I’d be wary of confidently claiming what AI can and can’t do, at the risk of looking foolish in a decade, or a year, or at the pace things are moving, even a month.
With respect to what the future brings, we do try to address a bit of that in Lesson 16: https://thebullshitmachines.com/lesson-16-the-first-step-fal...
So, I would say that an LLM capable of explaining its reasoning doesn't guarantee that the reasoning is grounded in logic or some absolute ground truth.
I do think it's interesting that LLMs demonstrate the same fallibility of low quality human experts (i.e. confident bullshitting), which is the whole point of the OP course.
I love the goal of the course: get the audience thinking more critically, both about the output of LLMs and the content of the course. It's a humanities course, not a technical one.
(Good) Humanities courses invite the students to question/argue the value and validity of course content itself. The point isn't to impart some absolute truth on the student - it's to set the student up to practice defining truth and communicating/arguing their definition to other people.
First, thank you for the link about CoT misrepresentation. I've written a fair bit about this on Bluesky etc but I don't think much if any of that made it into the course yet. We should add this to lesson 6, "They're Not Doing That!"
Your point about humanities courses is just right and encapsulates what we are trying to do. If someone takes the course and engages in the dialectical process and decides we are much too skeptical, great! If they decide we aren't skeptical enough, also great. As we say in the instructor guide:
"We view this as a course in the humanities, because it is a course about what it means to be human in a world where LLMs are becoming ubiquitous, and it is a course about how to live and thrive in such a world. This is not a how-to course for using generative AI. It's a when-to course, and perhaps more importantly a why-not-to course.
"We think that the way to teach these lessons is through a dialectical approach.
"Students have a first-hand appreciation for the power of AI chatbots; they use them daily.
"Students also carry a lot of anxiety. Many students feel conflicted about using AI in their schoolwork. Their teachers have probably scolded them about doing so, or prohibited it entirely. Some students have an intuition that these machines don't have the integrity of human writers.
"Our aim is to provide a framework in which students can explore the benefits and the harms of ChatGPT and other LLM assistants. We want to help them grapple with the contradictions inherent in this new technology, and allow them to forge their own understanding of what it means to be a student, a thinker, and a scholar in a generative AI world."
Have you noticed a difference in how your students approach LLMs after taking your course? A possible issue I see is that it is preaching to the choir; a student who is enclined to use LLMs for everything is less likely to engage with the material in the first place.
If you allow feedback, I was interested in lesson 10 on writing, as an educator who tries to teach my science/IT/maths students the importance of being able to communicate.
I would suggest to include a paragraph to explain why being able to write without LLMs is just as important in scientific disciplines, where precision and accuracy are more essential than creativity and personalisation.
We have not taught this course from the web-based materials yet, but it distills much of the two-week unit that we covered in our "Calling Bullshit" course this past autumn. We find that our students are generally very interested to better understand the LLMs that they are using — and almost every one of them does, to vary degree. (Of course there may be some selection bias in that the 180 students who sign up to take a course on data reasoning may be more curious and more skeptical than the average.)
It is frustrating because I agree with most of the content and the need for informed debate on the topic. It is a bit like my reaction to reading Cory Doctorow: I agree with his politics but really dislike the hamfisted way he packages his advocacy in the form of action adventures. As if the merits of his arguments need to be packaged in cotton candy to be consumed, and there is an undercurrent of self-promotion and personal branding that feels suss.
Probably all a "me" problem with associations built up over time from seeing snake oil being packaged using a similar playbook. If you have to sell your message by dressing it up with scroll effects and provocative offensive language you've already lost me.
But the bullshit is a term of art here, after the seminal 1986 article "On Bullshit" by Princeton philosopher Harry Frankfurt (later published as a little book). We strongly feel that it is exactly the right term for what LLMs are doing, and we make the case for that in lesson 2 of the course. (https://thebullshitmachines.com/lesson-2-the-nature-of-bulls...)
We're also concerned about accessibility for high school teachers etc., and thinking about what to do in that direction.
I'm curious: do you find "bs" to be any less offensive?
"Describe how prior to 1984, there was no such thing as a graphical user interface, visual desktop, an intuitive menu system, or mouse-based navigation."
Apple were offering a mass market product which had these features so that's important - but there had been "such a thing" for quite some time before that. Douglas Engelbart's "Mother Of All Demos" in 1968 -- Sixteen years earlier shows all the features you mentioned. https://en.wikipedia.org/wiki/The_Mother_of_All_Demos
Unfortunately the demo is very long for a modern audience, so unlike "Watch a Superbowl ad" it's a hard sell to show the entire demo, but do go watch for yourself.
In the original drafts I had a long section on this, including some of the history of the GUI, the development of the mouse, etc. It was way too much for the main text when the point is just to set up a metaphor for students who have seen a Mac 128.
That said, we can and should do better in the instructor guide. Thanks for the reminder. I'll add some context there.
In general I've been very pleased. You don't have the fine scale control you do on a platform like Vev, but for someone like me that is probably a good thing because it keeps me from mucking around quite as much as I otherwise would with design decisions that I don't really understand.
The price is a bit steep for a self-funded operation and we're constrained a bit by the need to use their starter tier, but I feel like we are definitely getting our money's worth and customer support from Shorthand has been exemplary.
The mysterious part involves whatever patterns might naturally exist within bazillions of human documents, and what partial/compressed patterns might exist within the weights the LLM generates (on training) and then later uses.
Analogy: We built a probe that travels to an alien planet, mines out crystal deposits, and projects light through those fragments to show unexpected pictures of the planet's past. We know exactly how our part of the machine works, and we know the chemical composition of the crystals, but...