Post lunch conversation with a colleague: trust in science

Yesterday, I had lunch with a colleague at a favorite BBQ spot in Arlington. Both of us work in science communication, so naturally our conversation drifted to the question that’s been nagging at many of us: why has public trust in scientific institutions declined in recent years? By the time we finished our, actually healthy food, we’d both come to the same conclusion—the current way scientists communicate with the public might be contributing to the problem.

From vaccine hesitancy to questions about research reliability, the relationship between science and society has grown more complex. To understand this dynamic, we need to examine not only what people think about science but also how different cultures approach the validation of knowledge itself.

Harvard scholar Sheila Jasanoff offers valuable insights through her concept of “civic epistemologies”—the cultural practices societies use to test and apply knowledge in public decision-making. These practices vary significantly across nations and help explain why scientific controversies unfold differently in different places.

American Approaches to Knowledge Validation

Jasanoff’s research identifies distinctive features of how Americans evaluate scientific claims:

Public Challenge: Americans tend to trust knowledge that has withstood open debate and questioning. This reflects legal traditions where competing arguments help reveal the truth.

Community Voice: There’s a strong expectation that affected groups should participate in discussions about scientific evidence that impacts them, particularly in policy contexts.

Open Access: Citizens expect transparency in how conclusions are reached, including access to underlying data and reasoning processes.

Multiple Perspectives: Rather than relying on single authoritative sources, Americans prefer hearing from various independent institutions and experts.

How This Shapes Science Communication

These cultural expectations help explain some recent communication challenges. When public health recommendations changed during the COVID-19 pandemic, this appeared to violate expectations for thorough prior testing of ideas. Similarly, when social platforms restricted specific discussions, this conflicted with preferences for open debate over gatekeeping.

In scientific fields like neuroscience, these dynamics have actually driven positive reforms. When research reliability issues emerged, the American response emphasized transparency solutions: open data sharing, study preregistration, and public peer review platforms. Major funding agencies now require data management plans that promote accountability.

Interestingly, other countries have addressed similar scientific quality concerns in different ways. European approaches have relied more on institutional reforms and expert committees, while American solutions have emphasized broader participation and transparent processes.

Digital Platforms and Knowledge

Online platforms have both satisfied and complicated American expectations. They provide the transparency and diverse voices people want, but the sheer volume of information makes careful evaluation difficult. Platforms like PubPeer enable post-publication scientific review that aligns with cultural preferences for ongoing scrutiny; however, the same openness can also amplify misleading information.

Building Better Science Communication

Understanding these cultural patterns suggests more effective approaches:

Acknowledge Uncertainty: Present science as an evolving process rather than a collection of final answers. This matches realistic expectations about how knowledge develops.

Create Meaningful Participation: Include affected communities in research priority-setting and policy discussions, following successful models in patient advocacy and environmental research.

Increase Transparency: Share reasoning processes and data openly. Open science practices align well with cultural expectations for accountability.

Recognize Broader Concerns: Understand that skepticism often reflects deeper questions about who participates in knowledge creation and whose interests are served.

Moving Forward

Public skepticism toward science isn’t simply a matter of misunderstanding—it often reflects tensions between scientific institutions and cultural expectations about legitimate authority. Rather than dismissing these expectations, we might develop communication approaches that honor both scientific rigor and democratic values.

The goal isn’t eliminating all skepticism, which serves essential functions in healthy societies. Instead, it channels critical thinking in ways that strengthen our collective ability to address complex challenges that require scientific insight.

Bold Ventures in Science: NSF’s NEON and NIH’s BRAIN Initiative

My favorite projects…

As loyal readers know, these are my two favorite science initiatives. They stand out as beacons of progress: the National Science Foundation’s National Ecological Observatory Network (NEON) and the National Institutes of Health’s Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative. These groundbreaking endeavors showcase the commitment of U.S. science agencies to tackling complex, large-scale challenges that could revolutionize our understanding of the world around us and within us.

NSF’s NEON: A Continental-Scale View of Ecology

Imagine having a window into the ecological processes of an entire continent. That’s precisely what NEON aims to provide. Initiated in 2011, this audacious project is creating a network of ecological observatories spanning the United States, including Alaska, Hawaii, and Puerto Rico.

Yes, NEON has faced its share of challenges. The project’s timeline and budget have been adjusted since its inception, growing from an initial estimate of $434 million to around $469 million, with completion delayed from 2016 to 2019. But let’s be honest: when did you last try to build a comprehensive ecological monitoring system covering an entire continent? These adjustments reflected the project’s complexity and the learning curve in such a pioneering endeavor.

The payoff? NEON is now collecting standardized ecological data across 81 field sites from Hawaii to Puerto Rico and in between. This massive time series in some 200 dimensions will allow scientists to analyze and forecast ecological changes over decades. From tracking the impacts of climate change to understanding biodiversity shifts, NEON provides invaluable insights that could shape environmental policy and conservation efforts for future generations.

NIH’s BRAIN Initiative: Decoding Our Most Complex Organ

Meanwhile, the NIH’s BRAIN Initiative is taking on an equally monumental task: mapping the human brain. Launched in 2013, this project is aptly named, as it requires a lot of brains to understand… well, brains.

With annual funding that has grown from an initial $100 million to over $500 million, the BRAIN Initiative is a testament to the NIH’s commitment to unraveling the mysteries of neuroscience. Mapping all 86 billion neurons in the human brain by 2026 might seem a tad optimistic. But I’m increasingly impressed with our progress, and I am hopeful we’ll be able to get some meaningful statistics about variability across individuals.

The initiative has already led to the development of new technologies for studying brain activity, potential treatments for conditions like Parkinson’s disease, and insights into how our brains process information. It’s like a real-life adventure into the final frontier, except instead of outer space, we’re exploring the inner space of our skulls.

The Challenges: More Feature Than Bug

Both NEON and the BRAIN Initiative have faced obstacles, from budget adjustments to timeline extensions. But in the world of cutting-edge science, these challenges are often where the real learning happens. They’ve pushed scientists to innovate, collaborate, and think outside the box (or skull, in the case of BRAIN).

These projects have also created unique opportunities for researchers to develop new skills. Grant writing for these initiatives isn’t just an administrative hurdle; it’s a chance to think big and connect individual research to grand, overarching goals. It’s turning scientists into visionaries, and isn’t that worth a few late nights and extra cups of coffee?

Conclusion: Big Science, Bigger Possibilities

NEON and the BRAIN Initiative represent more than just large-scale scientific projects. They’re bold statements about the value of basic research and the importance of tackling complex, long-term challenges. They remind us that some questions are too big for any single lab or institution to answer alone.

As these projects evolve and produce data, they’re not just advancing our understanding of ecology and neuroscience. They’re also creating models for conducting science at a grand scale, paving the way for future ambitious endeavors.

So here’s to the scientists, administrators, and visionaries behind NEON and the BRAIN Initiative. They’re showing us that with enough creativity, persistence, and, yes, funding, we can tackle some of the biggest questions in science. And who knows? The next breakthrough in saving our planet or understanding consciousness could be hidden in the data they’re collecting right now.