It is a College of Computing, not College of AI. Also note that MIT has Schools (School of Engineering, School of Science, etc.), not Colleges; so this will be something different.

For example, according to MIT's FAQ [2], EECS Department will likely continue to be part of School of Engineering, even as it becomes part of College of Computing.

In particular:

> The College will reorient MIT to bring the power of computing and AI to all fields of study at MIT, allowing the future of computing and AI to be shaped by insights from all other disciplines;

> Q: Why is this a college, rather than a school? What is the difference?

> A: The MIT Schwarzman College of Computing will work with and across all five of MIT’s existing schools. Its naming as a college differentiates it from the five schools, and signals that it is an Institute-wide entity: The College is designed with cross-cutting education and research as its primary missions.

> Q: What kinds of new joint academic programs or degrees are envisioned?

> A: MIT has been making progress in this direction for some time; for example, we already offer undergraduate majors that pair computer science with economics, biology, mathematics, and urban planning. The MIT Schwarzman College of Computing will allow MIT to respond to the student demand the Institute is seeing in course and major/minor selection more effectively and creatively. It will enable MIT to pursue this vision with unprecedented depth and ambition, and will give MIT’s five schools a shared structure for collaborative education, research, and innovation in computing and AI.

[1] http://news.mit.edu/2018/mit-reshapes-itself-stephen-schwarz...

[2] http://news.mit.edu/2018/faq-mit-stephen-schwarzman-college-...

Do you have a citation for this advance?

I wish they would take that $1 billion & invest it in modernizing online education. If you want to be a leader in AI, I argue you should open your doors to as many applicants as possible from all over the world at an affordable price. Discover a better way to improve collaboration & online learning. EdX & Coursera are nice but they seem to be halfhearted attempts. UNC's online MBA requires video conferencing for discussion & is much more engaging.

I guess $1 billion of server infrastructure & employees doesn't look as pretty though.

I believe that there are a few universities whose education is by far superior. If you can increase the amount of people receiving top education, you can increase those that can then go on to do research.

Getting into MIT is not easy. I imagine it is especially hard for those outside the US. The gatekeeper effect lowers the amount of people who can go on to become graduate students & researchers.

I'd imagine a more limiting factor is the a) willingness to work really hard for 6+ years for uncertain rewards for the joy of research with very low wages. especially when you can go into industry and make 100k+ b) student loans-see low wages as an academic.

As an academic in ML at least-I think there are more than enough academics in the field or trying to get here....look at NIPs submissions!

I am currently a CS grad student, I got started with computer science by watching MIT Open Courseware lectures.

The current education system is highly exclusionary based on characteristics that are obtained in high school and most of the characteristics are directly linked to income. The problem is many people can still go on to get these skills later in life but can't really get into MIT once they're adults. You can, in theory, but we all know in practice it is not realistic.

MIT and the other schools know if they gave away their core curriculum's online that are basically the same thing then less people would want to go to the school at the current over inflated rates. If you guys are looking for a revolution in online education, I hate to say it, but don't look at traditional institutions to do it.

The revolution in online education will be done by someone similar to a Steve jobs or Jimmy Wales (wikipedia) that basically has no connections to the traditional education industry but is just very motivated to change the world for the better. We all know that teaching is not rocket science (many people can teach it) and most of the significant human knowledge is being written down in books. The only exception is for the stuff that is cutting edge latest research but of course people aren't going to learn those topics until they've learned all of the other known subject matter on the topic which is recorded in books. So overall, the goal here is to simply take those books, produce free equivalents of them (the knowledge in the books are NOT subject to copyright) and then create some sort of online self-study system where people can learn the material. Tools need to be created that help people to learn the knowledge on their own and offer innovate tools to self-study.

Actually MIT undergrad tuition is about 14% of MIT's revenue and about 16% of expenses (all in, not just the teaching portion), numbers which have been remarkably stable over the last 30 years. Undergrads simply aren't that important to a major research institution like MIT which is better thought of as a big research lab with a small school attached (undergrads make up less than 20% of the personnel on campus).

> The big universities will NEVER give out high quality equivalents of their courses online... MIT and the other schools know if they gave away their core curriculum's online that are basically the same thing then less people would want to go to the school at the current over inflated rates.

