How researchers conceptualize a disease informs how they treat it. Cancer is often described as uncontrollable cell growth triggered by genetic damage. But cancer can also be seen from angles that emphasize mathematics, evolutionary game theory and physics, among others.

Molecular biology has brought significant advances in making it possible to live with cancer as a chronic illness rather than a fatal disease. Alternative frameworks, however, can offer scientists additional insights on how to prevent tumors from spreading throughout the body and becoming resistant to treatment.

Here are a few unconventional lenses through which researchers are viewing cancer with fresh eyes, drawn from The Conversation’s archives.

1. Evolution and natural selection of cancer

The body is far from a wonderland for cells. Each individual cell competes against trillions of others for finite space and nutrients. If they’re able to cooperate in an orderly enough fashion, sharing resources and dividing labor, the collective functions effectively. Cancer cells, however, cheat the system^[1]: They hog resources, take up as much space as possible and refuse to die^[2].

In this way, cancer can be thought of as an evolutionary disease^[3] – these are cells that have developed the genetic mutations to outcompete their neighbors, and subsequent cell generations inherit this survival advantage. Cancer cells benefit at the expense of the collective until the entire organism collapses.

Oncologist Monika Joshi^[5] and pathologists Joshua Warrick^[6] and David DeGraff^[7] believe that understanding evolution is key to understanding cancer. Screening programs are effective, for example, because removing a nascent tumor is easier than treating one that has evolved the ability to spread. Cancer cells likewise become resistant to treatments because they’re pushed to further evolve to survive.

Some researchers are applying the principles of evolutionary game theory to reduce treatment resistance^[8] and optimize therapies for children^[9].

“The fight against cancer is a fight against evolution, the fundamental process that has driven life on Earth since time immemorial,” they wrote. “This is not an easy fight, but medicine has made tremendous progress.”

---

Read more: Every cancer is unique – why different cancers require different treatments, and how evolution drives drug resistance^[10]

---

2. Fluid mechanics of cancer

As much as cancer is a disease that respects no boundaries, tumor cells are still shaped by their environment. Unlike healthy cells that take the hint when their presence isn’t wanted, however, tumor cells not only survive but thrive in stressful conditions^[11]. Isolated cancer cells able to adapt to harsh settings are the ones that establish metastatic colonies and become resistant to treatment.

While researchers have focused on how biochemical signals direct cells to move from one location to another, a cell’s physical environment also affects where it migrates. Mechanical engineer Yizeng Li^[12] found that a cell’s “solid” and “fluid” surroundings influence its movement.

Cancer cells encounter varying degrees of fluid viscosity, or thickness, as they travel through the body. Li and her team found that breast cancer cells counterintuitively move faster in high viscosity environments by changing their structure. This meant that fluid viscosity serves as a mechanobiological cue for cancer cells to metastasize^[13].

“Cancer patients usually don’t die from the original source of the tumor but from its spread to other parts of the body,” Li wrote. “Understanding how fluid viscosity affects the movement of tumor cells could help researchers figure out ways to better treat and detect cancer before it metastasizes.”

---

Read more: How cancer cells move and metastasize is influenced by the fluids surrounding them – understanding how tumors migrate can help stop their spread^[16]

---

3. Inflammation link to cardiovascular disease

Apart from being leading causes of death around the world, cardiovascular disease and cancer may not initially seem to have much in common. The many risk factors they share, however – like poor diet, smoking and chronic stress – coalesce with chronic inflammation: persistent, low-grade activation of the immune system can damage cells in ways that encourage either disease to develop.

For biomedical engineer Bryan Smith^[17], the developmental parallels between these diseases signal they could be treated at the same time^[18].

Drugs can be repurposed^[19] to target diseases for which they weren’t originally designed. Certain drugs, for example, can direct immune cells called macrophages to consume both cancer cells and the cellular debris that contribute to cardiovascular plaques.

“As basic science discovers other molecular parallels between these diseases, patients will be the beneficiaries of better therapies that can treat both,” wrote Smith.

---

Read more: Could a single drug treat the two leading causes of death in the US: cancer and cardiovascular disease?^[20]

---

4. Mathematics of cancer

In certain contexts, math has unique strengths in describing the natural world^[21]. For instance, epigenetics – where and when genes are turned on or off – plays as much a role in cancer progression as direct changes to the genetic code. Epigenetic changes can alter healthy cells to the point of losing their normal form and function. But the randomness of these changes makes it difficult to tease out pathological from normal genetic activity.

A mathematical concept called stochasticity – or how the randomness of the steps of a process influences how predictable its outcome will be – lends a logical framework to the epigenetic changes contributing to cancer^[22], clarifying when healthy cells rapidly develop into tumor cells.

