This article was originally published on The Digital Delusion. We thank Jared for allowing us to share it with our readers.
Last week, Mark Zuckerberg — founder and CEO of Meta — took the stand under oath for the first time in a criminal trial. At one point, Zuckerberg was questioned about Meta’s use of beauty filters: digital effects that make users, including children, appear younger, fitter, and more conventionally attractive in photos and videos. The prosecution referenced Meta’s own internal review, Project MYST. According to reports, 18 out of 18 wellbeing experts who evaluated the psychological impact of these filters raised serious concerns about potential harm to young users’ mental health. Despite those warnings, the filters remained available. Zuckerberg’s defense rested on a familiar line of reasoning: there was no peer-reviewed, causal evidence demonstrating this specific product directly harmed children. Absent validated proof of causation, harm could not be established. “There is no evidence of harm.” This is the same argument now being deployed by EdTech lobbyists at statehouses across the country as lawmakers attempt to regulate classroom technology. No Evidence of Causative HarmThis year, more than a dozen bills aimed at regulating EdTech have been introduced across at least nine states. Utah’s SAFE and BALANCE acts led the way, followed closely by Vermont’s effort to formalize parental opt-out rights and Tennessee’s proposal to remove digital devices from primary classrooms. These efforts are informed by decades of research showing that, on average, classroom technologies do not outperform – and often underperform - well-implemented analog instruction. Despite strong bipartisan support in most states, pro-tech lobbyists are pushing back with a familiar refrain: “There is no evidence of harm for emerging EdTech products.” Strictly speaking, that statement is often true. Educational technology evolves so rapidly that by the time researchers evaluate one platform, it has already been patched, rebranded, or replaced. Product-specific causal evidence is perpetually just out of reach. But this is not a scientific defense. It is a misleading procedural maneuver. When Causation Becomes DangerousDemanding product-specific, long-term, high-risk causative trials in children sets an unrealistic and ethically impossible standard. Returning to beauty filters, no ethics board would approve a study deliberately exposing children to a tool that 18 experts consider risky simply to “prove” harm. That is why no randomized control trial has tested whether these filters damage young users’ mental health — the likely harms of such a study outweigh any possible benefits. Luckily, we don’t live in a vacuum. A substantial body of correlational research links image manipulation and filter use to body dissatisfaction, self-objectification, weight concerns, and reduced wellbeing. The experts reviewing Meta’s policies were not guessing — they were applying decades of psychological research to a new technological wrapper. Software changes. Human biology does not. The same logic governs learning. Returning to UtahUtah’s digital inflection year occurred in 2014, corresponding with the statewide launch of SAGE — a fully computerized adaptive assessment system. Before this, digital tools were largely peripheral in Utah classrooms. After this, they became structurally embedded. Before widespread digital adoption, Utah NAEP scores rose consistently from 1992 through 2013. Pooled by subject and indexed to 2013:
After 2014, the slopes reversed:
This represents a structural swing of -1.15 points per year in math, and -1.02 points per year in reading. Importantly, excluding 2022 — the year most impacted by COVID-related closures — leaves these swings essentially unchanged: -1.05 points per year in math and -1.07 points per year in reading. In other words, this pattern is not a lockdown artifact — it’s a structural break beginning in 2015. These are correlational patterns, but so were the early signals about smoking, lead exposure, and beauty filters. When consistent patterns appear across nearly all 50 states’ NAEP data and across dozens of countries’ PISA, TIMSS, and PIRLS results — and when those patterns align with established cognitive mechanisms — we are no longer looking at coincidence. We are looking at converging evidence. And what we cannot ethically do (just as with beauty filters) is deliberately expose children to systems we have strong reason to believe may undermine learning simply to satisfy an unrealistic evidentiary demand. Demanding perfect causation before action doesn’t protect children; it protects developers. A Generous InterpretationEven if we assume the decline argument is overstated — that Utah’s NAEP data has merely “plateaued” since 2014 — the harm does not disappear. Between 2015 and 2025, Utah invested roughly $500 million in K-12 educational technology. If half a billion dollars produces stagnation, that’s not neutral. Every dollar committed to devices and platforms is a dollar not spent on interventions we know improve learning: teacher development, structured literacy programs, small-group instruction, targeted support for struggling students. Even under the most generous interpretation of the data, the opportunity cost alone is staggering. So Now Then…Demanding definitive causative proof of harm before acting to protect children sets an unrealistic and dangerous standard. If we wait for perfect causation, we will always act too late. Our society does not demand product-specific randomized trials before regulating food additives, vehicle safety standards, or consumer protections. We act when converging evidence suggests that risk outweighs benefit. Education should be no different. When billions of dollars and millions of children are involved, the burden of proof should rest on demonstrating clear, durable, replicable benefit — not on proving harm after the fact. Caution is not fear, and restraint is not regression. They are marks of a society that prioritizes children over products. |
