This is an excerpt of a blog that was originally posted on the Hack Education. Visit the link for the full transcript of the talk.
I gave the keynote today at WebWise 2013, and I have to say, after a long week at SXSWedu, I was pretty happy to be able to be around a bunch of librarians and archivists. The theme of this year’s WebWise was “Putting the Learner at the Center,” and my talk echoed something I’ve been pushing a lot lately: this question of who owns educational data. I was particularly eager to raise this question in front of this particular crowd, as I believe that IMLS-ish folks will be key in helping answer it. (No pressure, guys!)
Below is a rough transcript of my talk, along with a Storify of some of the tweets and a copy of my slides.
Whose Learning Is It Anyway?
Some of you might recognize the title of this talk as a nod to the TV program “Whose Line Is It Anyway?” — a show that ran for 8 seasons on ABC and which is apparently coming back to cable after a 10 year hiatus. Bonus points if this title conjures the British version of the show rather than the Drew Carey hosted one. Double bonus points if you think of the radio show that predated both.
“Whose Line Is It Anyway” was/is a comedy show — a game show, but only sort of — where the contestants had to compete in various challenges that tested their improvisational skills (as well sometimes as their skills in singing and impressions).
Improvisation is a particularly interesting form of comedy — an incredibly challenging but rewarding form of theater.
With improv, you must hold in your head as many cultural, historical, and literary references as you can. These must be quickly and readily accessible. Characters, themes, situations, voices, postures, gestures. Performers must be able to recall, remix, collaborate, innovate, pivot, and hopefully make the audience laugh.
Now this certainly sounds like a slew of tech-industry-related buzzwords doesn’t it – remix, collaborate, innovate, pivot — and as such, I’m sure there’s someone who might hear that and think “wow, let’s disrupt improv!” — this is a job for a database or an app: index it all, access it in real-time to maximize humor!
But can a computer do improv?
The Turing Test – the test to see if a machine is “intelligent” enough to fool a human – doesn’t necessarily help us here.
IBM’s AI machine Watson did appear on another game show after all — although on Jeopardy, not on Whose Line Is It Anyway?
Using far less sophisticated technology — as in something I can program — are Twitter bots, like the incredibly popular @horse_ebooks, that string together random phrases that look a bit like improv… And sometimes are funny. But unintentionally so.
I would contend there’s a difference here between the programmatic and the improvisational.
I’m currently working on a book on artificial intelligence and education technology — our decades long quest to build teaching machines — so I have been thinking a lot about these things lately: about how our increasing use of AI — a field that relies a great deal on machine learning — might shape what we think about human learning.
The idea for the book came to me when I was in one of Google’s self-driving cars, along with one of the car’s inventors, Sebastian Thrun. He explained to me as we zipped along interstate 280 all the cameras and sensors the car possessed — internally and externally — all the mapping data and all the traffic data that Google had amassed — how all of this going into building a car that does not need a human to steer it, to press on the brakes or the accelerator. In the future of self-driving cars, Thrun said, cars will move along the highway much more efficiently.
Now I confess, as someone who doesn’t drive and who recently moved to LA, I was thrilled with the idea of the robot cars.
But then I thought about Sebastian Thrun’s latest endeavors — the massive online startup Udacity — and I balked. “Wait, no!” I’m not too keen on the notion of automating education for the sake of efficiency.
I did wonder if it was simply me that was construing the self-driving car as a metaphor for education technology, or if this really was the model that the artificial intelligence used to think about our “learning journeys” if you will.
It’s worth pointing out that the three major MOOC initiatives — Udacity, Coursera, and edX — all have their origins in the AI lab. Daphne Koller, Andrew Ng, Sebastian Thrun, and are all AI professors at Stanford; Ng took over the head of Stanford’s AI lab when Thrun stepped down. Anant Agarwal, the head of edX, was the former head of MIT’s AI lab and a developer of exascale computing technology.
As such, these MOOC endeavors could be read as part of the long-running efforts on the part of AI researchers to develop automated teaching machines and intelligent tutoring systems.
If we just have enough data — from content to assessment data and sure, from the tens of thousands of students in massive online courses and all their keyboard and mouse clicks — we might be able to build algorithms and models that are “personalized” and “adaptive.”
But can that system ever really look like improv? Can it look like open inquiry? Can it look like self-driven learning?
If a tree falls in the road in front of a self-driving car, the car shuts down. It doesn’t go around it. It doesn’t take a different route. It stops. The self-driving car cannot handle that sort of serendipitous event.
And here we move to the heart of the matter — from “whose line is it anyway?” to “whose learning is it?” And let’s start with the data — because certainly there are many systems — robot teachers and robot graders and adaptive apps and quizzes — being built on top of it.
Who owns the learning? Who owns student data? Who owns our education data after we’re out of school? Who owns learners’ data across the variety of institutions — formal and informal — where we continue to learn throughout our lives?
I posed that question on Twitter a week or so ago. Do students own it? Schools? The government? Software providers?
The answers were varied — some people insisted that education data belongs to the student; others insisted that it belongs to however collects it. The discrepancies, to a certain extent, no doubt reflect the different levels of awareness about and definitions of education data. Whatcounts as education data – and I certainly don’t think it just means student test scores and student ID numbers.
And honestly, it’s probably not too hard to argue that our lack of a strong stance or understanding on this topic goes for all our digital data: who’s collecting it, to what end, under what legal protections or restrictions.
These questions aren’t entirely new, but our increasing use of technologies is creating lots of new data — and lots more data — some 2.5 quintillion bytes of data created every day according to IBM — and we are facing numerous challenges and opportunities as a society over what it means to control and access and — in our case here, I’d imagine — learn from it.
Yet the question of ownership of education data remains largely – and troublingly – unresolved.
Visit Hack Education for the full blog post.