The Rush to “Smart” Meters: Maybe Not So Smart?

In a recent blog post I discussed a critique of today’s “smart meters” that focused on the technology’s shortcomings as a step toward creating a “smart grid” that reduces climate change risks and other negative impacts associated with our current carbon-intensive energy systems. In another recent post I discussed the need for more research on EMF health effects.

In this post I’m going to revisit the subject of smart meters from a perspective informed by both of those prior posts. One of my goals is to use smart meters as a specific example of how, when making decisions about large-scale technology deployments, we can and should give more weight to the precautionary principle, especially when a technology’s benefits are as poorly understood and/or overstated as seems to be the case with today’s generation of smart meters.

As discussed in my earlier post on smart meters, their initial rollout (like much of the stimulus bill’s spending) was intended to invest in technologies and initiatives that had strategic value to our society, and to do so as quickly as possible (the federal government was, after all, trying desperately to revive demand following a global crisis that pushed our financial system to the brink of total collapse, and our economy into a deep recession).

Though this was a worthy goal, I’d argue that, in the case of smart meters (as well as electronic health records and other areas covered by the bill), the need to “spend fast” made the task of “spending wisely” very difficult and, perhaps in some cases, impossible.

To clarify this point, let’s briefly compare these two programs (smart meters and EHRs) to the broadband connectivity portion of the stimulus bill. Though the latter was not without some risk of misallocated investment, it involved mature and largely standardized technologies, and fairly straightforward and time-tested planning and execution steps.

In contrast, the investment in smart meters and EHRs involved inserting much less mature and standardized technologies into key interface points within essential infrastructure systems (e.g., electricity and healthcare) whose urgent need for fundamental and systemic change confronts a complex web of entrenched interests. For these programs, the potential risk of unintended negative consequencies is far more serious and difficult to predict than those involved in extending broadband networks to underserved areas.

Flying too fast and too blind?

As suggested by my earlier post, one of the risks associated with the current generation of wireless-networked smart meters relates to potential negative EMF impacts on health. My point here is not that these impacts are necessarily large and ominous, but that: 1) they are not well understood, especially when we consider the range of factors involved in the smart meter deployment (including, as discussed below, the configuration of devices in multiple dwelling units) and; 2) virtually no in-depth research on health risks was done prior to the nearly nationwide smart meter rollout now underway (in that earlier post I argued that such research was important to do and suggested one approach to funding it).

In the discussion that follows, I’m going to use my own evolution from barely-informed enthusiasm to somewhat-informed caution to make some key points about the smart meter deployment.

A few years ago I was living in California when San Diego Gas & Electric (SDG&E), the local utility, began its smart meter rollout. I was initially pretty excited about it, since the move to a “smart grid” was something I’d thought was a good idea since doing some research and consulting in this area back in the 1990s. But, after the meters were installed, I was exposed to information (ranging from personal stories to scientific studies) that made me wonder if more attention to safety was warranted. This information also convinced me that more research should have been done before utilities started deploying RF-networked smart meters on a massive scale and in ways that may have been most convenient, inexpensive and profitable for them, but that might increase the risks of negative health impacts; or to put it another way, that the overly-hurried smart meter rollout was premature and an unnecessary and unwise violation of the precautionary principle.

My concerns were initially triggered by my own situation with regard to the smart meter rollout.

When it began, I was living in a duplex structure where SDG&E had installed two meters per home: an electric meter connected wirelessly to its companion gas meter and, via a mesh network, to other electric meters in the area. As it turned out, all four meters were on the outside of walls where my wife and I spent a lot of time (e.g., where our couch, bed and my wife’s desk were located). While I personally didn’t notice any health impacts from the meter installation, my wife started to complain of tinnitus (ringing in the ear) and a few other symptoms. So we began to look into the “opt-out” provision that was available thanks to a local grassroots movement that had pressured SDG&E and other California utilities into offering this option. We also started reading information published by anti-smart meter groups and talking to people claiming to have been harmed by exposure to the meters.

What I soon realized was that, even if we decided to pay the upfront and monthly opt-out fees, our neighbors’ meters might still be located next to our couch, bed and desk without us having any legal right to have them removed (since the meters were owned by SDG&E and were measuring usage for our neighbor’s home). As it turned out, our neighbors, who had two young children, were also concerned about potential health impacts (the meters were in an area where their kids liked to play outside). So we had all four meters removed. The result: both households had to pay upfront and monthly fees to return to the pre-smart meter status quo (the state PUC has since ruled that the monthly fee can only be charged for three years). Healthwise, my wife’s tinnitus symptoms seemed to improve somewhat, but didn’t go away.