Stochasticity is commonly used to study stock market behavior and epidemic disease spread, and researchers quantify it by examining the degree of uncertainty, or entropy, of a particular outcome. Identifying high entropy areas in the genome could offer another approach to cancer detection and drug design.

Cancer geneticist Andrew Feinberg^[23] has been using entropy to quantitatively describe the epigenetics of cancer. He and his colleagues found that high entropy regions of the genome in the skin become even more entropic with sun damage, increasing the chance of developing cancer. This offers a potential explanation for why cancer risk significantly increases with age.

“Epigenetic entropy shows that you can’t fully understand cancer without mathematics,” Feinberg wrote. “Biology is catching up with other hard sciences in incorporating mathematical methods with biological experimentation.”

---

Read more: Cancer evolution is mathematical – how random processes and epigenetics can explain why tumor cells shape-shift, metastasize and resist treatments^[24]

---

5. A public health issue

Cancer is a disease that develops in an individual, but its socially derived causes and societal-wide effects are hardly limited to a single person.

Take the case of lung cancer. It is stigmatized as a disease brought on by poor lifestyle choices – a consequence of a personal decision to use tobacco products. But as thoracic oncologist Estelamari Rodriguez^[25] noted, the face of lung cancer has changed.

“Over the past 15 years, more women, never-smokers and younger people are being diagnosed with lung cancer,” she wrote. While lung cancer rates have significantly decreased for men, they have substantially risen for women^[26] around the world. Despite being the leading cause of cancer death among women, screening rates remain low compared with other cancers.

More broadly, cancer symptoms are often unrecognized or misdiagnosed, not only for women^[27] but also for many marginalized populations, including people of color^[28], transgender patients^[29] and the uninsured^[30].

These disparities are due in part to biases in medical education and clinical research^[31] that fail to prepare clinicians to care for the diversity of patients they’ll encounter. Tenuous access to preventive care^[32] and disproportionate exposure to carcinogens^[33] among certain populations compound these inequities.

The purview of cancer goes far beyond a single discipline. It takes a village of researchers, policymakers and patient advocates to achieve effective and accessible cancer care for all.

---

Read more: Lung cancer rates have decreased for the Marlboro Man, but have risen steeply for nonsmokers and young women – an oncologist explains why^[34]

---

For centuries, the quest for new elements^[1] was a driving force in many scientific disciplines. Understanding an atom’s structure and the development of nuclear science allowed scientists to accomplish the old goal of alchemists^[2] – turning one element into another^[3].

Over the past few decades, scientists in the United States^[4], Germany^[5] and Russia^[6] have figured out how to use special tools to combine two atomic nuclei^[7] and create new, superheavy elements^[8].

These heavy elements usually aren’t stable. Heavier elements have more protons^[11], or positively charged particles in the nucleus; some that scientists have created have up to 118^[12]. With that many protons, the electromagnetic repulsive forces between protons in the atomic nuclei overwhelm the attractive nuclear force that keeps the nucleus together.

Scientists have predicted for a long time^[13] that elements with around 164 protons could have a relatively long half-life^[14], or even be stable. They call this the “island of stability^[15]” – here, the attractive nuclear force is strong enough to balance out any electromagnetic repulsion.

Since heavy elements are difficult to make in the lab, physicists like me^[17] have been looking for them elements everywhere, even beyond the Earth^[18]. To narrow down the search, we need to know what sort of natural processes could produce these elements. We also need to know what properties they have, like their mass densities.

Calculating density

From the outset, my team wanted to figure out the mass density of these superheavy elements. This property could tell us more about how the atomic nuclei of these elements behave. And once we had an idea about their density, we could get a better sense of where these elements might be hiding.

To figure out the mass density and other chemical properties^[19] of these elements, my research team used a model that represents an atom of each of these heavy elements as a single, charged cloud. This model works well for large atoms, particularly metals that are laid out in a lattice structure.

We first applied this model^[20] to atoms with known densities and calculated their chemical properties. Once we knew it worked, we used the model to calculate the density of elements with 164 protons, and other elements in this island of stability.

Based on our calculations, we expect stable metals with atomic numbers around 164 to have densities between 36 to 68 g/cm³ (21 to 39 oz/in³). However, in our calculations, we used a conservative assumption about the mass of atomic nuclei. It’s possible that the actual range is up to 40% higher.

Asteroids and heavy elements

Many scientists believe that gold^[21] and other heavy metals were deposited on Earth’s surface after asteroids collided with the planet^[22].

The same thing could have happened with these superheavy elements, but super mass dense heavy elements sink into ground and are eliminated from near the Earth’s surface by the subduction of tectonic plates^[23]. However, while researchers might not find superheavy elements on Earth’s surface, they could still be in asteroids like the ones that might have brought them to this planet.

