This is a bunch of fluff. I hope at least the snacks and lunches during the discussions were good.
"Guiding principles: Be bold. Be humble. Put humanity front and center. Lean into learning. Teach with intentionality. No one size fits all."
"Recommendations: Adapt educational processes for an AI-aware world. Center people, community, and the residential experience. Build processes, teams and tools for continuous reflection, iteration, and improvement"
Yes, but as a K-12 administrator, I sadly have to tell you this is just about one of the more substantive things I have seen.
Yes, it's 95% fluff, but there is a real admission here that the guidance really ought to accept that there will be a whole host of tasks/assignments that kids engage in where the assumption SHOULD be that they basically will leverage AI, and that for their own benefit, resources should be set aside to promote experiences -- both in the context of assessments but also even in the social sphere -- there the influence of AI will be very purposefully prevented.
That is an actual stake in the ground, I think (as far as it goes in context like this). I think I would have been hard-pressed to have predicted that there would be such a revolutionary technology where the explicit ask of MIT faculty would be to prevent its influence in the school.
It will only get harder. From the trenches in tech it’s hard enough to get people who should know better to put in the work to understand the ai output.
For education I can’t imagine. You might have to resort to actual discussion in classrooms instead of homework, with the accompanying need for both more educators and higher quality therein. Which isn’t going to be easy when education is fully under regulatory capture (at least for K-12 in the USA)
K-12 means the public school system in USA & canada. It consists of kindergarten, elementary , middle and high schools, encompassing 12 grades/classes, each taking one year to complete.
Maybe it just requires approaching the problem differently. What about the vulcan study pod things? Have the discussion with the AI itself. Have the AI regularly assess understanding.
So this is an alternative that I actually don't object to at all, but you still need to create mechanisms where you then get at the quality of the mental models formed without the assistance of AI. My (very unpopular) hot take is that some of this will actually usher in a new era of "standardized test"-like things; we will be far more permissive about how/in what ways students/professionals acquire knowledge, and the real task will now shift from that to guaranteeing that there is some competency that was reached with the assurance that it isn't masked by an outside influence.
If you basically assume that everyone can and will cheat at all times, then you can let yourself be far more agnostic about it AS LONG as you are confident in some ability to measure the person's skill without the tools.
The interesting thing is that ai actually helps me learn more effectively than ever before. Each session can become a personalized little seminar that dynamically tests me as it presents ideas and concepts and I attempt to apply and extend them.
I think we need to move past recall as the test itself, and tasks as the gate we judge academic achievement by. These were only ever an approximate measure, which is why we still have things like thesis defenses.
But imagine the final being an interview with an agent that is designed to probe your mastery? From my experience so far it seems we could measure much more directly the educational outcome and also accelerate the learning at the same time. But this assumes those involved want to learn, which widespread cheating suggests is not the case. Maybe the real answer is that we shouldn’t attempt to force curiosity but instead cultivate it where we find it, allowing those who reject it to be redirected until they find something engaging.
I really do worry for our younger students - and I don't envy your job at all.
It seems as if all of teaching and student evaluation needs to be rebuilt from the ground up with AI as a default assumption.
Local high schools have added in class timed, hand written, essays for classes like AP US History.
I particularly like Chicago Law School's policy on AI.
E.g. Law students writing a "Substantial Research Paper" will have to defend it orally: "We will be adding one additional requirement, which is that all students will be required to engage in an oral discussion of their SRP with their supervising professor, in an in-person setting. This discussion will occur after a complete draft (or final version) of the paper has been submitted to the professor. The discussion could take place one-on-one, or as a class presentation in the style of an academic workshop. Either way, the oral exchange will involve the student answering questions that probe the reasoning of the paper and the implications of its arguments."
I thought the recommendations in section 3 were substantiative. That is move away from time-bound exams and move towards semester length project portfolios.
>"In the era of AI, some traditional learning goals may merit rethinking; for example, do the majority of our students need to be able to write complex programs by hand?"
>"quick, high-stakes evaluations embody the opposite of the signal we want to convey to them right now."
>"We urge instructors to consider forms of assessment that are less vulnerable to AI, and more valuable for learning, such as oral exams, semester portfolios, and out-of-class assignments paired with in-class conversations. This likely means resources such as TAs and class time will become more central to evaluation."
Project-based learning is not a new idea. However, it is precisely the sort of assessment strategy that is being attacked by AI: students can complete many projects fully using AI without learning anything about the underlying material.
In general, project/lab courses are pretty useƒul even iƒ they need some lecture/theory tacked on. Certainly, in school, I found hands-on and other project work, both individually and in groups, some of the better course work I did.
I don't agree? By the time you get to the specific policy sections (3.x.x) there are concrete changes outlined in bold, several of which are requests for the institute to invest large amounts of resources changing the current teaching process. Even the non-bolded text occasionally contains real insights, like this gem from the end of 3.1.9:
Students should not feel policed. Durable change will require instructors to be as clear as possible about their expectations and students to understand AI misuse as an unacceptable deviation from shared peer norms and community values rather than a violation of an arbitrary bureaucratic rule.
