> In a listening session with instructors, we learned that some were considering using AI agents as research assistants instead of hiring undergraduates as UROPs.
If researchers at a well funded institution like MIT are seriously considering replacing hiring undergrads with LLMs, I can just imagine how researchers at schools with less funding are open to it. I never did research as part of my undergrad (something I regret, but I likely wasn’t in the headspace for it back then) but my friends who have viewed it as a core part of their education and deeply helpful for future opportunities. I really hope schools come up with a policy to help discourage this.
I think you can tell who still has the ability to read long form content by whether they thought this was full of fluff or decently actionable. I think the bolded parts of section 3 are definitely not fluff. I found the document pretty interesting.
It can be both full of fluff and have actionable take aways.
This is dozens of pages long and reading it thoroughly will net you maybe a dozen useful sentences. That ratio is the problem people are complaining about.
I think this has been going on well before AI or LLMs: "A fundamental danger, as we’ve discussed, is that AI can allow students to bypass learning. Equally concerning is that students may internalize a transactional model in which assignments are outputs, teachers are evaluators, peers are optional, and knowledge (or an MIT degree) is an optimizable commodity to be acquired or produced as efficiently as possible."
Absolutely; it's a real problem. But institutions like MIT have also been participating in, and benefiting from, this transactional relationship from their side in offering degrees that they know carry so much value.
I'm surprised at the negative comments here. I'm about halfway done reading the report - I think it's clear, well written, and quite frankly the opposite of fluff.
A document like this isn't going to magically "solve" the use of AI in higher education. The purpose is to define a shared understanding of the situation across a large, complex organization, and set an initial direction and general shape for actions to take.
It contains clear, specific observations of how AI is organically changing the reality of education. And, in my opinion, fairly clear high-level guidance on what MIT as an entity wants to do about AI, and what individual departments and faculty should decide on their own.
A document like this doesn't need to be revolutionary, it may feel like fluff because no specific item in it is particularly surprising or groundbreaking, but the value is in having the entire document as a whole. And it is a lot more comprehensive and well thought out than what most companies can put out.
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.
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."
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)
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.
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.
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.
You can think what you like about MIT, but at least they're giving it some thought, however perfunctory it may seem. Many German universities prefer to try and ignore the issue and hope for the best.
Tell us more about how MIT giving AI some thought compares superiorly to 'many German universities', and please tell us more about which German universities and in which circumstances.
My statement was more of a dig at German universities than a compliment to MIT. I understand your criticism of this institution (which doesn't even exist in that form in Germany), but that doesn't mean I have to reflexively condemn everything from there.
I do like that they're open to reconsidering the grading paradigm wholesale. I taught at a boot camp for a while and our highest-placed cohorts were the ones to whom we gave neither grades nor certificates. They plainly understood the game was between them and an eventual interviewer, not them and the school or instructor.
I'm sick and tired of hearing about how LLMs are somehow going to cultivate a society of "creative people full of ideas" when increasingly the people who are using it the most are accepting the LLMs ideas without question.
To be fair, the US education system has long been "cooked" due to policies implemented many decades ago now to sacrifice excellence, exceptionalism, and true merit for engineered social stability and ruling class profiteering and plunder.
AI is an opportunity to improve true education and learning on an individual and community level based on free association without the authoritarian and violent hand of government imposing lowest common denominator uniformity on everyone to produce uniform and manageable, profitable pseudo-citizen cogs.
> In a listening session with instructors, we learned that some were considering using AI agents as research assistants instead of hiring undergraduates as UROPs.
If researchers at a well funded institution like MIT are seriously considering replacing hiring undergrads with LLMs, I can just imagine how researchers at schools with less funding are open to it. I never did research as part of my undergrad (something I regret, but I likely wasn’t in the headspace for it back then) but my friends who have viewed it as a core part of their education and deeply helpful for future opportunities. I really hope schools come up with a policy to help discourage this.
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I think you can tell who still has the ability to read long form content by whether they thought this was full of fluff or decently actionable. I think the bolded parts of section 3 are definitely not fluff. I found the document pretty interesting.
It can be both full of fluff and have actionable take aways.
This is dozens of pages long and reading it thoroughly will net you maybe a dozen useful sentences. That ratio is the problem people are complaining about.
I think this has been going on well before AI or LLMs: "A fundamental danger, as we’ve discussed, is that AI can allow students to bypass learning. Equally concerning is that students may internalize a transactional model in which assignments are outputs, teachers are evaluators, peers are optional, and knowledge (or an MIT degree) is an optimizable commodity to be acquired or produced as efficiently as possible."
Ok, but did AI and LLMs make the cheating easier, faster, harder to detect? Whatabout the past doesn't change the problems now.
"My leg already had a cut on it. No need to worry about the new stab wound in my chest!"
Absolutely; it's a real problem. But institutions like MIT have also been participating in, and benefiting from, this transactional relationship from their side in offering degrees that they know carry so much value.
2 replies →
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I'm surprised at the negative comments here. I'm about halfway done reading the report - I think it's clear, well written, and quite frankly the opposite of fluff.
A document like this isn't going to magically "solve" the use of AI in higher education. The purpose is to define a shared understanding of the situation across a large, complex organization, and set an initial direction and general shape for actions to take.
It contains clear, specific observations of how AI is organically changing the reality of education. And, in my opinion, fairly clear high-level guidance on what MIT as an entity wants to do about AI, and what individual departments and faculty should decide on their own.
