Attacking Discrimination in Machine Learning

Attacking Discrimination in Machine Learning

Imagine there's an important decision to be made about someone, like a bank deciding whether to extend a loan, or a school deciding to admit a student--unfortunately, we're all too aware that discrimination can sneak into these situations (even when everyone is acting with the best of intentions!). Now, these decisions are often made with the assistance of machine learning and statistical models, but unfortunately these algorithms pick up on the discrimination in the world (it sneaks in through the data, which can capture inequities, which the algorithms then learn) and reproduce it. This podcast covers some of the most common ways we can try to minimize discrimination, and why none of those ways is perfect at fixing the problem. Then we'll get to a new idea called "equality of opportunity," which came out of Google recently and takes a pretty practical and well-aimed approach to machine learning bias.

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Avsnitt(321)

Understanding AI Text Watermarking

Understanding AI Text Watermarking

Anthropic just announced they're baking invisible watermarks directly into Claude's generated text — and while everyone else was busy having opinions about it, we were busy asking the more interesting...

24 Aug 29min

Better Know a Benchmark: Humanity's Last Exam

Better Know a Benchmark: Humanity's Last Exam

Humanity's Last Exam was designed with a bold premise: questions that human experts can answer, but AI models can't. Originally dubbed "Humanity's Last Stand," this benchmark is a massive academic col...

17 Aug 23min

A Scientific Deep Dive into Overconfident LLMs: Interview with Kaitlyn Zhou (Cornell)

A Scientific Deep Dive into Overconfident LLMs: Interview with Kaitlyn Zhou (Cornell)

When a language model tells you it's absolutely certain, is it actually more likely to be right? Kaitlyn Zhou's research says: not necessarily — sometimes confident phrasing correlates with *worse* ac...

10 Aug 33min

Reasoning Models: When LLMs Went Beyond Fancy Autocomplete

Reasoning Models: When LLMs Went Beyond Fancy Autocomplete

Reasoning models don't just answer your question — they *think out loud* first. In this episode we dig into the class of AI models that generate intermediate chains of thought before arriving at a fin...

3 Aug 25min

Distillation, or, How to Steal a Model

Distillation, or, How to Steal a Model

This week we’re covering model distillation: the technique of using a large "teacher" model's outputs to train a smaller, cheaper "student" model that mimics it. They cover the two big reasons labs do...

27 Juli 23min

Invisible LLM Failures and AI Fluency with Chris Potts (Stanford)

Invisible LLM Failures and AI Fluency with Chris Potts (Stanford)

What happens when a Stanford linguistics professor turns his attention to AI chatbots — and the surprisingly invisible ways humans misunderstand them? Chris Potts joins the show to unpack the hidden f...

20 Juli 41min

Still summer break: back next week

Still summer break: back next week

Still summer break: back next week by Katie Malone

13 Juli 25s

Summer break: back soon

Summer break: back soon

Summer break: back soon by Katie Malone

6 Juli 36s

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