Summary of A Hypothesis on Black Swan in Unchanging Environments, by Hyunin Lee et al.
A Hypothesis on Black Swan in Unchanging Environments
by Hyunin Lee, Chanwoo Park, David Abel, Ming Jin
First submitted to arxiv on: 25 Jul 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel approach is proposed in this paper to redefine and formalize the concept of “black swan” events, which are statistically rare occurrences with extremely high risks. The authors challenge the traditional view that these events only occur in unpredictable environments, instead suggesting that they can also arise from human misperception of value and likelihood in unchanging environments. The paper categorizes and mathematically formalizes different types of black swan events, including “spatial” ones, with the goal of developing algorithms to prevent such events by correcting human perception. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study redefines what we think of as a “black swan event”. Normally, these are big surprises that happen when things are unpredictable. But this paper says that surprise can also come from our own mistakes – like misunderstanding how likely or valuable something is. The authors sort and explain different kinds of black swans, including ones that happen because of bad judgments. Their goal is to create tools to prevent these surprises by fixing our own mistakes. |
Keywords
» Artificial intelligence » Likelihood
