What Counts as Evidence

This is the third post of three in a series leading up to the 16th annual International Forum on Consciousness, taking place in Madison this May. Hosted by the BTC Institute, Promega and Usona Institute, the forum gathers scientists, philosophers, and practitioners from dozens of different fields to investigate the nature of the mind. This year’s theme, “Unspoken Intelligence,” explores forms of perception and knowing that fall outside conventional cognition.

In 1845, mathematician Urbain Le Verrier calculated where an unseen planet had to be based on irregularities in Uranus’s orbit, wrote a letter to an observatory telling them where to point their telescope, and Neptune was there. He found a planet without ever looking up.

This is what third-person inquiry looks like at its best: observe from the outside, measure what anyone with the right instruments can measure, build a model precise enough to predict what no one has seen yet. Then look. The history of science is full of such moments, equations pointing to phenomena that hadn’t been detected, particles that hadn’t been observed, forces that hadn’t been measured. The method works because it is ruthlessly disciplined about what counts as evidence. The observer is removed, the conditions controlled, and the measurement trusted.

That discipline is not a limitation. It is the engine of over four centuries of extraordinary results. It gave us germ theory, the structure of DNA, and the sequenced human genome. Every time something seemed to resist physical explanation, the method eventually found the mechanism and the method held. The winning streak was long enough that the assumption underneath it stopped looking like an assumption. Outside-in, third-person, measurable evidence stopped looking like one way of knowing. It started looking like the definition of knowing itself.

The assumption felt safe because it had earned its confidence. Digestion, heredity, mental illness, each had seemed to resist physical explanation until it didn’t. The pattern was consistent enough that the method felt inevitable rather than chosen.

Then science turned toward consciousness, and the winning streak entered dangerous territory.


Here is the problem, what philosopher David Chalmers named the “hard problem” of consciousness in 1995.

To understand what Chalmers meant, it helps to start with his own illustration. When you see red, something measurable happens. Light hits the retina. Signals travel along the optic nerve. Specific regions of the visual cortex activate in patterns that neuroscientists can map with increasing precision. All of that is, in principle, fully describable by the third-person, outside-in approach. Given enough time and instruments, you can trace the whole sequence.

What you cannot describe from the outside is what red looks like. The redness of red, that specific quality of experience that exists only in the moment of seeing it, is not in the neural map. No better scanner will find it there, because the felt quality of the experience isn’t a physical thing hiding in the data. It exists only from the inside. The outside measurement, however precise, cannot reach it.

Chalmers used “hard” deliberately, in contrast to what he called the “easy problems” of consciousness: how the brain integrates information, focuses attention, produces behavior. Those are genuinely difficult, but the outside-in approach knows how to go after them. The hard problem is different in kind. It’s the question that remains even after you’ve solved all of the “easy” ones: why does any of it feel like anything at all?

Think of it this way: everything the brain does could, in principle, happen without any felt experience attached. Processing, responding, behaving, all of it could run like a machine in the dark, with no one home. The question Chalmers is asking is why it doesn’t. Philosophers ask it this way: why is there something it’s like to be you, right now, reading this?

No amount of outside-in evidence, however precise, touches that question, not because the science is insufficient but because the method was specifically designed to exclude first-person data. That exclusion was the whole point. It’s what made the outside-in approach so powerful everywhere else.

With consciousness, the method’s central design decision runs into a question it wasn’t built to answer: how do you study first-person experience when your method was built to exclude first-person data?

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More Than Beer and Cheese: Why Wisconsin Has Always Been Good Ground for Science 

Challenging Assumptions About Innovation

When people talk about places where science and technology tend to flourish, a few names surface almost immediately. Silicon Valley, Boston, Seattle, Houston. Cities associated with density, competition and speed.

For many people outside the state, Wisconsin still collapses into a short list of associations: beer, cheese, cold winters, maybe a football team. Biotechnology rarely makes that list.

That hesitation usually has less to do with science itself and more to do with assumptions about where innovation is supposed to live. National Wisconsin Day, celebrated February 15, is a good moment to look past those assumptions and consider what Wisconsin has quietly offered for a long time: an environment and culture that is well-suited for scientific advances.

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The Science of Slipping… Blame the Molecules!

Whether it’s Home Alone’s booby-trapped icy steps, Bambi learning his legs have zero traction, or an Ice Age chase scene defying gravity, ice has been comedy gold for decades. In real life, the joke lands a little harder (sometimes literally).

Slippery Ice

We all know ice is slippery. The more surprising part is why it’s slippery and how long it took scientists to start agreeing on something closer to an answer. Researchers have long known the surface of ice behaves like it’s wearing a microscopic “wet” layer that lubricates motion. What they’ve argued about for nearly 200 years is what creates that layer in the first place (3,4).

So, let’s treat this like a mystery. Ice is the crime scene. Your dignity is the victim. Here are the main suspects.

