Phil 1.27.2023

Overconfidently conspiratorial: Conspiracy believers are dispositionally overconfident and massively overestimate how much others agree with themGordon Pennycook, David G. Rand

  • There is a pressing need to understand belief in false conspiracies. Past work has focused on the needs and motivations of conspiracy believers, as well as the role of overreliance on intuition. Here, we propose an alternative driver of belief in conspiracies: overconfidence. Across eight studies with 4,181 U.S. adults, conspiracy believers not only relied more intuition, but also overestimated their performance on numeracy and perception tests (i.e. were overconfident in their own abilities). This relationship with overconfidence was robust to controlling for analytic thinking, need for uniqueness, and narcissism, and was strongest for the most fringe conspiracies. We also found that conspiracy believers – particularly overconfident ones – massively overestimated (>4x) how much others agree with them: Although conspiracy beliefs were in the majority in only 12% of 150 conspiracies across three studies, conspiracy believers thought themselves to be in the majority 93% of the time.
  • I think this could have an effect on stampede behavior more broadly. Something to the effect that when rulers (people with dominant power over others) are overconfident, they can more easily head in the direction of social realities (e.g. conspiracy theories, but also that VW could get away with cheating on emissions, or that the USA would not fail in Afghanistan).
  • Overconfidence is a sort of dimension reduction since there is no need to look for complicated, nuanced positions. The most emotionally attractive answer is selected for and concentrates the overconfident.
  • An implication for diversity injection is that the “landing page” for diversity has to be simple and emotionally attractive.

Science has finally cracked the mystery of why so many people believe in conspiracy theories (Business Insider article on the above)


  • Schedule physical
  • See if my glasses are ready
  • Chores

GPT Agents

  • Wire up the loading of generator and embedding params. Maybe while I’m at it, read in a file with prompts and params? Done!
  • Had a thought that rather than clustering, I could just work on distances and the number of connections at that distance. Too many connections is a node like “the”, and nodes with only two connections (the predecessor and successor in the narrative) may not be that interesting and could be discarded. Something to think about.
  • Continue reading GPT-index documentation
  • How Cohere Works with Google’s Vertex Machine Engine to Power Embeddings
    • We’ve put together a notebook on GitHub to help you learn how to create embeddings with the Cohere API and then leverage the Vertex AI Matching Engine to create and query an index. The notebook includes code samples and step-by-step instructions for using the Cohere Embed endpoint to quickly capture semantic information about input data, and then applying the Vertex AI Matching Engine’s Approximate Nearest Neighbor (ANN) service to find similar texts.


  • Send Lauren the ppt to pass on
  • 11:00 presentation – DONE!
    • Re-read the rationale from the paper
    • Have the paper open in as a PDF
  • More editing and tweaking