I immediately forwarded 3.3 to a colleague (AD of Research). We have a blanket policy document at the institutional level to establish a framework for baselines, but it's absent of any practicable guidance outside of a general approval process and expectations for academic honesty.
All concerns, while the real goal is stated right in the article:
"With this new approach, he says, experts in many fields can gain a deeper understanding of AI so they can better harness it. Meanwhile, computing experts are gaining greater exposure to the work of their counterparts in other fields. That exposure is giving the technologists a better understanding of how to create and train AI tools to better serve others."
I'm sure they will have many meetings about future meetings.
These things don't lead to anything other than a rich guy getting his name on a building, and more corruption in academia. By far the best thing which could happen to MIT would be for 95% of the endowment to go up in a poof of smoke, bringing it back to nineties levels. That's the end of the period when the Institute did high-integrity research.
No, today institutions like Georgia Tech -- which has an endowment of just about the same as MIT in the nineties adjusted for inflation -- seem to function just about the same way as MIT did back then.
I want to get back to the era before people went to MIT as a center of wealth, power, and prestige, and would lie and cheat to get tenured positions there, to where it was a place where nerds went to nerd together.
And to a place where every !@#$% done didn't lead to a self-hyping press release, but where statements were precise, measured, calibrated, and most importantly, scientifically-accurate.
Anywhere the nerds or artists go, if they are good, eventually becomes overrun with such types. Just look at the state of Silicon Valley and y combinator, and gentrification in general…
It's going to be difficult not to be "fluffy" as no one really knows the true impact and what's going to happen. And it's especially challenging for universities as voices questioning the value of higher education will only grow louder.
I grew up with PC‘s starting with DOS 1.0. I built a career as a systems engineer, basically by being confronted with thousands of problems that took four hours to figure out because the Windows world was changing so fast there was no documentation to easily find your answer. Those same problems now take me five minutes to figure out by using AI, so I’m able to move onto the next challenge and learn the next thing. That’s one aspect that I think isn’t well recognized in the anti-AI mindset.
That fact, multiplied over 1000 different disciplines, is one of the ways that AI is going to bring amazing progress to our world.
Comments
This is a bunch of fluff. I hope at least the snacks and lunches during the discussions were good.
"Guiding principles: Be bold. Be humble. Put humanity front and center. Lean into learning. Teach with intentionality. No one size fits all."
"Recommendations: Adapt educational processes for an AI-aware world. Center people, community, and the residential experience. Build processes, teams and tools for continuous reflection, iteration, and improvement"
Yes, but as a K-12 administrator, I sadly have to tell you this is just about one of the more substantive things I have seen.
Yes, it's 95% fluff, but there is a real admission here that the guidance really ought to accept that there will be a whole host of tasks/assignments that kids engage in where the assumption SHOULD be that they basically will leverage AI, and that for their own benefit, resources should be set aside to promote experiences -- both in the context of assessments but also even in the social sphere -- there the influence of AI will be very purposefully prevented.
That is an actual stake in the ground, I think (as far as it goes in context like this). I think I would have been hard-pressed to have predicted that there would be such a revolutionary technology where the explicit ask of MIT faculty would be to prevent its influence in the school.
It will only get harder. From the trenches in tech it’s hard enough to get people who should know better to put in the work to understand the ai output.
For education I can’t imagine. You might have to resort to actual discussion in classrooms instead of homework, with the accompanying need for both more educators and higher quality therein. Which isn’t going to be easy when education is fully under regulatory capture (at least for K-12 in the USA)
Which works in some contexts; I've taken seminars.
Not sure how that works with a multi-hundred person core calculus, physics, or chemistry class.
They did say k-12.
K-12 means the public school system in USA & canada. It consists of kindergarten, elementary , middle and high schools, encompassing 12 grades/classes, each taking one year to complete.
Maybe it just requires approaching the problem differently. What about the vulcan study pod things? Have the discussion with the AI itself. Have the AI regularly assess understanding.
So this is an alternative that I actually don't object to at all, but you still need to create mechanisms where you then get at the quality of the mental models formed without the assistance of AI. My (very unpopular) hot take is that some of this will actually usher in a new era of "standardized test"-like things; we will be far more permissive about how/in what ways students/professionals acquire knowledge, and the real task will now shift from that to guaranteeing that there is some competency that was reached with the assurance that it isn't masked by an outside influence.
If you basically assume that everyone can and will cheat at all times, then you can let yourself be far more agnostic about it AS LONG as you are confident in some ability to measure the person's skill without the tools.
The interesting thing is that ai actually helps me learn more effectively than ever before. Each session can become a personalized little seminar that dynamically tests me as it presents ideas and concepts and I attempt to apply and extend them.
I think we need to move past recall as the test itself, and tasks as the gate we judge academic achievement by. These were only ever an approximate measure, which is why we still have things like thesis defenses.
But imagine the final being an interview with an agent that is designed to probe your mastery? From my experience so far it seems we could measure much more directly the educational outcome and also accelerate the learning at the same time. But this assumes those involved want to learn, which widespread cheating suggests is not the case. Maybe the real answer is that we shouldn’t attempt to force curiosity but instead cultivate it where we find it, allowing those who reject it to be redirected until they find something engaging.
