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AI Ethics, Impossibility Theorems and Tradeoffs - Chris Stucchio | Crunch 2018

CraftHub Events · talk · Watch on YouTube

AI safety, AGI & impactMachine learning & deep learningProbability & game theory

What it is

Chris Stucchio presents the ethical principles behind algorithmic decision making and shows with examples from lending, criminology and education that they cannot all be satisfied at once. The talk frames AI fairness as a set of quantitative tradeoffs.

Why Hacker News recommends it

HN cites it in algorithmic-bias threads for the impossibility result that an algorithm cannot be procedurally fair, group fair and maximally useful at once.

  • 2 people recommended it
  • 2 different months
  • 0 strong recommendations
  • first 2019, last 2021

What HN commenters said

  1. “found a video of his presentation if anyone else is interested.”

    Presentation expanding on the slide deck.

    dvtrn, 2019-01 · Recommendation · in “Alexandria Ocasio-Cortez Is Absolutely Right About Racist Algorithms”

  2. “it has some flaws but is a decent exploration of the problem space.”

    Decent exploration of fairness tradeoffs, despite some flaws.

    PeterisP, 2021-02 · Recommendation · in “Who Should Stop Unethical A.I.?”

Excerpts from Hacker News comments, linked to the originals. Summaries and labels were written by a language model from those comments.

Topics: ai ethics, impossibility theorems, bias, tradeoffs, machine learning

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