Except Open Courseware (thank you Hal Abelson) is exactly that: typically everything handed out by the prof including syllabus, lecture notes, problem sets, clarification notes...everything! And videos of lectures in some cases. And the motivation was precisely the opposite of what you say: "we assembled this stuff; perhaps it's useful for you to make your own course too."

> If you guys are looking for a revolution in online education, I hate to say it, but don't look at traditional institutions to do it....The revolution in online education will be done by someone ... that basically has no connections to the traditional education industry but is just very motivated to change the world for the better.

Umm, maybe. Sadly, a big part of higher education is credentialism, and for that you need to tie back to institutions. And the big institutions have an interest in such experimentation for the standard big institutional reasons that are not specific to universities (the "satellite campus" system has worked for some big institutions like NYU, and their students in, say, Abu Dabi who never go to NY at all) and there's no reason to think that similar classes of experiments could happen via linkups like U of Il + Coursera).

But I agree that new entrants like Kahn are doing interesting experiments that might have a huge, benefit effect in the long run.

* I'm an MIT alum and former edX engineer.

You can get a “certificate” or some asterisked form of diploma, or you can enter the traditional applicant lotto where a significant number are rejected yet go on to do great work.

The old lotto model is based on the legacy of having enough seats to put students into.

Some newer programs, including one from MIT are experimenting with a scalable online model.

You want a degree from us? Take some classes for a while, prove your ability, you could get in.

The lotto application process besides being limited is imperfect in so many ways. The GMAT if I recall correctly correlates to success only around 65% of the time.

It’s time for these elite schools to decide how important an issue brand dilution (maybe) is for them, and come out and be straight about how much they factor it into their strategy vs. limiting how many diplomas they grant based purely on scalability while maintaining quality.

Ones a logistical problem. One is profit (endownmenrm prestige) motivated.

Pick a side for the future.

MIT has done a lot to expand access to content in the form of OpenCourseWare (https://ocw.mit.edu/index.htm) and edX (https://www.edx.org/).

The issue you have identified is finding scalable method of accreditation. Other schools have certainly tested online-only degree programs and produced many graduates. As an alum, I do struggle with the question of, "would an online-only graduate be 'real' alum"? That's my own personal bias. I imagine the institute does think about brand dilution to some extent.

That said, while colleges may be gatekeepers to degrees, it is employers that require the degrees to get jobs. Why bother with degrees in the first place if the candidate can prove they have the necessary skills for a job despite not holding a degree?

I realize I'm deflecting, but it's worth pointing out that there are multiple parties in play here, not just universities—MIT or otherwise.

Author of edX here. At the time I left edX, the vast majority of courses used long videos and multiple choice questions.

* Open-licensed courses (as originally promised and intended)

* Real checks-and-balances and not-for-profit structures

* Investment in research in improving teaching-and-learning

* Commitment to integrity in results presented to the public, in respect for student privacy, and in general, a strong set of core values and to keeping what's working in education

A lot of courses are run asynchronously which blows a lot of meaningful collaboration out of the water right there. And even when they're run like a real-time course (which a lot of people who have other schedules/travel/etc. tend to hate), you have such a wide range of skill/language/etc. levels that it's hard to have sensible discussions.

Courses that try to be explicitly discussion-focused are even worse.

Autograding for coding assignments is nice when it works. But I'm honestly not sure the average MOOC is really any better than just reading a book and doing some related exercises.

I do think you need to have deadlines. They can be more flexible but deadlines help at least keep groups of the class at the same pace. The more people participating, the more relaxed the deadlines can be. I've seen some courses that have so many people, you could honestly take the class at your own time & always have people to discuss the current lecture with.

In the case of a real MIT online degree, I would support a schedule that mimics the campus schedule. If you have other schedules/travel/etc., then sign up only for 1 course at a time & understand what you're committing to.

I get scaling is hard the more "real" you make the course. I feel you can have a nice balance between hiring assistants to help with grading & discussions by increasing the cost somewhere in between on-campus & average MOOC prices.