Though this didn’t lead to me to any clearcut conclusions regarding health impacts, it did start me wondering whether the smart meter rollout might be premature from a public health perspective. This sense was intensified after hearing about individuals who reported even more noticeable and problematic health impacts after their smart meters were installed. Since these were typically in the form of personal stories (usually without clearly defined “controls”), they were (too often in my view) dismissed by smart meter supporters as unscientific and unworthy of consideration as indicators of potential health issues meriting further study.

As I was puzzling over this, I noticed a bank of roughly 20 pairs of electric/gas smart meters on the side of a nearby condo complex adjacent to a coffee house with outdoor seating very close to the bank of meters. It made me wonder about health impacts for residents of the apartments directly on the other side of the wall containing the meters, as well as the coffee shop’s staff and all those regular customers chatting with friends just a few feet from the bank of meters.

I later noticed a similar example at a different condo complex, this one restricted to those 55 and over, and inhabited by quite a few people in their 70s and 80s. In that complex I noticed that a bank of roughly 15 electric meters was just outside the homes of two individuals that appeared to be in their 80s and with frail health (which meant they probably spend most of their time at home and close to the bank of RF-networked meters).

These personal observations got me wondering whether these banks of smart meters located in multiple dwelling units (MDUs) might pose particular health risks for those living in close proximity to them, and that research focused on these kinds of network configurations should have been done prior to their deployment. But, as far as I could tell from some Google searches and document reviews, no such research has yet been done.

The more I thought about this, the more convinced I became that, from a public health perspective, the stimulus-funded rush to deploy the current generation of RF-networked smart meters was premature and perhaps harmful in ways that we still don’t understand and should be investigating.

Since—as explained in my earlier post—I’m also convinced that the overly hurried smart meter rollout is not very well suited to facilitate a rapid migration from carbon-based to renewable energy supply, I find myself thinking that the wisest—albeit politically difficult—decision would be to stop any further smart meter deployment until both aspects of these alleged deficiencies are carefully studied, including the health impacts related to deploying banks of EMF-radiating meters in MDUs, and impacts on especially vulnerable populations.

A different “smart grid” model

My earlier post discussed a paper by Tim Schoechle entitled “Getting Smarter About the Smart Grid,” and a related effort in Boulder, Colorado to create a municipal utility based on “a new model for a utility of the future” and much heavier reliance on distributed renewable energy generation.

As Schoechle explains:

[T]he idea is to provide energy services…at the best price and with the least environmental impact…based on distributed renewable energy [and] an “energy localization framework” that seeks to democratize energy decision-making so customers have more direct control over and involvement in energy decisions. This includes opportunities to invest in their long-term energy needs and to have a say in energy investments made on their behalf.

Schoechle also suggested that the term “smart grid” be replaced by “Intergrid,” a term coined by Jeremy Rifkin in his 2011 book The Third Industrial Revolution. As Schoechle explains:

Rifkin compares the grid with the Internet, where intelligence is distributed to the periphery. He envisions that in the future, people will be “…generating their own green energy in their homes, offices, and factories and sharing it with one another across intelligent distributed electricity networks—an Intergrid—just like people now create their own information and share it on the Internet” (p. 36). This transformation took place in telecommunications well over a decade ago, bringing competition and the creativity of the market to the telephone network and customer premises. Now it is the time for electricity to do the same.

A local opportunity?

As it turns out, the city of Lansing and parts of East Lansing, where Michigan State University and the Quello Center are located, are served by the Lansing Board of Water and Light (BWL), a 130-year-old municipal utility that has been conducting a small-scale smart meter trial and is planning to soon begin a five-year rollout across its service territory.

If possible, I’d recommend that BWL hold off on the broader deployment and take some additional time to consider: 1) the potential negative health impacts of that deployment, especially with regard to MDUs and impacts on vulnerable populations and; 2) the relevance to its plans of the arguments and alternative “smart grid” strategies presented in Schoechle’s paper, which I discussed in my earlier blog post.

While this would be an ambitious project for a single municipal utility to undertake, it might be more manageable if it also involved Michigan’s other utilities and relevant state agencies, and took advantage of the multidisciplinary expertise at MSU (including its Institute of Public Utilities), U of M, and the state’s other universities.

Though the Lansing area may not be able to match Boulder’s abundance of sunshine, it has the advantage of already being served by a community-oriented municipal utility that has been moving to expand its use of renewables, and whose tagline reads “Hometown People. Hometown Power.”

Perhaps with some “outside the smart-meter box” thinking, BWL, and perhaps other utilities in the state, can explore possibilities for moving more quickly and fully toward a renewables-based “Intergrid” model that is healthier for the environment, the customers and communities they serve, and their own long-term future.

