevant keywords. When it finds a keyword, it plays back an appropriate answer to the user, often in the form of a new question ( the Rogerian approach). And this repeats all the time. When ELIZA cannot make sense of the input, it returns a general answer such as "Tell me more about X" (where X matches a word from the user's input), or "What do you mean by that?" Moreover, ELIZA has stored several alternative formulations for the same answer, so it doesn't repeat itself all the time.