Conversational AI Theory
1 Overview of Conversational AI
What is Conversational AI?
Conversational artificial intelligence can be defined is the application of computing technology to facilitate a natural conversation between computers and people. Conversational AI can be achieved using several different modes of communication including voice, text or chat. Voice is when the user speaks directly to the system and the AI agent can respond using a synthesized voice. Text is when the AI agent responds to a query and produces a textual reply. A chat is similar to text except it generally represents a number of short message exchanges between the user and the computer in near real-time. Some of the most well-known examples of conversational AI systems in use today are the digital assistants such as Amazon Alexa, Apple Siri, Google Assistant and IBM Watson.
Benefits of Conversational AI
Conversational AI systems can achieve numerous benefits over traditional computer systems including;
- Voice can be a more efficient and convenient way to interface with machines.
- A more intelligent system that can extract user intents then evaluate and determine correct responses without have to be pre-programmed for every condition or user utterance.
- There are numerous business advantages to using a conversational AI system including achieving a consistent (and hopefully better) customer experience, a contact less customer experience, increases efficiency, reduction in operational costs and consistent up-selling opportunities.
The Turning Test
1950 Allen Turning proposed a method of inquiry to determine whether a computer is capable of thinking liking a human being. His original work hypothesized that a computer could mimic human responses under specific conditions. This idea eventually evolved into what is now called the Turing test. The Turning Test is benchmark for Conversational AI system to evaluate how well it responds and mimics the responses of a human, such that it become indistinguishable from a real person to fulfill a specific task. If the user can not tell if the responses are coming from a real person or a computer. The system has “passed” the Turning Test.
Notable Dates in Conversational AI History
When PARRY met ELIZA
In 1966 Joseph Weizenbaum developed Eliza. Eliza was programmed to respond to a number of keywords and produce responses that mimicked a psychotherapist. In 1972 Kenneth Colby developed Parry. Parry was program to model the behavior of a paranoid schizophrenic. In January 1973, as part of a international computer conference ELIZA and PARRY were connected together using the ARPNET. ELIZA was located at MIT and PARRY was at Stanford. Below is a transcript of their conversation.
Transcript of ELIZA and PARRY conversation
ELIZA: Good Evening. Tell me your problems.
Please terminate input with a period or a question mark.
PARRY: People get on my nerves sometimes.
ELIZA: I am not sure I understand you fully.
PARRY: You should pay more atten