Blended models have a lot of promise--at least in theory. My understanding is that post-pivot Udacity does some things along these lines. And, of course, there are more traditional degree programs that have a large online component.

One of the nice things about CS/programming is that, in many cases, you don't really need the physical resources of a university campus. And even if you can't handle 100% of a full degree program, "nanodegrees" and the like are a big win. It's also nice that computer systems can handle a lot of the grading of problem sets--and, as you say, it's not super-expensive to have TAs handle the rest. (Source: I remember what I was paid to be a grader for a few courses in grad school :-))

CMU's Machine Learning Department was founded in 2006, before the current AI hype cycle started. If this is MIT's response to a 'department' of AI, then MIT has been asleep for >10 years.

Perhaps you mean CMU's new undergraduate AI degree. But that is not a new department. It's merely a separate major within the existing school. And not really comparable to MIT's recent announcement, which is much more focused on research than new undergraduate majors.

> Yet I can't imagine why an entire 'college' of AI is needed. AI simply isn't a field that's deep or broad enough to warrant an entire college with a handful of distinct majors, like an engineering college or medical school.

The article discusses this point.

Let's start from the premise that MIT is going to focus a lot its hiring efforts on "Computational X" for all X in which it hires. There are basically three advantages to introducing a new academic unit instead of hiring Computational X people into the X department:

1. Collaboration

2. The "X" department might be ossified and unwelcoming to "Computational X". So from a P&T incentive structure perspective, starting a new department/college can make sense.

3. Naming rights => $$$

> Each of this college's AI degrees will span distinct problem or solution spaces? Not likely.

They're hiring 50 faculty, and half those lines will be dedicated to non computer scientists. That's larger than many R1 CS departments. So, they're certainly hiring enough manpower to run several innovative educational programs.

This also explains why it's a college instead of a department. Hiring historians, philosophers, MD/PhDs, biologists, engineers, and computer scientists into the any single pre-existing college would be pretty awkward.

The current field of AI might not yet be as broad or deep as the fields you mentioned.

The science and engineering of intelligence, however, holds potentials to be even deeper and more impactful than those fields. Intelligence underlies most human endeavors. Civilization itself would not be possible without it. It is the greatest distinction between us and other animals.

Depends which departments/courses they're assimilating. Course 6 is computer science that holds CSAIL, course 9 is Brain and Cognitive Sciences that holds cognitive science, cognitive psychology, and neuroscience. CBMM encompasses everything from probabilistic programming to deep neural nets to classical computer vision.

I think that if they take some of the more exciting but empirically rooted stuff from CBMM and build up a department that can actually train students for it in-depth, that will be a significant improvement in training tracks available to people now. Computational neuroscience, theoretical neuroscience, computational cognitive science, machine learning, statistical learning theory, etc all remain small specialties within larger fields when taken alone, but when put together really deserve to have their connections considered as potentially forming the foundations for a single field.

Its ultimate subject is how to make machines think as well as brains think. Arguably, brains are the thing that distinguish homo sapiens from other animals, and we don't know how brains can be engineered or how such devices can be made efficient and accurate.

If you conceptualize that math/engineering/biology/philosophy question holistically, it is definitely worth an independent college.

AI is a field that's over 60 years old, that includes at least half a dozen sub-fields, by my counting (say, NLP, speech processing, machine vision, robotics iiish, game-playing, information retrieval, knowledge representation, inference and reasoning, etc, and, of course, machine learning), with, oh I don't know, out of the top of my head, 50 or so conferences, and about a thousand journals? Thereabouts.

That's broad enough and deep enough to warrant a couple of colleges alright. And if you take into account the age and breadth of subjects encompassed by many of the sub-fields of AI, you probably need a college for each.

I don't see why not? We are a long way away from general AI.

There was a point in time where this statement would sound true when describing computer science as a degree. People quite reasonably thought that CS should just stay under the math department. Yet look where we are today.

Who's knows how much bigger the field will become in a couple decades.

If it’s anything like the funding that goes to climate research, chunks of the gift will get funneled into projects that are tangentially associated with AI, for the reasons you mentioned.

I guess by this move their goal is to now make it deep enough.

Am I wrong in this understanding?