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Why Do We Love Being Scared? The Science Behind Horror Movies

Haunted mansion with pointed towers in a foggy, moonlit forest, creating a spooky, eerie atmosphere.

There’s something oddly captivating about watching a film that makes you jump, scream, or better yet—a film that sticks with you long after watching. Millions of people embrace the fear, willingly diving into the dark world of horror movies. But why? What is the appeal of subjecting ourselves to terror? The reasons we watch and enjoy scary movies go far beyond the jump scares—they’re deeply psychological.

For those who find themselves covering their eyes or clutching the nearest pillow, it might be hard to understand. Yet, as the hair-raising month of October ends, many people spent the 31 days leading up to Halloween watching films designed to scare the daylights out of them. In this blog, we explore why people enjoy fear (or why they don’t) and what psychology reveals about the movies that truly terrify us.

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The Casual Catalyst: Science Conversations and Cafes

There is no shortage of stories about great scientific collaborations that have taken root as the result of an excited conversation between two scientists over sandwiches and beer at a bar or a deli. One of the most famous examples of such a conversation was that between Herbert Boyer and Stanley Cohen when they attended a conference on bacterial plasmids in 1972—that very conversation led to the formation of the biotechnology field as the two scientists worked together to clone specific regions of DNA (1).  

“Over hot pastrami and corned beef sandwiches, Herbert Boyer and Stanley Cohen opened the door to genetic engineering and laid the foundations for gene therapy and the biotechnology industry.”  

Steven Johnson, author of Where Do Good Ideas Come From, credits the English coffee house as being crucial to the spread of the enlightenment movement in the 17th and 18th centuries (2). He argues that coffee houses provide a space where ideas can come together and form networks. In fact, he defines the concept of “idea” not as a single entity—a grand thought that poofs into existence upon hard work—but at its simplest level, a new idea is a new network of neurons firing in sync with each other.  

Johnson further argues that the development of great new ideas not only requires a space for ideas to bump into each other, connect and form a network, but also that great ideas are rarely the product of a single “Eureka” moment. Rather, they are slowly developing, churning hunches that have very long incubation periods (2).  

Science is Ripe with “Coffee House” Discoveries

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The Central Dogma of Promega: The Story and Science Behind Our Kit Packaging Design

An amazing transformation is taking place, unseen and unnoticed, within the microscopic bits that make you, you.

A tightly coiled lattice unspools to reveal a sinuous DNA stand. Along its length, tendrils of RNA sprout, growing bit by genetic bit. Eventually, the signal to stop and break away arrives, yielding a new strand of RNA that faithfully transcribes the DNA strand’s genetic code. Proteins trim and splice this new growth, pruning it so it takes its final form, messenger RNA. More proteins then ferry this mRNA strand through a pore in the nuclear envelope into the open space of the cell’s cytoplasm. Ribosomes and codon-carrying tRNA alight onto the released mRNA strand, reading the instructions it has carried from the DNA in the nuclear nursery. From this trio new forms emerge, bulbous proteins shaped by their destined purpose.

And so it goes, every second of every day, in the tens of trillions of cells in your body…

…And on the tens of thousands of kit packages we deliver to customers across the globe every year.

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Decades of Discovery: How the NCI-60 Revolutionized Cancer Drug Screening

The National Cancer Institute’s NCI-60 drug screening panel, comprised of 60 diverse human cancer cell lines, has been a cornerstone in advancing cancer research and drug discovery since its inception in the late 1980s. Developed in response to the need for more predictive and comprehensive preclinical models, the NCI-60 facilitates the screening of thousands of compounds annually, aiming to identify potential anti-cancer drugs across a broad spectrum of human cancers. This article traces the origins, development, and evolution of the NCI-60 panel, highlighting its significant role in advancing our understanding of cancer and therapeutic agents.  

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Knitting Needles, Balls of Yarn and the First Molecular Model

ball-and-stick model of a molecule

One day while reading a knitting blog I discovered in 1883 a Scottish chemist created the first “ball-and-stick” model of a molecule using knitting needles and balls of yarn. This initial ball-and-stick molecule represents the structure of sodium chloride and is constructed of knitting needles, representing the bonds, and alternating balls of blue and red yarn, representing the atoms of sodium and chloride. It was displayed as part of the International Year of Chemistry 2011 activities.

The chemist who created this model was Alexander Crum Brown, distinguished chemistry and professor at the University of Edinburgh, and one of his particular interests was the arrangements of atoms in molecules and the depiction of these structures. Those of us who spent countless hours poring our organic chemistry books and molecular model sets trying to understand nucleophilic attacks and SN1 and SN2 reactions have Alexander Crum Brown to thank. Those students who now use computer 3D modeling programs to accomplish the same studies (without the delight of chasing down the last nitrogen atom that has rolled off the desk and under the dresser) are also indebted to Dr. Brown.

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