# Passed the Turing Test: Living in Turing Futures

arXiv: https://arxiv.org/abs/2409.07656 · HTML: https://mlsanity.com/paper/2409.07656/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 20 references that are in the map.
- First posted on arXiv 11 Sep 2024.

## Builds on (most cited first, 4 of 4)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models](https://mlsanity.com/paper/2206.04615/) (2022)
- [Turing's Test, a Beautiful Thought Experiment](https://mlsanity.com/paper/2401.00009/) (2023)

## Abstract (arXiv)

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.