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Educators may never truly trust AI when it comes to the generative tool's place in classroom learning, but we are sure going to use it.

4 lessons learned about AI in 2023


Educators may never truly trust AI, but we are sure going to use it

Key points:

As a forward-thinker in the realm of education, I’m constantly exploring how emerging tools and strategies shape learning. Each year I share my predictions about these trends. (Here’s a look at my 2023 predictions.) While these predictions are rooted in reality, just as in the show Black Mirror, technology can have some unintended consequences.

It’s no surprise to find that artificial intelligence (AI) made the top of my prediction list last year. In January 2023, about one month after the release of ChatGPT, there were already stories about colleges switching to “pen-and-paper” tests to battle the AI bots.

As I reflect on the year that was, it was amazing to watch AI’s “life cycle of change” happen right before my eyes. Widespread fear gave way to some hesitant acceptance. That acceptance led to some empowerment for educators and students. Hallucinations and bias swung the AI pendulum back to a place of cautious trust. Couple all of these feelings with our preconceived notions of AI fed by Hollywood movies like Terminator and War Games, and I’ve realized that we may never truly trust AI–but we are sure going to use it.

These four lessons learned from this past year really get into the subconscious to discover how we feel about AI in our schools.

  1. The AI revolution happened because of COVID.

In Steve Jobs’ memorable 2005 commencement address at Stanford, he shared a story about “connecting the dots.” He talked about how he dropped in on a calligraphy class, and from that knowledge he created the idea of different types of computer fonts some 10 years later. In reflecting on this year of AI, I, too, have been connecting the dots. Jobs’ launch of the iPhone in 2007 led to a revolution in mobile computing. This revolution hit the education industry in earnest in 2011, with the launch of the Chromebook to compete with Apple’s iPad. This meant that devices were somewhat affordable and that, potentially, every student could have access to one. Flash-forward to March of 2020. The COVID-19 pandemic accelerated every school’s device program. Students needed devices to learn in remote settings, so most schools that weren’t 1:1 before the pandemic became it almost overnight. Recent survey data shows that 90 percent of secondary students are part of a 1:1 device program.

These programs set the table for the main course to come…AI. With devices in every student’s hands, they, too, have access to AI and all that it can potentially do for them when it comes to learning…and cheating. (More to come on that.)

  1. AI affects all subject areas.

Now that every student carries the potential of AI at their fingertips, what does this mean for learning? In the past, new technology tools were introduced in a computer lab or during a computer science course that some students enrolled in. AI is different. Free AI tools out there, from large language models like ChatGPT to image generators like Bing Image Creator, mean that every student (depending on age) can leverage AI to help them complete whatever learning tasks the teacher has given them. If a math teacher gives you a set of problems to solve, why not leverage Khanmigo to help you solve them? Your history teacher wants you to write about the Gettysburg Address: Why not have ChatGPT give you some of the main points?

Traditionalists see this and immediately think that students are taking a shortcut, much like when Google became prevalent at the turn of the century and people guffawed at the fact that students didn’t use their Encyclopedia Britannica anymore. Our beliefs about what is “real learning” are clouded by our own personal experiences. That said, our students do need to learn some fundamental skills that AI cannot teach them. We have to strike a balance when it comes to using AI for learning.

  1. We need to reframe the idea that using AI is cheating.

The scenarios I mention above are becoming more commonplace as we navigate the landscape of AI. This also correlates with the rise in concern about AI being used as a shortcut for learning or as a cheating tool. I think we need to reframe that thought process. While I don’t deny that a student could use AI to help them complete a paper, is that cheating? If so, why? And why do we blame the tool used to cheat instead of looking at a larger problem in education?

The larger problem is that grading overemphasizes students’ final product of learning instead of their process of learning. This creates scenarios in which cheating is almost inevitable. If a student doesn’t understand the topic or is disinterested in it, they are going to try and figure out a way to get the “A” so they can win at the “game of school.” If teachers instead evaluated their learning process with the same weight as their final product, cheating would fall by the wayside.

  1. Human compassion is greater than artificial intelligence.

“Why not just have AI do everything?” This has been a common question I have heard when doing AI workshops with teachers across the country. You can use it to generate quizzes and students can use it to answer the quizzes, so why do we even matter as educators?

This is the most important question we should be asking ourselves: Why do we matter? What is our role as a teacher? Ultimately, it’s to empower students to become life-long learners. Yes, there are state tests and required subject areas that they must pass, but learning is still the objective.

With AI-enhanced learning, our role as educators (and humans) becomes even more important. AI won’t motivate a student to learn. It won’t listen and react to their emotions or offer unsolicited help when they perceive struggle. It won’t coach them, care for them, or be empathetic towards them. These traits of human compassion will become more important in an AI-enhanced future. And, ironically, because of AI, educators can free up some of their time from menial tasks to actually focus on personalizing the educational experience for every student.

Looking back on this year excites me for what the future holds. AI-enhanced learning will redefine much of what we do in education and will cause us to reflect on what we hold most dear in terms of evaluating student learning.

In predicting the upcoming year (I can’t help myself), I see education continuing to evolve as we get ever so closer to the dream of actual personalized learning. What do you think the future holds when it comes to AI? This is a question only a human can truly answer.

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