Passed the Turing Test: Living in Turing Futures
This is an incremental analysis of AI capabilities in relation to the Turing test, relevant for researchers and philosophers in AI ethics and theory.
The paper argues that current generative AI models, such as transformers, can pass the Turing test by appearing human-like in conversation, but notes that Turing originally envisioned 'child machines' that learn naturally like humans to achieve this.
The world has seen the emergence of machines based on pretrained models, transformers, also known as generative artificial intelligences for their ability to produce various types of content, including text, images, audio, and synthetic data. Without resorting to preprogramming or special tricks, their intelligence grows as they learn from experience, and to ordinary people, they can appear human-like in conversation. This means that they can pass the Turing test, and that we are now living in one of many possible Turing futures where machines can pass for what they are not. However, the learning machines that Turing imagined would pass his imitation tests were machines inspired by the natural development of the low-energy human cortex. They would be raised like human children and naturally learn the ability to deceive an observer. These ``child machines,'' Turing hoped, would be powerful enough to have an impact on society and nature.