🤖 5 ideas from my new AI keynote

🚨 BREAKING: New AI teacher readiness course

This one’s so new, I don’t even have an image for it! 😂

I’m really not even supposed to be announcing this yet.

I’m teaming up with two friends and edu leaders to create an online course.

(Can’t even tell you who they are yet …

… but if you’ve been watching on social media, I’ll bet you can figure it out.)

Topic: What teachers need to know to navigate school and the classroom in an AI world.

Here’s why I’m jumping the gun and announcing this before I’m supposed to:

Do you have end of year PD funds that you need to spend?

Think you might be interested in signing up a group of teachers this course?

Then hit reply and tell me! Give me your timeline / deadline and ask for whatever details you need. We’ll do our best to take care of you in time.

📚 New AI resources this week

1️⃣ AI Agents Reveal New Tech Possibilities in K–12 Education (via EdTech Magazine): Agentic AI workflows can help schools break down silos and use their data sets more proactively.

2️⃣ Schools’ AI Policies Are Still Not Clear to Teachers and Students (via EdWeek): A majority of educators say their districts have not made their artificial-intelligence policies clear to educators and to students.

3️⃣ OPINION: Parents have the power to drive change and make sure that AI addresses inequality (via The Hechinger Report): As AI continues to influence education, it’s vital that we approach this technology with both optimism and caution

📢 Your voice: Ken Shelton’s keynote

Last week’s poll: Which of these points from Ken Shelton’s keynote made you think most?

🟩🟩🟩🟩🟩🟩 Teacher-centered pedagogical biases in AI tools. (12)
🟨🟨⬜️⬜️⬜️⬜️ To personalize, you must know the person. (5)
🟨🟨🟨⬜️⬜️⬜️ Not cheating. "Behavior detrimental to my learning." (7
🟨🟨🟨🟨⬜️⬜️ AI literacy: definitions. Not mindless platitudes. (8)

AI literacy: definitions. Not mindless platitudes: A big cornerstone for AI literacy is about teaching and understanding thinking WITH AI. It’s about evolving our expectations—so students can do what only humans can do: question, reflect, and make meaning. — Erin Tashian

Teacher-centered pedagogical biases in AI tools: This left me grappling with the fact that AI is forcing teachers to be more student-centered to ensure students engage in the learning process, while leaving teachers with tools that create lessons and assessments that do the opposite. How do we bridge the gap? — Abigail Felten

Teacher-centered pedagogical biases in AI tools: AI literacy is key to everything - without a strong definition to guide the work schools/districts do surrounding AI, the focus will likely remain simply on the tools rather than a more comprehensive understanding of AI's power, pitfalls, ethical concerns, and implications for teaching/student learning. I couldn't select 2 options, but the "Not cheating. 'Behavior detrimental to my learning.'" also got me. I heard him mention this during last December's Ditch Summit and it has stuck with me since then--I had never really thought about cheating and talking with students about cheating framed in this manner before but it makes so much sense! Asking students to think about the learning experiences they are willing to sacrifice and for what in return can be a powerful way to shift thinking--both for students and teachers. — Melanie WInstead

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🗳 Poll: Ideas from my new AI keynote

Instructions:

1. Please vote on this week’s poll. It just takes a click!

2. Optional: Explain your vote / provide context / add details in a comment afterward.

3. Optional: Include your name in your comment so I can credit you if I use your response. (I’ll try to pull names from email addresses. If you don’t want me to do that, please say so.)

🎙️ 5 ideas from my new AI keynote

Can you believe that the movie Back to the Future Part II was set in 2015 … and that was 10 years ago?!?

That future-facing movie was a monumental moment in my childhood. I loved the glimpse into the future — 25 years into the future at the time.

Hey, they got some things right:

• Video calls

• Wearable tech

• Hands-free gaming

… and the Cubs almost won the world series that year, in 2015!

It wasn’t 100 percent accurate, though. Fax machines were everywhere in that movie — and we never got TRUE flying cars or hoverboards.

We’re in our own Back to the Future Part II moment right now — an opportunity to peer into the future and make our best prognostications about what’s to come.

Yesterday, at the Region 1 Educational Service Center tech conference in South Padre Island, Texas, I gave a new spin on my AI keynote, “Tomorrow Glasses.”

Here are five big ideas from that new speech …

1. What does “tomorrow glasses” mean?

It still centered on the big analogy of “tomorrow glasses” from my book, AI for Educators …

• Often, in education, we look at schools, policies, even lesson plans through our “today glasses.”

• We’re using today’s world and today’s reality to make decisions as a guide to prepare students for the future.

• The problem? Today is not our students’ future … and their future will likely look vastly different from today’s realities.

• Instead of looking through our “today glasses,” we need to use our “tomorrow glasses.”

• That means looking at trends for the world, workforce, tech, etc. to see where everything’s headed — and try to prepare them for THAT reality instead.

• The problem? Using your “tomorrow glasses” is imprecise and messy. We are bound to be mistakes — because we can’t truly predict the future.