Primary takeaways

Digital inequality shows larger impacts on youth academic performance as compared to time spent on screens.
Digital skills play a significant role in mediating unstructured online engagement (social media use, playing video games, browsing the web) and youth academic, social, and psychosocial development.
Unstructured online engagement and face-to-face social interaction are complementary and continuously interact to create and enhance youth capital outcomes.

A familiar story: concerns of screen time

Today’s discussions of adolescent well-being have coalesced around a clear narrative: teenagers spend too much time online, and their academic performance, mental health, and social lives are deteriorating as a result. A steady stream of academic papers, books, and op-eds, alongside a growing number of policy proposals––school phone bans, age-gated social media use, restrictive screen-time limits––rest on the same underlying claim, aligning with a contemporary, digitized version of the displacement hypothesis:

Screen time, particularly the unstructured, free-time spent on social media, gaming, watching video content, or browsing the web, is said to displace the productive face-to-face activities that build adolescents into capable adults.

The implied and often practiced solution is restriction. In response, this dissertation tested this claim directly, and placed it within the broader context of adolescence.

Across three years, I followed 653 Michigan adolescents from early through late adolescence: in grades 8 or 9 (survey one, 2019) to grades 11 or 12 (survey two, 2022). Notably, these students, studied over time, were part of a broader pooled sample of 5,825 students across the same eighteen highschools. The study window captured the year before and the year after the peak of the COVID-19 pandemic and related lockdown orders, functioning as an unprecedented stress test for theories of adolescent social, academic, and digital life and, importantly, as a benchmark to compare the effects of pandemic-related change and inequality to those effects from screen time alone.

Across four studies of adolescents, consisting of six cross-sectional and longitudinal analyses, findings are not consistent with the displacement narrative, nor the broader concerns about the time youth spend on screens.

Findings are, however, consistent with something the current public and (most) academic discussions have largely overlooked or ignored: the gaps and inequalities that determine whether adolescents can access and use the internet meaningfully in the first place.

What the displacement hypothesis overlooks

Displacement and related research and policy concerning the time young people spend online assumes a “zero-sum” model of adolescent day-to-day time. An hour online is an hour not spent studying, reading, sleeping, or interacting face-to-face (i.e., time spent on more productive or developmentally “better” activity).

Indeed, this makes sense logically. However, as an empirical claim, this model requires time spent online to behave differently from all other ways adolescents allocate time; it must produce uniquely negative outcomes and be inherently harmful across digital contexts, rather than the typical mix of trade-offs corresponding to, and often overlooked among any other social or developmental context.

Yet, online time does not differ from other youth activity. Instead, I find it has a mix of pros, cons, and even some “uniquely digital” benefits which youth utilize for social and academic gains. When I compared unstructured digital media use against traditional face-to-face interaction and activities, both produced similar patterns: some negative associations with academic outcomes, some null, and some positive.

Trade-offs within traditional face-to-face activity (for example, social time with friends and family, or time spent in after-school extracurriculars) are treated as ordinary developmental experiences that must be experienced for the betterment of development. The identical trade-offs involving digital time tend to be overlooked or ignored, and online engagement is perceived as altogether harmful.

A growing body of evidence, including this dissertation, do not support that distinction. Indeed, the developmental context is routinely misread, leaving out the context of the experiences and time spent on digital, as well as face-to-face activities, interactions, existing inequalities, and changes inherent to development. As such, I proposed a novel framework to understand these contexts:

Digital capital exchange

Rather than treating screen time as a unified harm, this dissertation advances an “exchange”-based framework, grounded in James Coleman’s theories of youth capital and digital inequality scholarship, particularly following Eszter Hargittai, Jan van Dijk, and Alexander van Deursen (see this list of all dissertation references for full works).

The core proposition is that adolescents’ online engagement is not an alternative to developmental activity but another, albiet modern domain through which young people accumulate and mobilize online resources––particularly digital skills––that work alongside existing social networks and experiences to be exchanged for human capital (measured as: academic achievement, aspirations, STEM interest) and social capital (peer networks, community participation, extracurricular involvement).

Online time is not the mechanism; instead, it is digital skills that I find to be the most vital component in youth capital exchange and enhancement. Unstructured online engagement contributes to online skills; those skills, accumulated and mobilized alongside existing peer, family, and community networks, translate into the outcomes researchers and parents care about, i.e., academic achievement, aspirations, and face-to-face interaction and social networks.

