We’ve been following the trajectory of AI closely over the past few years, noting it as one of the greatest opportunities and challenges in modern history. As with most emergent technologies, conversations about AI are riddled with fears, overpromises and doubt.
Over the last few months, we conducted a field scan of artificial intelligence in learning and found what educators, edleaders and learners need to know about this exponential technology. This Getting Smart Town Hall highlighted AI’s role in our current lives, what the civic and educational implications are and will be and, as always, got many outstanding contributions from our audience.
We started out with two poems. Both poems, to the surprise of the audience, were written by GPT-2, a compositional AI that synthesizes tons of data into original pieces of “art”. One of the poems, entitled Rise, is below:
In their little room with the door ajar
And the candle hanging on the wall ajar,
I have come across the word “Rise”
With a face as grave and flat as you please.
The one thing I remember of “Rise”
Is the way it makes you feel — so bad, so bad.
And I’ve come across many words to-night
That are so like “Rise” — so like — so vague, so vague.
”Elegance,” and “Artistic Vigour,”
But “Rise” is far above the rest,
And I cannot hear — or see — the word,
I will just stop here (I’ll stop if I can).
If you don’t know what “Rise” means, try.
We then defined AI and went through some of the important work that AI4K12 is doing to develop useful frameworks for understanding AI’s role in society and learning. We then passed the mic to Justin Aglio, the Founding Senior Director of the Readiness Institute who led the conversation on the worries and bright spots pertaining to AI. Then our team highlighted a number of leading AI companies and applications tracing the categories of our field scan: Learning Applications, Student Supports, Enterprise Solutions and Learning About AI.
As always, the town hall chat was rich with links and references and many of our participants helped us learn through their keen insights and generous sharing. Here are a few of the quotes that stuck out:
“I worry that our concerns about AI problems—biases or other—be taken more seriously than our concerns about Human Intelligence—with its biases, other, etc.” – Marc Prensky
“We need to capitalize on the techniques/tools that pull young people into snapchat, etc. and build these into AI driven learning experiences that focus on real-world impact and learner interest.” – Nate McClennen
“AI in writing is really exciting to me. It is right now the most labor intensive aspect of teaching and learning.” – Mike Olson
“AI provides efficient ways to match student interests and current masteries to appropriate activities to get them going with lower cognitive load. It’s a great way to give a better onramp for students.” – Bror Saxburg
Questions from the attendees
Why are we associating [Artificial] Intelligence primarily with “learning” and not “accomplishing”?
A. This is a great question and largely has to do with the current state of AI. As we addressed on the town hall, most of AI in education tools/apps functions as marketing language at this time and has more to do with processing rather than accomplishing. This will change in the next 5-10 years as machine learning shifts to true AI.
Will AI spell the end of standardized learning?
A. It could if we’re thoughtful and creative. If we’re not, it could reinforce the worst parts of learning that youth are experiencing today. We won’t be able to get away from standardized learning unless we design with students at the center, have community conversations about what we mean when we say “learning” and ask the right questions like: “what should youth know and be able to do?”
I’m curious about students and teachers as AI operators. What does UX look like in this case? Right now, the barrier to entry is quite high just to be “in the loop” in this sense? How can we get students to “do AI” more than “be at the whim of AI decisions”?
A. We referenced a few great AI models that will support with AI curriculum: AI4K12 and AI4All. We also have seen an outpouring of early maker kits and tools to help put the power of AI in the hands of students and teachers. Check out this piece on NVIDIA’s Jetson Nano 2GB for more information.
What would it take to better align what we know works in learning science and what is pushed to market as a product? Instead of just AI help for students, do we need “double vision” AI help that addresses both the learning needs of the students, and the learning/training/action advice needs of the teachers engaging with the students? If teachers and AI act incoherently, students will have more trouble than they should.
A. We would love to see more of this. Due to the refocusing on SEL as a result of COVID-19 and a year of challenged learning models, the learning sciences have re-entered the foreground. We believe that this will be a driving force in the technologies to come. Also, due to the nature of machine learning and artificial intelligence (i.e. learning how to learn) it may be true that the creation of these tools and technologies will not only learn from the learning sciences field, but will continue to shape it as well.
Another guest from the town hall, Bob Hill, is thinking about the implications of AI: “It would be helpful to hear perspectives on the extent of socio-economic impact AI is having and will have (positive and negative) for the foreseeable future.”
This is what we’re thinking about as well. More to come. Until then, be sure to register for our next Town Hall “Let’s Talk About C.B.E.: Competency-Based Everything” which is happening July 14th!.