Jevin West and I are professors of data science and biology, respectively, at the University of Washington. After talking to literally hundreds of educators, employers, researchers, and policymakers, we have spent the last eight months developing the course on large language models (LLMs) that we think every college freshman needs to take.
https://thebullshitmachines.com
This is not a computer science course; it’s a humanities course about how to learn and work and thrive in an AI world. Neither instructor nor students need a technical background. Our instructor guide provides a choice of activities for each lesson that will easily fill an hour-long class.
The entire course is available freely online. Our 18 online lessons each take 5-10 minutes; each illuminates one core principle. They are suitable for self-study, but have been tailored for teaching in a flipped classroom.
The course is a sequel of sorts to our course (and book) Calling Bullshit. We hope that like its predecessor, it will be widely adopted worldwide.
Large language models are both powerful tools, and mindless—even dangerous—bullshit machines. We want students to explore how to resolve this dialectic. Our viewpoint is cautious, but not deflationary. We marvel at what LLMs can do and how amazing they can seem at times—but we also recognize the huge potential for abuse, we chafe at the excessive hype around their capabilities, and we worry about how they will change society. We don't think lecturing at students about right and wrong works nearly as well as letting students explore these issues for themselves, and the design of our course reflects this.
I was speaking to a friend the other day who works in a team that influences government policy. One of the younger members of the team had been tasked with generating a report on a specific subject. They came back with a document filled with “facts”, including specific numbers they’d pulled from a LLM. Obviously it was inaccurate and unreliable.
As someone who uses LLMs on a daily basis to help me build software, I was blown away that someone would misuse them like this. It’s easy to forget that devs have a much better understanding of how these things work, can review and fix the inaccuracies in the output and tend to be a sceptical bunch in general.
We’re headed into a time where a lot of people are going to implicitly trust the output from these devices and the world is going to be swamped with a huge quantity of subtly inaccurate content.
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