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.
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.
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.
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.
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.
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:
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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.
"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.
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.
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.
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.
17 comments
[ 5.2 ms ] story [ 37.7 ms ] threadWe are hurling to a reality where the only noteworthy metric is human to human validation.
All to say—I wish it was this easy to change the academy. But it's not.
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.
Is that really the case though? It seems like quite a lot of cases get hushed up and swept under the rug.
---
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.
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.
https://htmx.org/essays/universities-and-ai/