This digital capital framework treats online and in-person contexts as complementary rather than antagonistic, and it situates adolescents’ digital lives within the structural conditions––connectivity quality, device reliability, autonomy of use––that determine whether exchange can occur at all.

Methods (in brief)

Paper-and-pencil surveys were administered to students in classrooms at two time-points: spring 2019 (N=2,876) and spring 2022 (N=2,949), across the same eighteen predominantly rural Michigan schools, grades 8–12. Official, nationally-ranked standardized reading, writing, and math test scores (PSAT 8/9, PSAT 10, SAT; College Board) were then anonymously linked to students’ survey responses with the help of participating districts.

Cross-sectional path analyses modeled pooled and wave-specific samples (pooled N=5,825); two-wave cross-lagged panel models tested reciprocal, longitudinal relationships on the 653 students who completed both surveys. Multi-group analyses of the cross-lagged panel models compared relationships between girls (N=345) and boys (N=308). All longitudinal models included time-invariant socioeconomic covariates as well as time-varying covariates to reduce omitted-variable bias.

Key findings: an overview

To summarize, to the best of my ability, eight chapters across 376 pages, I present two primary findings:

First: digital inequality predicted larger and more consistent declines in human capital than screen time did.

Unreliable home internet and technology maintenance problems––experiencing and/or dealing with broken or outdated devices and software, restrictive school-issued hardware, issues with connecting to or maintaining internet access––decreased youth GPA and standardized test achievement. And, these effect sizes were substantially larger than any negative direct effect from unstructured digital media use.

Across all four empirical studies, digital inequality emerged as the most substantial predictor of academic and developmental decline.

Second: digital skills mediated the relationship between online time and adolescent academic and social outcomes.

Unstructured digital media use, particularly online gaming and web browsing, predicted higher internet and social media skills for adolescents, which in turn predicted stronger academic achievement and self-efficacy (human capital), and social interaction and extracurricular participation (social capital). The positive indirect effect of screen time through skills offset or exceeded any small negative direct effects across several outcomes (supporting our existing peer-reviewed work: Hales & Hampton, 2025, and which you can read more about here).

These exchange processes were amplified when peer and family networks were modeled alongside digital skills, consistent with the premise that online and offline contexts operate together rather than in competition. The effect was not universal: social media skills amplified rather than offset a negative association with consistency of interest, one of the two subscales of grit. The exchange framework describes a contextual and conditional, domain-specific mechanism, not a blanket defense of time spent online.

Implications

If digital inequality, and not screen time, is the primary predictor of adolescent academic and developmental decline, and still warrants concern regarding access quality and experience even with the broader adoption of digital devices across the United States, the current policy emphasis on restriction is pointed at the wrong target. The evidence supports a different set of priorities.

Stable, reliable home (fast) broadband should be treated as an educational prerequisite rather than a consumer amenity. Unreliable connectivity exerted larger downward pressure on human capital than any measure of screen time, and that pressure intensified during the pandemic-era reliance on digital infrastructure. Technology maintenance, device repair, replacement, technical support, and the flexibility to install software and explore the web autonomously, matters as much as initial access, and school-issued devices that restrict autonomous use appear to hinder skill accumulation rather than support it.

Restrictive parental mediation of internet use was negatively associated with grit and self-efficacy at magnitudes comparable to the positive contributions of face-to-face activity. This challenges the assumption that digital restriction functions protectively. Instructive mediation, teaching adolescents to verify information, navigate platforms critically, and mobilize online resources toward meaningful ends, is the posture the data supports.

Finally, the technical skill-building that occurs through gaming, self-directed exploration, and deep web use is skill-building, not wasted time. Closing the persistent gender gap in these domains likely requires legitimizing technical play for girls, rather than restricting it for everyone.

None of the above is an argument that screen time is benign. It is an argument that screen time is the wrong focus, particularly when studied mostly in isolation. Context matters substantially, whether that is time spent on other activities during adolescence, the period of adolescence itself, digital inequality, resources gained from such online use, and how all such factors interact. The factor that predicts whether a given adolescent can convert online engagement into capital outcomes is structural: access, infrastructure, skills, and the autonomy to use them. These factors are distributed unevenly, and its uneven distribution, not hours logged, is what separates adolescents who thrive from those who fall behind.

The full dissertation is available through Michigan State University’s ProQuest archive, or see the embedded full-text PDF below. I’m happy to share papers, preprints, or the underlying framework with anyone interested and working in this area––don’t hesitate to reach out via my contact form. Thanks for reading.

Tags: EMFs health impacts Lansing Board of Water and Light renewable energy smart grid smart meters

The Rush to “Smart” Meters: Maybe Not So Smart?