Where does trusted information come from? In a world of misinformation, where everyone is skeptical of everything, at least we can rely on expert, authoritative government agencies like the Environmental Protection Agency, the Centers for Disease Control, the Patent Office, and the Food and Drug Administration, right? Right!?
Not so fast, Professor Janet Freilich persuasively but depressingly argues in the smart, eye-opening, “why didn’t I think of that” Government Misinformation Platforms. Freilich’s central point is fairly straightforward (although the article is rich with nuance and detail): We usually laud the government’s sharing of information because government-provided information is usually pretty trustworthy and useful for all kinds of things, and because transparency is usually a good goal. There’s a whole law (the Freedom of Information Act) about getting government to share information on request, supplemented by various transparency efforts. But there are also many government-run platforms that share information that the government itself didn’t produce—and in fact, that share unvetted, frequently incorrect, sometimes deliberately misleading information. When people see information on these platforms and think “government information = trustworthy,” then the problems start.
But is this really a big problem? Isn’t it just a couple of examples? In Part II, Freilich convincingly dismantles that resistant questioning. She recounts a disheartening parade. Let’s say people want to know who’s releasing toxins into the environment. The first obvious step would be to visit an EPA site to find out…but the data are compiled by companies and unvetted. What about a government-run list of ongoing clinical trials? Not vetted by NIH or FDA! Patents are examined, so they must surely be correct, at least. Nope, pronounces Freilich, relying on some of her terrific earlier work showing that patents are full of fictional experiments (with results laid out!) that the patentee never actually conducted. Maybe the most prominent example is the Vaccine Adverse Events Reporting System (VAERS), run by CDC. It lists thousands of people who died after getting the COVID-19 vaccine. You guessed it—those reports are self-uploaded, unvetted, and have absolutely nothing even pretending to demonstrate causation. But there the data are, on a CDC website.
This information both matters and misleads. Freilich persuasively shows that people do rely on information on these government-run platforms, and at least some treat it as authoritative. Scientists read patents, even when the contents aren’t accurate or are based on totally fictitious experiments (Did you know that the difference between an experiment that happened in a patent versus one that didn’t is whether it’s described in the past or present tense? Lots of patent-reading scientists don’t!). People rely on clinical trial listings as some sort of imprimatur. And VAERS data are trumpeted on news sites, despite big disclaimers on the website about the unreliability of the information.
So that’s one big problematic consequence: People believe things that are wrong because they see them on government websites and mistakenly think they’re government vetted.
The opposite problem also occurs: People start to mistrust the government because it’s sharing bad information. If there’s garbage on CDC and FDA and EPA and PTO and NIH websites, how can people be sure that those agencies are worthy of trust—or at least that the things on their websites are worth trusting? That decrease in trust is awfully problematic for those agencies, especially in a time when trust in government agencies is declining.
On a broader level, Freilich exposes the fascinating, troublesome, and unstable gap between “trusted” and “trustworthy.” It’s a space where con artists live, one that research hospitals have struggled with in the bioethics space, one the government seems to have wandered unwittingly into—and one the government needs to exit expeditiously.
The problem of government misinformation, alas, is easier limned than solved. Freilich presents a menu of options—including increased disclaimers, hurdles to posting information, correcting incorrect information, and more—but they’re all partial palliatives limited by capacity, will, or law. There’s no silver bullet here.
In a sense, the complex tangle of partial potential solutions is unsurprising. This paper exemplifies a really fun genre of legal scholarship, what we might call the “Hey this problem is actually widespread” paper. Freilich has deep expertise in the foibles of the patent system, and some of that work has focused on how patents aren’t so reliable, even though one might reasonably think they are a high-quality source of technical information (that’s part of the point of the patent system, after all). There’s the aforementioned issue of fictitious experiments. Even worse, when patents are based on experiments that are so wrong the associated scientific papers are actually retracted, the patent system seems…unconcerned. (Not great!). Government Misinformation Platforms steps back to show that this information quality problem is disturbingly widespread across many contexts. But while there might be at least quasi-straightforward solutions in the limited context of patent examination and publication, the nuances of how those solutions work, or don’t, changes quite a bit from context to context. Freilich deftly and clearly recognizes this complexity, but it’s an ongoing challenge.
A particularly fun thing about the paper is that it lends itself to exploration and further work both conceptual and applied. On a broad theoretical level, how should the government perform its weirdly mixed role in developing, promulgating, aggregating, and sharing information going forward? Where’s the right balance between easy, quick access and maintaining trust and accuracy? Is information-provision trustworthiness distinct from other-stuff trustworthiness, or are they inextricably intertwined? And on the nitty-gritty practical level, after Freilich has unearthed so many spheres of government-enabled misinformation, what’s the right solution for each? Should EPA treat misinformation differently than FDA? CDC versus NIH? How might one practically taxonomize them and link effective interventions to contextual cues? There’s so much to be done! Freilich has opened a new and tremendously interesting door in how we think about information and the government; I look forward to seeing what grows on the other side.
