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Joined 3 years ago
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Cake day: June 15th, 2023

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  • You’re certainly welcome to your own opinion

    Why golly thanks

    Sure thing, friend.

    How? By asking their chatbot to verify each statement?

    Wow, you’re really failing on the reading comprehension tonight. This is explained in the immediately proceeding sentence to the one you quoted of mine which you either skipped or did not comprehend. That sentence is “even those with only a little bit of knowledge”. The student wouldn’t have to ask a chatbot. The student would already know enough domain knowledge of the example topic to know the LLM output is wrong.

    I’m not sure whats up with your abrasiveness tonight, but I’m not interested in it. Maybe tomorrow will be better. Have a nice night.


  • It doesn’t do anything better or in an innovative way,

    It does it in a very applicable way in the sense that these students will be encountering AI “in the wild” in the years to come. The ways and methods AI is wrong isn’t really identical to the way humans deceive. As an example, most humans won’t straight up manufacture a fake citation to prove a point where this is a commonplace action of factually wrong LLMs.

    In this way using AI to produce the content that students are assigned to criticise is much more useful and less costly than human generated content. I’m not saying that LLMs should be used exclusively to create the target content, but it would be equally wrong to use human generated target content exclusively because humans are wrong in different ways (and that content is much more costly to create).

    especially when accounting for the costs associated with AI.

    Are you talking about monetary costs or something more philosophical (ethical, environmental, sociological)? The monetary costs would be extremely cheap. Probably less than $10 in tokens for the entire curriculum for the AI generated content. The necessary human contributions would be significantly more expensive, likely tens of thousands of dollars. The human component is still absolutely necessary, but it would be the far more monetarily expensive part.

    It is unnecessary to make a brand new round hole for this square peg.

    AI content students (when graduated into adults) have the evaluate is a new peg with a new shape. We can pretend its the same shape as the previous one and attempt to use the prior solution, but it will fail the education system and the students going through it arriving unprepared in the adult world rife with AI content that they will need to evaluate in their daily lives.









  • AI is anathema to teaching and learning.

    Your statement on its face value, sure I agree, but I can see a path were AI is a fantastic tool for teaching and learning critical thinking. If the teacher is able to alter the “temperature” setting of the LLM, they could crank it all the way up to 1 (meaning full creativity) which will likely induce AI hallucination.

    The AI LLM can create output which can speak to a topic but even those with only a little bit of knowledge can easily see the flaws in the AI response. It would give the student a chance to see how rational sounding output can be factually wrong. It would teach students to evaluate the statements individually and tease out logical fallacies or even outright manufactured falsehoods.

    Further, if the teacher can again set the temperature lower (perhaps to .7) which reduces the creativity then the LLM output would be more factual with possible logical or factual errors. This would increase the difficulty on the students to be able to inspect what they are given as LLM output and explore the tools and resources available to provide a human check on not only AI, but anything that another human says too.

    It can become an excellent tool for teaching critical thinking.

    EDIT: The more I’m thinking about this, the better I see this as a teaching tool. Tests students take to cover the material can be teacher created questions accompanied with a completely AI generated answer and the question to the student is “Is this true or bullshit? If bullshit, which parts are wrong?”. Every question on the entire test could use that format. It would be a great test of the student because they’d have to know the material well enough to know where the LLM produced a “right sounding answer” but was in fact, wrong. Even better, if a student tried to cheat using their own AI to answer the “bullshit or not?” question there’s an even higher chance the students cheating LLM would give a wrong answer because of the repeated Error Cascade.




  • If that doesn’t happen here, I can’t think of a valid reason to keep her over someone willing to do reforms.

    Politically this is gift to Mamdani that she holds the position:

    • He didn’t appoint her, so he has low risk of keeping her
    • It can make him look apollitical that he is willing to keep on staff from the previous administration and not act purely on political grounds
    • He earns political points, influence, and support from the rich family because he did not remove her
    • She knows she has a political target on her back, so she’s incentivized to keep him happy carrying out his mandates
    • When NYPD has a scandal, he can immediately point to her, and her leadership, and fire/prosecute her for it
    • When the removal finally does happen he’ll score points with his base for removing yet another relic of the Adams administration and be able to appoint a reformer



  • It’s got a mount where you can stick a phone or tablet if you want, but nothing built-in.

    I’m not sure how that will be road legal in the USA because after the passage of a law in 2018 all vehicles under 10,000 lbs require a backup camera.

    “Today’s final rule requires all vehicles under 10,000 pounds, including buses and trucks, manufactured on or after May 1, 2018, to come equipped with rear visibility technology that expands the field of view to enable the driver of a motor vehicle to detect areas behind the vehicle to reduce death and injury resulting from backover incidents. The field of view must include a 10-foot by 20-foot zone directly behind the vehicle. The system must also meet other requirements including image size, linger time, response time, durability, and deactivation.”

    source