Scientists have estimated that some asteroids have mass densities greater than that of osmium^[24] (22.59 g/cm³, 13.06 oz/in³), the densest element found on Earth.

The largest of these objects is asteroid 33, which is nicknamed Polyhymnia^[25] and has a calculated density of 75.3 g/cm³ (43.5 oz/in³). But this density might not be quite right, since it’s quite difficult to measure the mass and volume of far-away asteroids.

Polyhymnia isn’t the only dense asteroid out there. In fact, there’s a whole class of superheavy objects, including asteroids, which could contain these superheavy elements. Some time ago, I introduced the name Compact Ultradense Objects, or CUDOs^[26], for this class.

In a study published in October 2023 in the European Physical Journal Plus^[27], my team suggested some of the CUDOs orbiting in the solar system might still contain some of these dense, heavy elements^[28] in their cores. Their surfaces would have accumulated normal matter over time and would appear normal to a distant observer.

So how are these heavy elements produced^[29]? Some extreme astronomical events, like double star mergers^[30] could be hot and dense enough to produce stable superheavy elements.

Some of the superheavy material could then remain on board asteroids created in these events. They could stay packed in these asteroids, which orbit the solar system for billions of years.

Looking to the future

The Eurpoean Space Agency’s Gaia mission^[31] aims to create the largest, most precise three-dimensional map of everything in the sky. Researchers could use these extremely precise results to study the motion of asteroids^[32] and figure out which ones might have an unusually large density.

Space missions are being conducted to collect material from the surfaces of asteroids and analyze them back on Earth. Both NASA and the Japanese state space agency JAXA^[33] have targeted low density near-Earth asteroids with success. Just this month, NASA’s OSIRIS-REx^[34] mission brought back a sample. Though the sample analysis is just getting started, there is a very small chance it could harbor dust containing superheavy elements accumulated over billions of years.

One mass-dense dust and rock sample brought back to Earth would be enough. NASA’s Psyche mission^[36], which launched in October 2023, will fly to and sample a metal-rich asteroid^[37] with a greater chance of harboring superheavy elements. More asteroid missions like this will help scientists better understand the properties of asteroids orbiting in the solar system.

Learning more about asteroids and exploring potential sources of superheavy elements will help scientists continue the century-spanning quest to characterize the matter that makes up the universe and better understand how objects in the solar system formed.

Evan LaForge, an undergraduate student studying physics and mathematics, is the lead author on this research^[38] and helped with the writing of this article, along with Will Price, a physics graduate student.

Only “persons” can engage with the legal system – for example, by signing contracts or filing lawsuits. There are two main categories of persons^[1]: humans, termed “natural persons,” and creations of the law, termed “artificial persons.” These include corporations, nonprofit organizations and limited liability companies^[2] (LLCs).

Up to now, artificial persons have served the purpose of helping humans achieve certain goals. For example, people can pool assets in a corporation and limit their liability vis-à-vis customers or other persons who interact with the corporation. But a new type of artificial person is poised to enter the scene – artificial intelligence systems, and they won’t necessarily serve human interests.

As scholars^[3] who study AI and law^[4] we believe that this moment presents a significant challenge to the legal system: how to regulate AI within existing legal frameworks to reduce undesirable behaviors, and how to assign legal responsibility for autonomous actions of AIs.

One solution is teaching AIs to be law-abiding entities^[5].

This is far from a philosophical question. The laws governing LLCs in several U.S. states^[6] do not require that humans oversee the operations of an LLC. In fact, in some states it is possible to have an LLC with no human owner^[7], or “member” – for example, in cases where all of the partners have died. Though legislators probably weren’t thinking of AI when they crafted the LLC laws, the possibility for zero-member LLCs opens the door to creating LLCs operated by AIs.

Many functions inside small and large companies have already been delegated to AI in part, including financial operations, human resources^[8] and network management, to name just three. AIs can now perform many tasks as well as humans do. For example, AIs can read medical X-rays^[9] and do other medical tasks, and carry out tasks that require legal reasoning^[10]. This process is likely to accelerate due to innovation and economic interests.

A different kind of person

Humans have occasionally included nonhuman entities like animals^[11], lakes^[12] and rivers^[13], as well as corporations^[14], as legal subjects. Though in some cases these entities can be held liable for their actions, the law only allows humans to fully participate in the legal system.

One major barrier to full access to the legal system by nonhuman entities has been the role of language^[15] as a uniquely human invention and a vital element in the legal system. Language enables humans to understand norms and institutions that constitute the legal framework. But humans are no longer the only entities using human language.

