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.
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.
"My leg already had a cut on it. No need to worry about the new stab wound in my chest!"
"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, 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 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."
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.
>"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."> 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.
That fact, multiplied over 1000 different disciplines, is one of the ways that AI is going to bring amazing progress to our world.
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.
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.
1. Upvotes
2. Time passes
3. Downvotes
I'm starting to suspect Institutional astroturf.
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 !@#$% done didn't lead to a self-hyping press release, but where statements were precise, measured, calibrated, and most importantly, scientifically-accurate.
I think the axis of AI in Ed should be, use it to super-charge learning, while assessment should be impossible to outsource to AI.
Verbal exams.
Is that AI or just horribly clichéd writing?
Anyone put it into pangram yet?
No, I can't provide a cite. Insider information. But whistleblowers have been threatened with being "Shwartzed" since (e.g. have frivolous criminal charges filed, to make their lives hell). In every case I've seen, whistleblowers signed an NDA, a non-disparage, and backed down.
That's why I don't trust a !@#$% thing from MIT anymore. Lies and fraud get covered up. Once that starts happening, you can't trust anything.
In this particular case that makes the message more trustworthy for me ;-)
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.
I'm just ignorant to German universities. Honestly, the only thing I know of is not even University level German education, but just the concept of the German gymnasium system, and that was from when a exchange student visited my high school, in the 1990s!
Thanks for the response. Cheers.
To explain briefly:
Broadly speaking, there are these types of schools:
- Hauptschule (lower secondary school) - Realschule (intermediate secondary school) - Gymnasium (grammar school)
in various organizational forms. At a Gymnasium, you can obtain a full Abitur (university entrance qualification), which qualifies you to study at - Universities - Universities of Applied Sciences
For studies at Universities of Applied Sciences, a Fachabitur (subject-specific university entrance qualification) is necessary, which can be obtained in various ways. Previously, diplomas were usually awarded there, an academic degree between a B.A. and M.A. Since the Bologna reforms, the system has been changed to B.A./M.A.
At Universities of Applied Sciences, studies are more practically oriented (with practical phases); however, the biggest difference is that you cannot pursue a doctorate there, which is only possible at a "proper" university.
Besides social informatics, I also teach academic writing, which is why the topic of AI is important to me, because it's not easy for teachers to deal with. But I also don't think the strategy of simply looking away is effective.
- 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
And there aren't enough hobbyist learners to sustain education at its current level.
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.
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 did view 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.