The “Techlash” is Telling Us Something. Are We Listening?
by Shawn Rubin
Right now, district leaders across the country are navigating a debate that is only getting louder and more complex. On one side sits parents and community members demanding that schools move faster on AI, frustrated that their children are falling behind students in districts with bigger budgets and bolder technology agendas. On the other side sits the “techlash”, driven by parents, school committees, and student groups who cite concerns about academic integrity, screentime, environmental harm, and the erosion of the human relationships that make schools worth attending in the first place. In the middle are the leaders and teachers who are being asked to have a coherent answer for both groups simultaneously, usually without additional staff, funding, or time to figure it out.
While the national debate continues to get louder and more polarized, the version that district leaders are actually living is more exhausting than ideological. It is the experience of making a deeply divisive decision, with very little evidence in hand to explain where you are headed and why.
A Lesson from Farming Worth Borrowing
My mom was an educator, not a farmer. But she had an analogy she reached for often in her work as a district leader, and it stuck with me. She used to say: “the education system loves to weigh the cow but struggles to make time to feed it.”
If you're a cattle farmer, your purpose is to raise healthy, heavy animals that will do well at the county fair. The weight is the proof. But if you're so focused on pulling cows out of the pasture to weigh them that you’re taking them away from the grass that actually makes them grow, you’ve lost sight of the job. The successful farmer is tending the field, not chasing the number.
The parallel to our schools is uncomfortably close, and it runs deeper than our testing protocols. It shows up every time:
- A district purchases software and assumes that minutes logged equals skill mastery
- Students access AI tools without understanding whether those tools are building knowledge and skills or quietly replacing productive struggle
- We can't answer a parent's basic question about why their child is on a screen, what specifically that screen time is supposed to produce, how we'll know if it's working, and what we'll do if it isn't.
We have gotten very good at pulling the cows out of the field, but we have not built the collective muscle to ask whether the time this is taking is actually producing more weight.
Imagine if the farmer tries something different. Instead of routinely pulling cows out of the field on the regular weighing schedule, the farmer leaves some cows in the pasture and tries something evidence-based to support their growth: playing certain music, staying close while they eat, adjusting what part of the field they had access to each week. The farmer pays attention to what is changing and compares results with the rest of the herd after the allotted time period ends. If the cows who have been left in the field grow more, the farmer now has something worth understanding more deeply, something worth trying with other cows, and something specific enough to explain to other farmers.
This is the muscle our schools need to build with AI:
- Decide what you are trying to grow.
- Try something specific and grounded in what you already know works.
- Watch for the early signs of success.
- Then measure to see what you actually have.
A Different Approach
What if district leaders stopped trying to defend AI and screen time in the abstract and started asking a much more specific question instead?
Every district I work with already has something it cares about. There are instructional priorities, professional learning goals, and building-level commitments. The question worth asking is whether there is an AI tool that could help teachers implement current priorities more consistently or with greater impact(opens in new tab).
Say a high school has spent two years building professional learning around student-to-student academic discourse. Teachers have been coached, protocols are in the room, and learning walks are taking place. Could an AI tool or agent help more teachers plan these rigorous student interactions more efficiently or facilitate that kind of discourse more consistently? That is a concrete scenario to investigate, something specific enough to design a real pilot for, and because it is tied to something the school already believes in, the rationale for AI use is already built into the work.
It also creates a potential outcome worth watching. Is the AI agent helping to produce more structured discourse in more classrooms during the pilot window? If not, you have learned something real and you have not scaled a mistake in the process. We know this work by several different names, like continuous quality improvement or a strategic innovation approach. It's just good practice in general, but as leaders step into these competing headwinds it feels like a critical district move to focus on right now.
Defining the problem before reaching for the tool, identifying what success looks like before asking anyone to change their practice, and building in the data collection from day one, is how you move forward with intention. And it changes the stakeholder conversation away from a defense of AI in general and toward a specific story connected to district priorities.
A leader can now stand in front of a school committee and say, “Here is the instructional challenge our tenth grade teachers were facing. Here is what we tried. Here is what we are seeing in classrooms now, and here is what we are still working to understand.” That kind of communication earns trust in a way that no policy statement or board resolution about AI ever will, because it asks stakeholders to consider a specific use case rather than form an opinion about technology in theory only.
This is what families want from their districts, even when they don't articulate it that way. Parents trust schools and educators to be the experts, or at minimum to be the people being paid to build expertise on behalf of students. Most families are not asking to co-design AI governance frameworks or weigh in on product procurement decisions. They are asking for rationale, for strong examples, and for evidence that the tools selected are connected to something the district already believes is important. When leaders can provide that, the local version of the techlash tends to quiet down, even as the national debate continues to rage.
The Slower Work
None of this is flashy. Districts cannot buy it at a conference, and there is no certification that signals you have arrived. What there is instead is a muscle, and like any muscle it gets stronger with repetition and weaker when ignored.
The muscle is the ability to connect instructional priorities to specific use cases, design small pilots, identify leading indicators before launch, and communicate what you are learning to the communities you serve. That is the same sequence the farmer used, just applied to classrooms rather than tending pastures, and it works for the same reason. You cannot know what is growing if you never stop to look. You cannot defend what you are doing when your definition of success is tied to one single lagging measure that you test over and over.
The leaders we work with aren’t avoiding this work because they don't care about getting it right. It’s because nobody handed them a model that actually fits inside the constraints of their day, their budget, and their team. That is the gap Throughline Learning exists to close. We work alongside district leaders to build implementation, evaluation, and communication infrastructure, grounded in the instructional priorities districts already hold, designed to grow the evidence base that school communities are asking for, and built to be sustainable without adding to an already stretched budget.
Research confirms that transformational systems change in school districts is rare and incredibly challenging(opens in new tab). The most reimagined school models in the country will not spread by being cloned into public systems. They will spread when thousands of traditional districts have run this pattern enough times to build the governance trust to try something new, the co-design muscle to build with their communities instead of buying at them, and the evidence infrastructure to know what worked and say so publicly. Nobody arrives at those three capacities by being told to want them. They arrive by winning something small, and then wanting to win again at something harder.
We cannot ask families to trust technology when its purpose and impact are hidden from view, so we help districts lean into the current AI headwinds. Districts that can show their communities what they are trying and what they are learning will always have a stronger position than districts that are simply defending a position on technology use. And the leaders who build that capacity now will be well-positioned when the next wave of technology arrives and the debate starts all over again.
Note: The ideas, the farming analogy, the core argument, and the voice in this piece are the author's own. Claude (Anthropic) assisted in the drafting process.
Learn More
At Throughline Learning, we know that effective instruction will always be about human interaction. We help districts establish thoughtful AI strategy that boosts your educators’ capacity, confidence, and creativity in this new era of possibilities. Explore our Fuse AI Partnerships Guide to learn more about our AI task force facilitation and professional learning offerings.
About the Author
Shawn Rubin is the Executive Director of Throughline Learning (formerly Highlander Institute) in Providence, RI. He is an internationally recognized thought leader and speaker with deep expertise in classroom coaching and change management strategies for building and district leaders. In 2018 Shawn co-authored the book Pathways to Personalization: A Framework for School Change, which details Throughline Learning's community-driven school improvement approach. Shawn prioritizes supporting at least one of Throughline’s portfolio schools every year to build connectivity between the organization’s classroom implementations and national field building efforts. He has won several innovation awards for his work in the nonprofit sector, including iNACOL's annual award for Outstanding Individual Contribution to Personalized Learning.