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  • Hacker News
  • How about we embrace the era of the superhuman?
  • What superhuman? This system will never have a 99.99% accuracy based on its current prediction models and data input, neither is it a targeted to make us superhumans in the first place.

    It still will need human supervision for corrections and if it doesn't it won't require humans to process further. Humans are not in the central picture of the future of AI.

  • It's not the era of the superman coming. It's the era of the sewers man.
  • I don’t think it has killed it per se. I think it’s a major shift and the long standing institutions were in equilibrium to where society was prior. It worked. Disruption came and quicker than ever. We are adapting much slower than we have before. This makes it seem bleak. Just like a market, we will reach an equilibrium again but it won’t be like before. We now have the opportunity to increase our learning velocity like never before. It’s important to distinguish between substitution and supplemental on where we go especially with AI.
  • On the flip side, the value of new, clever and repeatable experimental results goes up when compared to regurgitated publications.
  • Very much this. Very funny to see we're back to hardware is still hard.
  • "Yes, going back to paper and pencil strains our current resources, but is a likely necessity" -- When I reached this sad, arthritic point in the article it was clear that the author has no constructive idea about what happens next in education. There is no critical dialogue regarding assessment and its necessity. There is no critical understanding and projection for what intelligence as a service represents for society. Just a simple monastic shrug and a familiar scent of old world pencil lead.
  • It frustrates me that your comment is being down voted, because I agree with your sentiment.

    Too many educators don't actually know how to educate, and only focus on what to educate.

    LLMs are offering some ways to dramatically improve how people learn (and therefore how well they learn, what they learn,etc - to rapidly accelerate and improve outcomes). However most educators, who are ignorant to the principles of how people learn, have no idea how to harness that potential. The result is in most cases students are just using AI to sabotage their own learning, because no better alternative is being offered.

    It's a hard problem... But it's a shame that so few people are working constructively and pragmatically on it.

  • I wrote an essay about how I am handling AI in my CS courses:

    https://htmx.org/essays/universities-and-ai/

  • And I welcome the change. In my long experience in academia, I've only found two types of practitioners:

    1% are the absolutely brilliant minds that academia was originally created for. People that, without a doubt, leave their mark in the vast corpus of human knowledge. I consider myself fortunate for meeting and learning from them, and I thank the academia ecosystem for that.

    But the remaining 99% are the maximalists, as described in the article. More papers/students/grants, then repeat. Worse enough, they're absolutely useless outside of academia, as they never did anything at all outside that bubble.

    An embarrassing lot of CS professors would stumble around your average production codebase.

    I think AI is just the final nail in the coffin for the latter bunch, as they have been dogs eating their own tail for decades already.

  • > An embarrassing lot of CS professors would stumble around your average production codebase.

    As would be expected. The value of computer science has very little overlap with navigating a typical production code base.

  • I think it's very field dependant. In maths and biology I've seen very few professors that could reasonably be described as maximialists here; computer science really seems to be the outlier. My impression is that impactful CS professors tend to be more strongly associated with either maths, or the field that their cs research is being used in.

    Arts faculty on the other hand seem to basically just be a popularity competition.

  • I don’t believe that at all. Maybe it’s killed large lecture classrooms. There’s a lot of other ways to engage students and ensure they’re learning but it involves being more active and actually communicating with them instead of yapping lectures at them and making them write about it. I find most college classes that involved lectures to be a waste, why sit and listen to a teacher summarize a book for an hour? My best experiences were classes with active engagement and producing things in class or bringing them back to class to share discuss and learn.
  • I'm working on my PhD nonetheless. Here was a meditation of mine on the Literature Review that is relevant here:

    ---

    Academic literature (AL) predates the social media (SM) of recent decades. AL identifies and preserves human knowledge across time, space, language, andexperience level.

    These implicit "goals" contrast with SM's emphasis on the present moment, colloquial focus, idiomatic word choice, and general disregard for larger context beyond the. Therefore, when engaged in producing AL, a detached mindset seems helpful.

