On the Friday afternoon before Memorial Day, the Trump administration released an Executive Order (EO), ostensibly meant to improve the science used to inform federal policy. As my colleagues have pointed out, that’s absolutely not what it does. It’s important to unpack what’s really hidden under the layers of misleading text.
A dubious premise
The EO gets off to a bad start right away. Generally in science, we cite sources when referencing someone else or making statements that aren’t commonly known or agreed upon. While executive orders don’t often include citations, the failure to cite any of the sweeping claims made in the “Policy and Purpose” section of this EO calls into question whether its authors know anything about scientific standards. Some of the statements made in the Policy and Purpose section are not supported with evidence–for example, the statements justifying the EO’s changes by referencing the public’s distrust of science. Contrary to the administration’s rhetoric, there is evidence that people have a relatively high level of trust for science compared to other professions.
This EO and the resulting guidance are crucial for us to monitor because our government uses science when making decisions that affect American community’s health, access to services, and the infrastructure we count on every day. Certainly, it undermines public trust when decisionmakers suppress or distort science to advance a political goal. This EO, far from addressing that issue, is actually just another attempt to subvert science and enable deception.
The Requirements section of the EO lays out some basic premises of the scientific method, stating that federal science must be: “reproducible; transparent; communicative of error and uncertainty; collaborative and interdisciplinary; skeptical of its findings and assumptions; structured for falsifiability of hypotheses; subject to unbiased peer review; accepting of negative results as positive outcomes; and without conflicts of interest.” All fair enough. But, as my colleague Jules Barbati-Dajches discusses, it doesn’t include the word “independent,” which is fundamental in ensuring that studies are free of bias toward favored industries or ideological preferences. The EO uses scientific terminology to create an impression of support for science, but considering the context in which this EO was published draws a stark contrast–we’ve seen attacks on academic institutions; freezing, decreasing, and eliminating scientific funding; and firing and reassigning federal scientists. This EO is not simply a wasteful attempt to solve a problem that doesn’t exist. It sets the stage for political appointees to exercise total control over science and throw out evidence that doesn’t suit the ideological viewpoints of this administration.
A dangerous process to discard science
One of the many alarming red flags in this EO is the way it talks about transparency and reproducibility in science. These are, of course, important aspects of the scientific method, but again it is important that we consider the context and the history of how these terms have been exploited. After the dubious Policy and Purpose section, and the list of some of the principles of the scientific method, the EO gets specific about what will be required of federal agencies to comply with the stated goals of transparency and reproducibility. These requirements include providing all scientific information including data, models, and source code, except when “prohibited by law, and consistent with relevant policies that protect national security or sensitive personal or confidential business information.” The decisions about whether the science is sufficiently transparent to be considered won’t be made by scientists—they’ll be made by political appointees who will be free to subjectively apply these criteria. We have been here before. It’s worth digging into these parts of this EO, because this is where they are setting up a dangerous process that will enable the politicization of science and science-informed policy.
First, let’s dissect the phrasing in this EO a bit. The term “sensitive personal information” (SPI) is defined differently and used inconsistently under federal government statutes, but there are some basic categories of SPI, including financial, geolocation, health, and data distinguishing people’s identities. The US Code defines SPI using these categories as applying to data held by federal agencies. “Confidential business information” (CBI) refers to information or data held by an individual or company that is proprietary. One difference between these two types of private information is that the US Code sets up a process for businesses and companies to request treatment of certain data and information as CBI, whereas SPI is defined in statute and not generally open to case-by-case requests by individuals. This creates an imbalance between these two types of sensitive or private information. These differences stand out to me, as does the history around the use of forced raw data sharing.
Public health studies, such as those that examine associations between toxic chemical exposures and health effects, often rely on anonymized personal health information—which is a type of SPI—between health care providers and their patients. This allows researchers to aggregate data in order to compare populations, eliminate other variables that could explain the results, or increase in the robustness of the study, all while maintaining the privacy of individual participants. This type of health information is called “protected health information,” and is covered under the Health Insurance Portability and Accountability Act (HIPAA), later amended and finalized as the Health Information Technology for Economic and Clinical Health (HITECH) Act. Maintaining individual privacy is a necessary protection for many reasons, and doing so supports the public health studies that are vital to understand the impacts of, for example, air pollution on children’s respiratory health and comparisons of different populations’ exposures to toxic substances.
The requirement to keep individual data private has been exploited over time to remove consideration of these types of studies from decision making. The tobacco industry has been a historic (and health damaging) leader in this tactic—notably, when Phillip Morris attempted, unsuccessfully, to obtain the raw (protected) data indicting second hand smoke in lung cancer, right as the Environmental Protection Agency (EPA) was set to classify it as a known human (Class A) carcinogen. The fact that the fossil fuel industry has borrowed tactics from the tobacco industry’s science-squashing efforts is well-documented. These and other for-profit groups have developed earlier renditions of “science guidance” that set up barriers to keep scientific results that indicate health harms out of government decision-making. The 1997 “Sound Science Plan”, funded by Phillip Morris, recommend many of the tactics that this EO requires of federal agencies as a strategy to avoid enactment of safeguards around secondhand smoke.