• Even with the mistakes, using our “tomorrow glasses” to predict and prepare is still our best bet to prepare students for their future.

2. AI will change doing, thinking, and knowing

Not only will the technology change — and what we are able to do when we use it …

AI will also change our relationship with knowledge … our relationship with intelligence.

It’s going to alter some of the fundamental understandings that we have about who we are as humans and how we go about our lives.

AI will change what it means to do, what it means to think … and what it means to know.

• AI will change what it means to do. What does it mean to do something yourself? How much AI assistance classifies it as “not done yourself”? We already have a real disconnect in education with collaborative work — even though it’s widespread in the work world and in our personal lives. This will just further shine a light on our complex with “doing it yourself.”

• AI will change what it means to think. What happens when you have a thought partner in your pocket? A co-creator that levels up what you can do? Is that an unfair advantage—or does it level the playing field for everyone? At some point, we have to reckon with the idea that our abilities WITH tools is as valuable (more valuable?) than our abilities without.

• AI will even change what it means to know. Already today, we augment our knowledge with other technologies. We use digital technologies like our phones and the cloud. We even use analog technologies like notebooks and sticky notes. Right now, if I have a question about something, I can just ask my Meta Ray-Ban smart glasses, and they’ll whisper the answer in my ear. We need to strike a better balance between utilizing our knowledge tools and shunning them for human memory.

3. You can teach about AI AND your curriculum.

I know it — because I did it myself.

When I was teaching Spanish full-time last spring, I made and used AI-generated images to get my students practice with new vocabulary.

We got lots of great Spanish vocabulary practice. But I was also gradually teaching my students AI literacy by …

• Labeling AI-generated content (modeling how to be transparent about AI use)

• Identifying that I was using AI in my work (removing the stigma that “AI = cheating”)

• Encouraging them to pick out “AI weirdness” in the images (practice finding the signs that something is artificial)

• Talking about prompting the AI for images and what went well/poorly (strategizing how to best use AI)

• Talking about why I use / don’t use it in certain circumstances (discussing ethical and responsible use)

I didn’t pull out a canned unit on AI or machine learning.

I don’t have a computer science degree.

But I was still able to help my students build their AI literacy — in very practical ways that they could immediately apply to their own work and lives.

4. Focus on questions

What happens when AI advances to the point when we can’t outthink it anymore?

How should we teach — and our students learn — when all of the world’s information is at our fingertips?

(Wait … all of the world’s information has been at our fingertips for a while now. Let’s adjust that question …)

What happens when AI can take all of the world’s information and use it to explain and write and summarize and create?

How do we respond?

For one, we need more questions.

And when I say that, yes … we educators need to ask more questions.

But our students REALLY need to ask more questions.

When all of the world’s information is at our fingertips, it cheapens knowledge itself. Everyone has access to it.

So … what empowers us? What is valuable? Questions.

Good questions give us access to knowledge, information, answers.

GREAT questions unlock new ideas, spark innovative thinking, unleash new possibilities.

When AI cheapens the answers, focus on the questions.

5. Focus on the process

Here’s another response to having all of the world’s information at our fingertips …

We need to get over our fixation on the end product.

Worksheets. Quizzes. Tests. Essays. Research reports. Artifacts of learning, no matter what they are.

What if AI can create those products? Well, when our schools are hyper fixated on the product, then that leaves a big ugly situation on our hands. AI is much faster — and often times just as good — at creating the products.

(And somehow, we’re all surprised when this problem rears its ugly head. It’s like they say: every system is perfectly designed to create the results that it does. This is the system we’ve created! And now we have to lie down in the bed we made.)

So … what do we do?

When AI cheapens the product, focus on the process.

Instead of asking for the essay or the research report, we ask …

• What did you find most interesting in this?

• Was there a part in the writing process where you struggled?

• If you could do this all over again from scratch, what would you do differently?

The process. Let’s be honest. As teachers, we like the end product. But we LOVE the process. Because that’s where the learning happens. That’s how our students learn the real lessons about how the work gets done. They develop resilience and grit and perseverance in the process. 

When all we grade is the end product, what are we really teaching students? We’re implying that the process isn’t the valuable part. Get to the end product by all means necessary -- because that’s how you’ll earn the points in the grade book. Of course, when they learn that AI can create that end product for them, they shortcut right past the best part.

Let’s build in opportunities for students to talk about the process – and show us their learning through it.

When AI cheapens the product, focus on the process.

Love the idea of this keynote?

It’s a new message in my repertoire of keynote speeches now.

If you’re looking for a speaker who can push people’s thinking and spark discussion — while also entertaining and engaging them …

… then we should talk. That’s the work that I aspire to do — and it’s the feedback that I got at this event I did in Texas yesterday.

Next steps:

• Email [email protected] to get more info about pricing, availability, and details.

• Hit reply and email me directly if you’d like to engage and discuss the ideas above. I always welcome the dialogue!