I really do worry for our younger students - and I don't envy your job at all.
It seems as if all of teaching and student evaluation needs to be rebuilt from the ground up with AI as a default assumption.
Local high schools have added in class timed, hand written, essays for classes like AP US History.
I particularly like Chicago Law School's policy on AI.
E.g. Law students writing a "Substantial Research Paper" will have to defend it orally: "We will be adding one additional requirement, which is that all students will be required to engage in an oral discussion of their SRP with their supervising professor, in an in-person setting. This discussion will occur after a complete draft (or final version) of the paper has been submitted to the professor. The discussion could take place one-on-one, or as a class presentation in the style of an academic workshop. Either way, the oral exchange will involve the student answering questions that probe the reasoning of the paper and the implications of its arguments."
https://www.law.uchicago.edu/news/ai-strategy-statement
I thought the recommendations in section 3 were substantiative. That is move away from time-bound exams and move towards semester length project portfolios.
Project-based learning is not a new idea. However, it is precisely the sort of assessment strategy that is being attacked by AI: students can complete many projects fully using AI without learning anything about the underlying material.
In general, project/lab courses are pretty useƒul even iƒ they need some lecture/theory tacked on. Certainly, in school, I found hands-on and other project work, both individually and in groups, some of the better course work I did.
I don't agree? By the time you get to the specific policy sections (3.x.x) there are concrete changes outlined in bold, several of which are requests for the institute to invest large amounts of resources changing the current teaching process. Even the non-bolded text occasionally contains real insights, like this gem from the end of 3.1.9:
I immediately forwarded 3.3 to a colleague (AD of Research). We have a blanket policy document at the institutional level to establish a framework for baselines, but it's absent of any practicable guidance outside of a general approval process and expectations for academic honesty.
They have always dressed it up as concerned humanitarianism. They did it already with large donations in the past:
https://www.philanthropy.com/news/can-a-350-million-gift-cha...
All concerns, while the real goal is stated right in the article:
"With this new approach, he says, experts in many fields can gain a deeper understanding of AI so they can better harness it. Meanwhile, computing experts are gaining greater exposure to the work of their counterparts in other fields. That exposure is giving the technologists a better understanding of how to create and train AI tools to better serve others."
I'm sure they will have many meetings about future meetings.
Makes me sick.
MIT is so very, very overcapitalized.
These things don't lead to anything other than a rich guy getting his name on a building, and more corruption in academia. By far the best thing which could happen to MIT would be for 95% of the endowment to go up in a poof of smoke, bringing it back to nineties levels. That's the end of the period when the Institute did high-integrity research.
It sounds like you want a return to a time before a lot of the government research money coming to institutions like MIT was gutted.
No, today institutions like Georgia Tech -- which has an endowment of just about the same as MIT in the nineties adjusted for inflation -- seem to function just about the same way as MIT did back then.
I want to get back to the era before people went to MIT as a center of wealth, power, and prestige, and would lie and cheat to get tenured positions there, to where it was a place where nerds went to nerd together.
And to a place where every !@#$% done didn't lead to a self-hyping press release, but where statements were precise, measured, calibrated, and most importantly, scientifically-accurate.
Anywhere the nerds or artists go, if they are good, eventually becomes overrun with such types. Just look at the state of Silicon Valley and y combinator, and gentrification in general…
https://meaningness.com/geeks-mops-sociopaths
FWIW: I see this pattern each time I discuss MIT (drifting from the Institutional Propaganda partyline) on HN:
1. Upvotes
2. Time passes
3. Downvotes
I'm starting to suspect Institutional astroturf.
It's going to be difficult not to be "fluffy" as no one really knows the true impact and what's going to happen. And it's especially challenging for universities as voices questioning the value of higher education will only grow louder.
I grew up with PC‘s starting with DOS 1.0. I built a career as a systems engineer, basically by being confronted with thousands of problems that took four hours to figure out because the Windows world was changing so fast there was no documentation to easily find your answer. Those same problems now take me five minutes to figure out by using AI, so I’m able to move onto the next challenge and learn the next thing. That’s one aspect that I think isn’t well recognized in the anti-AI mindset.
That fact, multiplied over 1000 different disciplines, is one of the ways that AI is going to bring amazing progress to our world.
They have to do something. There's a cheating epidemic right now everywhere.
I think the axis of AI in Ed should be, use it to super-charge learning, while assessment should be impossible to outsource to AI.
Verbal exams.
Assessments are arguably the least important part related to post-secondary education.
Accurate description.
“Boy, these guys are just [your typical Bill Lumberghs] with upper management written all over them.”
What human writes, "This is not a moment for patches and duct tape."
Is that AI or just horribly clichéd writing?
Maybe JK Rowling?
I hope AI was used to generate those empty words. What a waste of human effort.
A bunch of highly paid administrators were hired to use AI to generate it.
Human slopality
I'm shocked, shocked, that they recommend hiring more administrators and forming more committees to study the problem.