In 2014, the US House of Representatives introduced and passed the so-called “Secret Science Reform Act.” This bill, if enacted, would have mandated that the US EPA could only propose a regulation if ”all of the data, models, methods, and other information in the scientific studies used in its development were publicly available, accessible, and reproducible,” putting the tobacco industry’s carefully-crafted barrier in the way of public health and safety rules. The bill never passed the Senate. But in the first Trump administration, political leaders at EPA proposed the misleadingly-titled Transparency in Pivotal Science Rule, and later amended it.
Under that rule, most studies collecting individual-level data would not have met the sharing requirements and, as a result, would have been given less weight when developing EPA health-based pollution standards and policies. It stands to reason, of course, that effective public health rules for chemicals already in our environment are better when you base them on actual evidence that comes from studies of real people. That proposed rule drew tens of thousands of comments, and was broadly criticized by health researchers and scientific organizations such as the American Academy for the Advancement of Science, scientific journals, state departments of health and environmental protection, and many non-profits and state attorneys general. The Journal of Science wrote explicitly about the nuanced importance of transparency in scientific studies for reproducibility. On February 1, 2021, the rule was vacated following legal challenges based on both the EPA’s lack of authority to enact it and its inherent conflicts with the Clean Air and Water Acts.
Sowing doubt by design
There are other tactics to censor or exclude scientific information that reveal health and environmental harms. One is the “re-review” tactic. The final Transparency in Pivotal Science rule required that EPA conduct additional internal peer review of “pivotal” science, even if those studies had already undergone independent peer review. Section 5 of this gold standard science EO includes this tactic, since it requires “re-review” of “regulations, guidance documents, policies, and scientific evaluations” developed between January 20, 2021 and January 20, 2025. The UCSF library curates a collection of industry documents that includes evidence of plans for industry manipulation of government decision-making, including that industry-developed Sound Science Plan I mentioned earlier—which suggests required data transparency, creating a narrative to decrease trust in certain areas of science, and setting procedural science criteria without input from the scientific community. The Trump administration’s new EO is drawn straight from these corporate disinformation tactics.
We all want science to be free from the influence of industries and organizations that value their profits over truth and the public interest. We want scientific studies to undergo independent and unbiased peer-review, and to have the resources to produce high quality studies. In fact, some scientists have laid out a set of criteria that industry could follow so that their studies would be met with greater trust – like competitive and transparent funding processes, independent research agendas, and freedom to publish. An administration that is truly supportive of science wouldn’t be cutting funding, producing bogus reports, firing scientists, threatening to block scientists from publishing, or claiming falsehoods as facts. Admittedly, sometimes it’s tricky to sift through the rhetoric to figure out what is supportive of science and what is a guise to keep evidence of health harms out of policy-making. Data sharing is not an all-or-nothing issue; it is nuanced and there are levels of data sharing and availability, ranging from general description of the sources to fully accessing the raw data itself. Some observers have proposed divulging all but individual identifiers (e.g. names, addresses) in order to comply with data transparency rules. However, researchers tested this and found that they could successfully re-identify 25% of de-identified participants with publicly available datasets. For medical data that can and should be kept private, that’s too high a risk.
There’s a real way to improve scientific standards
One of the recommendations to protect science from politicization is to enact scientific integrity policies, and UCS has been studying and advocating for these policies for a long time. The Biden administration enacted the “Restoring Trust in Governmental Decisionmaking and Evidence-Based Policymaking” EO, which set up a scientific integrity taskforce and required federal agencies to develop scientific integrity policies. That administration’s Office of Science and Technology Policy adopted this definition of scientific integrity: “the adherence to professional practices, ethical behavior, and the principles of honesty and objectivity when conducting, managing, using the results of, and communicating about science and scientific activities.” This EO followed many recommendations from the Center for Science and Democracy at UCS, with a focus on reducing and eliminating the risk of political interference in science. It set up metrics to develop and monitor high quality scientific integrity policies. Ironically, the Trump administration’s so-called “gold standard” EO regresses all scientific integrity policies back to 2021, before this progress was made.
The danger here is that this EO creates pathways for science to be influenced for political and financial gain, and specifically to down-weight or censor scientific studies and data from decisionmaking if they cannot comply with unnecessarily broad raw-data transparency requirements, (as is the case for most health studies). It bears repeating: the power to decide over whether a study meets the Trump administration’s “standard” would rest in the hands not of scientists but of political appointees, who could use this power to discard any evidence that doesn’t give them an answer they want.
UCS supports transparency practices in government, academia, and industry, but these requirements set out by the Trump administration are designed to be impossible for many valuable studies to meet. In the face of website takedowns, the removal of inspectors general and Freedom of Information Act officers, and a general culture of dishonesty, it’s laughable to think that these “transparency” requirements are offered in good faith. It’s just the latest iteration of a tactic that powerful industries created to shield themselves from accountability.
The U.S. Congress is making strides to move the Scientific Integrity Act forward. This law would actually reduce the risk of the politicization of science in the federal government by requiring all agencies to create and enforce strong scientific integrity policies. To learn more, read here and take action here. The time to speak up is now: saving science saves lives.