About ELIZA
The earliest examples of a chatbot dates back to the mid-1960s with the project ‘Eliza’, a significant program in the history of artificial intelligence and computer science. This program, developed by Joseph Weizenhaum, was initially created as an experiment to demonstrate the superficiality of communication between humans and machines.
ELIZA was most famous for a script called "DOCTOR", which allowed it to emulate a Rogerian psychotherapist. It used pattern matching and substitution methodology to simulate conversation. It engaged users in a conversation, mainly by rephrasing the user's statements and posing them back as questions. This technique allowed ELIZA to give an illusion of understanding, though it had no built-in framework for contextualizing or understanding conversations.
ELIZA is considered one of the first programs capable of passing the Turing Test , making people believe they were conversing with a human. It was a foundational program in the field of natural language processing (NLP) and influenced the development of later AI chat systems. The program led to discussions about the ethical implications of machines imitating human conversation and the psychological impact on users who might form emotional attachments to or misinterpret the abilities of these systems.
The ELIZA effect
Despite its innovative design, ELIZA had no understanding of the content of the conversations. Its responses were purely mechanical and based on the input's surface characteristics. Weizenbaum himself became a critic of the over-interpretation of ELIZA's capabilities, warning against the overuse and misuse of such technology.
The "ELIZA effect", named after this program, refers to the phenomenon where users interacting with any computer program attribute more understanding and intelligence to the system than it actually possesses, the same point Weizenbaum himself was trying to make.
This is significant in the field of AI as it demonstrates the principle of using social engineering, rather than explicit programming, to pass a Turing test. The Turing Test, developed by Alan Turing in 1950, is a method to evaluate a machine's ability to exhibit human-like intelligence. It involves a human judge engaging in a conversation with both a human and a machine, without knowing which is which. If the judge can't distinguish the machine from the human, the machine passes the test.
As mentioned previously, ELIZA managed to convince some users that a machine was human, marking a significant milestone in human-machine interaction but also foreshadowing the misunderstanding many users may make using future chatbots. Examples of the ELIZA effect in modern times include attributing human traits such as genders and personalities to AI voice assistants, believing that text-based chatbots have real human emotions, and even falling in love with these chatbots. This tendency to anthropomorphise extends beyond computers and is a common human behaviour. For more detailed examples, click the ‘CASE STUDIES’ section.
The ELIZA effect also highlights the potential dangers of overestimating AI systems' intelligence, which can lead to excessive trust and acceptance of misinformation. Sophisticated chatbots, like ChatGPT, can occasionally output incorrect information that is eloquently presented, leading users to accept it as truth. Additionally, recent AI experts such as Professor Mike Wooldridge, advises caution when sharing personal information with chatbots like ChatGPT, warning that such data could be used to train future AI versions. He emphasises that AI lacks empathy and consciousness, a perspective that aligns with the ELIZA effect where people may overestimate the understanding and capabilities of AI systems.