>>5434410>schizophrenic democracy, votingHere is a weird sci-fi thing I read about recently: how about some sort of cult movement or political party whose followers are directed by AI. (Did Alastair Reynolds write this sci-fi novel already? Neural implant voting, Demarchists, from Revelation Space?)
Some researchers explored the idea of using gpt-3 to conduct "Silicon Sampling" instead of getting real people to fill out online surveys or focus groups or Pew Research etc, why not stratify sample just text conversations and construct simulated people and demographics, and then interrogate that interface with gpt-3. Here is the link to that research paper
https://arxiv.org/abs/2209.06899 [Submitted on 14 Sep 2022]
Out of One, Many: Using Language Models to Simulate Human Samples
We propose and explore the possibility that language models can be studied as effective proxies for specific human sub-populations in social science research.
We show that the "algorithmic bias" within one such tool -- the GPT-3 language model -- is instead both fine-grained and demographically correlated, meaning that proper conditioning will cause it to accurately emulate response distributions from a wide variety of human subgroups. We term this property "algorithmic fidelity" and explore its extent in GPT-3. We create "silicon samples" by conditioning the model on thousands of socio-demographic backstories from real human participants in multiple large surveys conducted in the United States. We then compare the silicon and human samples to demonstrate that the information contained in GPT-3 goes far beyond surface similarity. It is nuanced, multifaceted, and reflects the complex interplay between ideas, attitudes, and socio-cultural context that characterize human attitudes. We suggest that language models with sufficient algorithmic fidelity thus constitute a novel and powerful tool to advance understanding of humans and society across a variety of disciplines.
