Allison Tuthill, Financial Advisor Modern Woodmen of America

10/26/2026

**WHAT ARE WE ACTUALLY TRYING TO ACCOMPLISH?**

Before introducing AI into a child's educational experience, I think we should ask a question that sounds almost embarrassingly obvious: **WHAT ARE WE TRYING TO ACCOMPLISH?** Better grades? More efficient completion of assignments? Improved reading comprehension? Greater independence? Stronger critical thinking? More opportunities for creativity? Increased access for students with disabilities?

Those are not necessarily interchangeable objectives. And a technology that helps accomplish one might do very little for another.

Imagine an AI tool that helps students complete writing assignments more quickly. Wonderful! But what if our educational objective was to help those students become better writers? Did they learn to organize their thoughts more effectively? Did their vocabulary expand? Did they become better at developing arguments? Could they demonstrate those abilities without the technology? Or did they simply produce better finished assignments?

I don't know the answers to those questions for every tool, child, or situation. And that's precisely the point. **WE NEED TO DEFINE SUCCESS BEFORE WE START MEASURING IT.** Otherwise, we risk confusing impressive outputs with meaningful developmental progress.

AI may create extraordinary educational opportunities, but those opportunities become much more useful when we know what we're trying to cultivate.

**Question:** If you were designing an AI-assisted learning experiment, what would you measure to determine whether students were actually benefiting?

10/26/2026

10/26/2026

10/25/2026

**SUNDAY, OCTOBER 25: RESPONSIBILITY DOESN'T WAIT FOR CERTAINTY**

This week, we've been asking who is responsible for children growing up in an increasingly AI-integrated world: parents, teachers, schools, researchers, technology developers, policymakers. And perhaps the most important conclusion is that none of them can responsibly hand the entire problem to someone else. Parents cannot be expected to become experts in every new model. Teachers cannot independently evaluate every new educational tool. Schools cannot create effective developmental strategies without evidence and professional expertise. Researchers cannot investigate systems they cannot meaningfully study. We also can't expect them to be experts in childhood development and education. And technology companies cannot reasonably assume that providing a useful product resolves every question about its effects.

All of these groups have different responsibilities. And they need to work together. WE all need to work together.

But there's something else I want to emphasize. **WE DO NOT HAVE TO KNOW EVERYTHING BEFORE WE CAN ACT RESPONSIBLY.** We can distinguish evidence from speculation, identify specific objectives, design limited experiments, preserve human oversight, listen to children and the adults who know them, study outcomes, acknowledge uncertainty, and we can change course when new evidence warrants it.

I don't think responsible stewardship requires perfect foresight. I think it requires humility, curiosity, courage, integrity, and a willingness to learn. And I think those qualities become more important, not less, when the technology is advancing faster than our ability to fully understand its consequences. Because the ultimate objective isn't to produce the most technologically sophisticated generation in history. **It's to help children become capable, thoughtful, flourishing human beings even in a time of extraordinary technological innovation and rapid change.**

And the technology should serve that objective, not replace it.

Question: What would responsible stewardship of AI in children's lives look like to you?

10/24/2026

**SATURDAY, OCTOBER 24: SHOULD THE PEOPLE BUILDING AI HELP STUDY ITS EFFECTS?**

Technology companies possess information that researchers, educators, and families often cannot access. They know how their systems are designed and when (and how) models change. They can evaluate certain capabilities and limitations. They may have information about how people interact with their products. And they can modify the systems themselves. That creates an important opportunity, but it also creates a responsibility.

If AI companies are building products that children use, shouldn't understanding those products' effects be part of the development process? Not merely whether a system produces accurate answers or whether users enjoy interacting with it or merely whether it increases engagement, but whether the technology supports the human capacities we're trying to cultivate.

Of course, companies cannot answer every developmental question themselves. And company-funded or company-conducted research should not be our only source of evidence. Independent researchers need meaningful opportunities to investigate these systems. Families and children need appropriate privacy protections. Educators need clear information about relevant limitations. And findings that complicate an attractive commercial narrative should not disappear simply because they're inconvenient.

I think we should be looking for ways to make serious research collaboration easier while preserving independent scrutiny. **THE PEOPLE WHO BUILD A TECHNOLOGY HAVE SPECIALIZED KNOWLEDGE ABOUT IT.** That knowledge should help society understand its consequences, but it should not give those companies exclusive authority to decide what those consequences mean.

Question: What responsibilities should AI developers have to support independent research into how their products affect children?