    One enters a discourse with people across the ages who were soberly adding to the sum of human knowledge, not pursuing SM "likes", and not regressing to the mean of some Artificial Intelligence corpus. AL seeks to cover the prior art, to honor those who came before, to minimize duplication of effort, and to filter the "novelty" out of ideas by detailing their pedigree.

    The writing style of AL targets a reader half a century in the future of unknown gender, nationality, and depth within either the topic or with the English language itself.

    Therefore, the writing style needs to favor:

    - Simplicity in word choice. Archaic words or definitions, however valid, are not preferred. Two or three shorter words is often easier on that unknown reader.

    - Linearity in development. No dramatic tension. Set the ideas in front of the reader and move through them in order.

    - Connectedness. The chain of the ideas is obvious as we move from one to the next, so that reiterating to remember the current topic is less necessary.

    - Cohesiveness. A paragraph should almost stand on its own, because it contains enough information to make its point even if quoted within another article.

  • The grant application process is wild now, half the questions I'm to respond to feel AI generated as well. I feel certain that the reviewers are just taking my responses and feeding them.into another AI to evaluate too.
  • Solving the paper submission is easy. Just hold frontal interview where the submitter defends their paper. They can't create papers every day and still be knowledgeable about them in depth.

    We are hurling to a reality where the only noteworthy metric is human to human validation.

  • With the volume of outputs in today's academia, this is simply not possible. There are conferences with tens of thousands of submitted papers, grants have hundreds of pages, etc.
  • Paper reviews are traditionally blinded, so the reviewer doesn't know the authorship of the paper they're reading.
  • If a journal finds that it's getting more papers than peer reviewers are willing to go through, how does a more heavyweight, synchronous review process solve the problem? Many researchers already find peer review requests annoying, they're not going to agree to hold a bunch of video calls.
  • I'm not as pessimistic about its impact on scientific publishing. Yes, you can churn articles faster, but if people catch you gaming this system to extreme lengths your reputation will take a huge hit. And the system is very transparent and visible, so it'll follow you forever.
  • > And the system is very transparent and visible

    Is that really the case though? It seems like quite a lot of cases get hushed up and swept under the rug.

  • Flip the classroom, make students learn the material on their own (Using AI or whatever resources they want to use) and then in-classroom time is divided on working on problems (without AI assistance which can be controlled in this environment) and quizzes/exams (again without AI). We don't need lectures anymore, they are an incredibly ineffective way to learn.
  • Yep. I've been using AI to teach myself system design and it's been a god send. Was struggling with other courses because I couldn't have it tailored to what I wanted.
  • I had a chat with my state legislators to streamline education; shift all public school and university funding to libraries staffed by SMEs

    Mandate N hours year of and guided group work for under 18s

    Mandate N hours for becoming an SME for roles that require such

    Break the pipeline from the factory era of linearly pumping out kids who are just smart enough to run the machines

  • You are right and this is the way, it's just a lot easier said than done, especially the quizzes/exams part.

    There is a tension between: - authentic assessments (not multiple choice/ - grading resources - computer lab availability - students using AI in very discreet ways on their own laptop when taking an in-person exam

    So overall you are on point, it's just really hard to do honest authentic assessment at scale right now (in person or otherwise).

    I see a potential for it to get much better, or much worse... Hard to tell which way it will go right now.

  • Lectures have been an incredibly ineffective way to learn forever. Faculty continue to lecture, and we continue to build lecture-style classrooms, further enshrining this poor approach. Active learning works, and yet both faculty and students dislike it. Faculty like to talk and pretend they're teaching, and students like to listen and pretend they're learning.

    All to say—I wish it was this easy to change the academy. But it's not.

  • I had some "reverse classroom" classes back in college, and it was the best kind of class for me. Read the papers on your own time before class, and spend class discussing and in tests.

    It did, however, absolutely require everyone to prepare for every class. Some people complained a lot about this, which might be why this was not as popular as more common lectures.