A document like this doesn't need to be revolutionary, it may feel like fluff because no specific item in it is particularly surprising or groundbreaking, but the value is in having the entire document as a whole. And it is a lot more comprehensive and well thought out than what most companies can put out.
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.
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
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)
3 replies →
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:
> 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.
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 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.
5 replies →
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.
> This is a bunch of fluff.
Accurate description.
“Boy, these guys are just [your typical Bill Lumberghs] with upper management written all over them.”
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
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'm shocked, shocked, that they recommend hiring more administrators and forming more committees to study the problem.
You can think what you like about MIT, but at least they're giving it some thought, however perfunctory it may seem. Many German universities prefer to try and ignore the issue and hope for the best.
I mostly think about what they did to Aaron Swartz.
Regarding Swartz, I agree, but those are two different things. My statement was also more about the avoidance of the topic at German universities.
They also formed committees and investigated after the fact back then!
1 reply →
This seems to have touched a nerve, based on the number of downvotes.
In this particular case that makes the message more trustworthy for me ;-)
How is this interesting? Sincerely?
Tell us more about how MIT giving AI some thought compares superiorly to 'many German universities', and please tell us more about which German universities and in which circumstances.
My statement was more of a dig at German universities than a compliment to MIT. I understand your criticism of this institution (which doesn't even exist in that form in Germany), but that doesn't mean I have to reflexively condemn everything from there.
2 replies →
I do like that they're open to reconsidering the grading paradigm wholesale. I taught at a boot camp for a while and our highest-placed cohorts were the ones to whom we gave neither grades nor certificates. They plainly understood the game was between them and an eventual interviewer, not them and the school or instructor.
There's no magic rule that you have to give grades. A few colleges don't and MIT doesn't for the (I think) first term.
"Be bold" by saying nothing of any interest. I have to agree that this is basically just fluff.
Anyone put it into pangram yet?
97% human-written
I guess prolific em-dashes is not considered a sign of LLM writing anymore.
8 replies →
- 2. Guiding Principles
- 2.1. Be humble
- 2.2. Be bold
- 2.3. Put humanity front and center
- 2.4. Lean into learning
- 2.5. Teach with intentionality
- 2.6. No one size fits all
- 2.7. Augmentation not automation
- 2.8. Think beyond the classroom and the campus
- 3. Recommendations
- 3.1. Adapt educational processes for an AI-aware world
- 3.1.1. Revisit course goals
- 3.1.2. Ensure durable learning through new course policies, structures, and forms of assessment
- 3.1.3. Emphasize experiential and project-based learning
- 3.1.4. Build structured in-person social learning into subjects
- 3.1.5. Preserve and expand out-of-class research and career experiences
- 3.1.6. Reconsider grades and incentives
- 3.1.7. Expand in-person spaces for labs and in-person evaluation
- 3.1.8. Provide AI use policies, with justification
- 3.1.9. Exercise caution with AI detectors and online exam platforms
- 3.1.10. Support responsible experimentation in the curriculum
- 3.2. Center people, community, and the residential experience
- 3.2.1. Define and communicate the value of residential education
- 3.2.2. Strengthen social connection and personal wellbeing
- 3.2.3. Encourage instructor disclosure around their own AI use
- 3.2.4. Teach effective, responsible, and ethical use of AI
- 3.2.5. Recognize and mitigate negative impacts of AI
- 3.2.6. Acknowledge AI use in theses and other research work
- 3.3. Build processes, teams, and tools for continuous reflection, iteration, and improvement
- 3.3.1. Establish an ongoing AI and education committee
- 3.3.2. Create school/college- or department-level AI Leads
- 3.3.3. Fund AI Fellows and an AI Implementation Team
- 3.3.4. Create an AI Pilot Fund
- 3.3.5. Provide ongoing training and instructor support
- 3.3.6. Develop metrics
- 3.3.7. Ensure equitable technology access
- 3.3.8. Protect sensitive data and preserve model choice
- 3.3.9. Establish privacy, logging, and auditing policies
- 3.3.10. Monitor AI costs and environmental impact
- 4. Conclusion
Was expecting something more concrete with a set of deliverables that can actually be acted on.
vibewashing
I'm sick and tired of hearing about how LLMs are somehow going to cultivate a society of "creative people full of ideas" when increasingly the people who are using it the most are accepting the LLMs ideas without question.
Reminds me of when the crypto people were saying system used almost exclusively for money laundering was going to facilitate a financial revolution.
It's like assuming that the advent of fast food will create a society of people who exercise and otherwise eat well, to balance it.
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Education is so cooked. In 10 years, people arent going to find it useful financially. The AI will be better at economically relevant thinking.
And there aren't enough hobbyist learners to sustain education at its current level.
I figure once it collapses I'll transition into being a tutor for some billionaire's kids at roughly triple my current salary. :)
Isn't that how Parasite starts?
To be fair, the US education system has long been "cooked" due to policies implemented many decades ago now to sacrifice excellence, exceptionalism, and true merit for engineered social stability and ruling class profiteering and plunder.
AI is an opportunity to improve true education and learning on an individual and community level based on free association without the authoritarian and violent hand of government imposing lowest common denominator uniformity on everyone to produce uniform and manageable, profitable pseudo-citizen cogs.