10/23/2026

**FRIDAY, OCTOBER 23: HOW DO YOU STUDY A MOVING TARGET?**

Let's talk about research. I think we should be conducting as much thoughtful, rigorous research as possible into AI and human development, especially into children's development. But there's a rather extraordinary methodological challenge:
**THE TECHNOLOGY IS CHANGING WHILE WE'RE STUDYING IT.**

Imagine designing a study around a particular AI model. You establish your research questions, recruit participants, develop protocols, collect observations, analyze results, and submit your findings for publication. Meanwhile, new models have been released, capabilities have expanded, products have changed, and people have developed new ways of using the technology.

Does that make the original study worthless? Absolutely not. It may tell us something important about a particular intervention, population, and set of conditions. But it raises serious questions about how broadly we can generalize those findings.

And children's development introduces another complication. Some outcomes may take years to become apparent. What if a tool improves immediate assignment performance but affects independent skill development differently over time? What if a benefit for one age group doesn't generalize to another? What if effects depend on the child's prior knowledge, relationships, or level of adult guidance? Not to mention how individual each child and his or her circumstances are! These are research questions, not conclusions.

I think we need multiple approaches: controlled experiments, longitudinal studies, observational research, qualitative inquiry, and continuing evaluations as technologies change. And we need researchers to be extraordinarily clear about the limits of their findings.

**GOOD RESEARCH DOESN'T REQUIRE PRETENDING WE KNOW MORE THAN WE DO.**

It requires asking better questions and allowing reality to correct our expectations.

Question: How should researchers adapt their methods when the technology they're studying changes faster than traditional research timelines?

10/23/2026

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10/22/2026

**THURSDAY, OCTOBER 22: A SCHOOL POLICY IS NOT THE SAME AS A DEVELOPMENTAL STRATEGY**

Imagine a school district announces a comprehensive new AI policy. It explains which tools students may use, establishes rules for assignments, addresses academic integrity and perhaps student privacy. Excellent. Those are important responsibilities.

But I have another question. **WHAT IS THE DEVELOPMENTAL OBJECTIVE?** Are students supposed to learn how to evaluate AI-generated information, understand the limitations of the technology, use AI to support independent inquiry, develop better questions, recognize when assistance becomes substitution, learn when NOT to use AI, and how do those objectives change between elementary, middle, and high school?

A policy can tell students what is permitted. But a developmental strategy needs to consider what capacities we're trying to cultivate over time. That requires more than technology rules. It requires educators, developmental specialists, families, administrators, and students to consider what appropriate AI use actually looks like at different stages.

And it requires something else. **A willingness to revise the strategy as evidence and technology change.**

I don't think schools should have to choose between permanent prohibition and uncritical adoption. There should be room for carefully designed, supervised, measurable experimentation. But the educational objective ought to determine the role of the technology. Not the other way around.

Question: What should every school's AI strategy include beyond rules about permitted and prohibited use?

10/22/2026

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10/21/2026

**WEDNESDAY, OCTOBER 21: TEACHERS ARE BEING ASKED TO NAVIGATE A MOVING TARGET**

I spent fourteen years teaching French. And one thing I know about teaching is that the work doesn't end when you've prepared a lesson. You have to observe what happens when actual students encounter it. You ask yourself questions like: Who understands?, Who is confused?, Who needs more practice?, Who is ready to move ahead?, Who appears to understand but cannot apply the concept independently?, And what needs to change tomorrow?

Now imagine introducing AI into that environment. A teacher might use it to develop differentiated materials, generate additional practice, explore alternative explanations, or provide individualized support. Those possibilities are exciting.

But teachers also have to consider whether students are actually learning. Are they practicing the intended skill? Are they evaluating information? Are they developing independent understanding? Or are they producing better-looking assignments while doing less of the intellectual work?

And then there's the technology itself.

A tool evaluated at the beginning of the school year might behave differently after a major update. That will certainly be the case this school year and for some school years in the future. The rate of change makes that a near certainty.

A new model might introduce capabilities that weren't available when a district adopted its policies. When I recently checked, not many school systems even had policies, much less true governance. I hope schools are moving to quickly address this gap, but I understand why there is a gap. Things are just moving THAT fast.

A system might become better at one task while retaining significant weaknesses in another.

**WE CANNOT EXPECT TEACHERS TO NAVIGATE ALL OF THIS THROUGH INDIVIDUAL TRIAL AND ERROR.** Professional development, institutional guidance, time for evaluation, and opportunities to share observations are essential. And teachers need permission to exercise judgment rather than being expected either to embrace every new tool or reject the technology entirely.

Question: What kinds of support would help teachers evaluate AI without adding an unreasonable burden to their already demanding work?