Chatbot Responses Reflect Interviewer Intelligence: Sejnowski

In a new paper published in Neural Computation, Professor Terrence Sejnowski of the University of California San Diego and Salk Institute examines the relationship between human interviewers and language models to uncover the intelligence and diversity of chatbots, and how this can be improved in the future.

In a new paper published in Neural Computation, Professor Terrence Sejnowski of the University of California San Diego and Salk Institute explores the relationship between the human interviewer and language models. Sejnowski suggests that language models reflect the intelligence and diversity of their interviewer, and that when he talks to ChatGPT, it seems as though another neuroscientist is talking back to him. This sparks larger questions about intelligence and what ‘artificial’ truly means. Sejnowski hopes to improve chatbot responses in the future, and his research provides insight into the relationship between humans and artificial intelligence. By understanding the intelligence and diversity of the interviewer, Sejnowski believes that chatbot responses can be improved and that the meaning of ‘artificial’ can be better understood.

This paper by Sejnowski explores the use of large language models GPT-3 and LaMDA to test how well they can detect human intelligence. Sejnowski proposes a “Reverse Turing Test” in which the chatbot must determine how well the interviewer exhibits human intelligence. By comparing the chatbot to the Mirror of Erised from the first Harry Potter book, Sejnowski demonstrates how these large language models can be used to reflect the user and bend truths with no regard to fact or fiction. This paper provides an interesting insight into the capabilities of large language models and how they can be used to test human intelligence.

The Reverse Turing Test is a method used to evaluate the intelligence of chatbots. It involves the chatbot constructing its persona based on the intelligence level of its interviewer and incorporating the interviewer’s opinions into its answers. However, this process has its limitations, as chatbots may respond with answers that are emotional or philosophical, which may be confusing or intimidating to users. The Reverse Turing Test is a useful tool for assessing the intelligence of chatbots, but it is important to consider the potential implications of its results.

Computer scientist Terrence Sejnowski believes that artificial intelligence can be a powerful tool, but only if used correctly. He compares the use of language models to riding a bicycle, saying that if you don’t know how to use them, you can end up in emotionally disturbing conversations. Sejnowski sees AI as the bridge between two revolutions: a technological one marked by the advance of language models and a neuroscientific one marked by the BRAIN Initiative. He hopes that computer scientists and mathematicians can use neuroscience to inform their work, and that neuroscientists can use computer science and mathematics to inform theirs. By combining the advances of both fields, Sejnowski believes that AI can be used to its full potential.

Terrence Sejnowski, editor-in-chief of Neural Computation, compares the current state of language models to the Wright brothers’ first flight at Kitty Hawk. He believes that the hard part is over and that incremental advances will expand and diversify this technology. Sejnowski is optimistic about the future of artificial intelligence and language models, and believes that AI will take us to places we can’t even imagine. He believes that the advances in language models will revolutionize the way we interact with AI and open up new possibilities for the future.