What Does it Mean for the Public to “Trust Science”?

by James Lyons-Weiler, PhD, Popular Rationalism, ©2024

(Sep. 18, 2024) — What does it indeed mean to have a society that “trusts science”? The phrase is invoked everywhere, from policy debates to media headlines, and it implies a near-universal reverence for scientific institutions like the NIH, NSF, and NASA. Yet, beneath this notion of trust lies a more fundamental question: Who controls the science we trust? When we say we trust science, are we placing that trust in the systematic process of discovery and data-driven inquiry, or are we entrusting the institutions that direct which questions are asked, which research is funded, and which therapies are prioritized?

The truth is that the vast coffers of these institutions can bias scientific progress by determining what science gets done. This bias doesn’t stem from the scientific method itself but from a systemic entanglement of research funding with political, financial, and institutional interests. As a result, science—particularly in biomedicine—often prioritizes profitable therapies over those that have the most significant positive clinical impact. This creates an unspoken but dangerous precedent: therapies that offer individualized, personalized treatment or those with fewer financial incentives are underexplored.

We live in an era where the public often assumes that the science they hear about is the science that will most benefit them. However, that assumption is often misguided. Effective, low-cost therapies for chronic conditions or precision medicine tailored to individual genetic profiles are frequently ignored. This neglect persists not because they lack scientific merit but because they don’t align with the financial imperatives that dominate research funding. As a result, individualized medicine, driven by prediction science, remains underfunded and underutilized.

The entanglement of funding with profit-driven motives and political narratives creates an entropic loss within the scientific system itself—a progressive decline in innovation, creativity, and analyzability. Science becomes less about discovery and more about maintaining a profitable status quo. As public trust is placed more in institutions, these non-linear, non-static forces skew the trajectory of scientific inquiry away from objective, open-ended discovery and towards financial and political reinforcement.

This is where the problem lies: trusting science in today’s world too often means trusting the agendas of the government agencies that wield control over research funding. Figures like Anthony Fauci and organizations such as the NIH have weaponized funding to reinforce specific narratives, silencing scientists or institutions that might otherwise pursue novel but less profitable areas of research. The threat is real: universities and research hospitals face the possibility of losing all funding if they dare to question these narratives.

If the public truly wants to trust science, then the solution lies in reclaiming control over what is prioritized and researched. This means prioritizing studies that offer effective therapies in biomedicine, especially those with significant positive clinical impact that aren’t necessarily the most profitable. Prediction science—the ability to use scientific knowledge to predict outcomes or states of things – is particularly well-suited to biomedical research. Via Prediction Science, we can tailor treatments to individuals based on their genetics, environment, and lifestyle become central to this effort. Personalized, precision medicine promises better patient outcomes, but it requires a shift in how we approach scientific funding and how we define success in biomedical research.

At its core, science is a method, a way of knowing, and not a tool for political or financial gain. As we rethink the future of scientific inquiry, we must create funding models that prioritize the public good, not just profit margins. This means supporting therapies and research that offer maximum benefit to the patient, not maximum benefit to shareholders. Only then can society genuinely begin to trust science again—not because of the institutions that control it, but because of the integrity of the process itself.

Regulatory Capture Yields Entrenched Priorities

Government institutions like the NIH, NSF, and NASA have long been heralded as the pillars of scientific progress, but their influence on what research gets done—and how—is anything but neutral. By controlling the lion’s share of funding, they dictate the agenda for scientific inquiry. While this structure has facilitated advancements, it has also introduced deep systemic bias, particularly in fields like biomedicine, where profit and political influence are entrenched.

At its core, government funding tends to prioritize research that is safe, predictable, and profitable. This structure naturally favors large pharmaceutical projects or politically expedient research, leaving less room for innovative, less profitable, but clinically significant therapies. What’s often sidelined are studies that may not yield the highest financial return but could drastically improve clinical outcomes, especially in areas like chronic disease management or individualized medicine. This very research holds the potential to reshape healthcare for the better.

The profit-driven bias is especially apparent in the type of therapies that get fast-tracked. For example, conditions with massive patient populations, like cardiovascular disease, often attract substantial funding because of the market potential for new drugs or treatments. But conditions that affect fewer people—or those that require more personalized, predictive treatment—are typically overlooked. This creates a skewed methodological landscape where precision medicine, which could tailor treatments to an individual’s unique genetic makeup or lifestyle, is underfunded and undervalued.

Moreover, the structure of government funding fosters a conservative, non-linear dynamic in research. Agencies like the NIH tend to favor projects that produce incremental advancements rather than groundbreaking breakthroughs, as the latter often come with greater risk. This conservative approach limits the exploration of non-static, adaptive therapies that respond to the evolving understanding of complex diseases like cancer or neurological disorders. Instead, funding flows to established ideas that promise safe returns—both financially and politically.

One of the most damaging aspects of this system is the weaponization of funding. Figures like Anthony Fauci have exemplified how funding can be wielded not as a tool for discovery but as a mechanism for enforcing narratives. Universities, research hospitals, and individual scientists are often pressured to align with prevailing ideologies or risk losing vital resources. Dissenting voices—those who challenge mainstream narratives or propose less conventional research pathways—are often marginalized. For many institutions, the cost of going against the grain is the loss of all funding, a death sentence in the competitive world of scientific research.

This creates a feedback loop where institutions become increasingly risk-averse, producing research that reinforces existing narratives rather than challenging them. As a result, science becomes less dynamic, less creative, and ultimately less effective at addressing the most pressing health issues. Innovative research into holistic, individualized approaches to healthcare—for instance, exploring the interaction between genetics, lifestyle, and environment to predict and prevent diseases—receives far less attention than it deserves.

A particularly alarming consequence of this funding bias is the entropic loss of scientific diversity. The entropy of mathematics demonstrates how analyzability declines as complexity is reduced for elegance. It so too does the creativity of science decline when political and financial motives restrict research agendas. Via a beauracratic nonlinearity, science becomes a boring, linear, tightly constrained system, one that reinforces established power structures rather than pushing the boundaries of human knowledge.

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