The recent development^[16] of AI’s ability to understand human language^[17] unlocks its potential to interact with the legal system. AI has demonstrated proficiency in various legal tasks, such as tax law advice^[18], lobbying^[19], contract drafting and legal reasoning^[20].

An LLC established in a jurisdiction that allows it to operate without human members could trade in digital currencies^[22] settled on blockchains^[23], allowing the AI running the LLC to operate autonomously and in a decentralized manner that makes it challenging to regulate. Under a legal principle known as the internal affairs doctrine^[24], even if only one U.S. state allowed AI-operated LLCs, that entity could operate nationwide – and possibly worldwide. This is because courts look to the law of the state of incorporation for rules governing the internal affairs of a corporate entity.

We believe the best path forward, therefore, is aligning AI with existing laws, instead of creating a separate set of rules for AI. Additional law can be layered on top for artificial agents^[25], but AI should be subject to at least all the laws a human is subject to.

Building the law into AI

We suggest a research direction of integrating law into AI agents^[26] to help ensure adherence to legal standards^[27]. Researchers could train AI systems to learn methods for internalizing the spirit of the law^[28]. The training would use data generated by legal processes and tools of law, including methods of lawmaking, statutory interpretation, contract drafting, applications of legal standards and legal reasoning.

In addition to embedding law into AI agents, researchers can develop AI compliance agents – AIs designed to help an organization automatically follow the law. These specialized AI systems would provide third-party legal guardrails.

Researchers can develop better AI legal compliance by fine-tuning large language models with supervised learning^[29] on labeled legal task completions. Another approach is reinforcement learning^[30], which uses feedback to tell an AI if it’s doing a good or bad job – in this case, attorneys interacting with language models. And legal experts could design prompting schemes – ways of interacting with a language model – to elicit better responses from language models that are more consistent with legal standards.

Law-abiding (artificial) business owners

If an LLC were operated by an AI, it would have to obey the law like any other LLC, and courts could order it to pay damages, or stop doing something by issuing an injunction. An AI tasked with operating the LLC and, among other things, maintaining proper business insurance would have an incentive to understand applicable laws and comply. Having minimum business liability insurance policies is a standard requirement that most businesses impose on one another to engage in commercial relationships.

The incentives to establish AI-operated LLCs are there. Fortunately, we believe it is possible and desirable to do the work to embed the law – what has until now been human law – into AI, and AI-powered automated compliance guardrails.

Prominent cases of purported lying continue to dominate the news cycle. Hunter Biden was charged with lying on a government form^[1] while purchasing a handgun. Republican Representative George Santos allegedly lied in many ways^[2], including to donors through a third party in order to misuse the funds raised. The rapper Offset admitted to lying on Instagram^[3] about his wife, Cardi B, being unfaithful.

There are a number of variables that distinguish these cases. One is the audience: the faceless government, particular donors and millions of online followers, respectively. Another is the medium used to convey the alleged lie: on a bureaucratic form, through intermediaries and via social media.

Differences like these lead researchers like me to wonder what factors influence the telling of lies. Does a personal connection increase or decrease the likelihood of sticking to the truth? Are lies more prevalent on text or email than on the phone or in person?

An emerging body of empirical research is trying to answer these questions, and some of the findings are surprising. They hold lessons, too - for how to think about the areas of your life where you might be more prone to tell lies, and also about where to be most cautious in trusting what others are saying. As the recent director of The Honesty Project^[4] and author of “Honesty: The Philosophy and Psychology of a Neglected Virtue^[5],” I am especially interested in whether most people tend to be honest or not.

Figuring out the frequency of lies

Most research on lying asks participants to self-report their lying behavior, say during the past day or week. (Whether you can trust liars to tell the truth about lying is another question.)

The classic study on lying frequency was conducted by psychologist Bella DePaulo^[6] in the mid-1990s. It focused on face-to-face interactions and used a group of student participants and another group of volunteers from the community around the University of Virginia. The community members averaged one lie per day^[7], while the students averaged two lies per day. This result became the benchmark finding in the field of honesty research and helped lead to an assumption among many researchers that lying is commonplace^[8].

But averages do not describe individuals. It could be that each person in the group tells one or two lies per day. But it’s also possible that there are some people who lie voraciously and others who lie very rarely.

In an influential 2010 study, this second scenario is indeed what Michigan State University communication researcher Kim Serota^[9] and his colleagues found. Out of 1,000 American participants, 59.9% claimed not to have told a single lie^[10] in the past 24 hours. Of those who admitted they did lie, most said they’d told very few lies. Participants reported 1,646 lies in total, but half of them came from just 5.3% of the participants.

This general pattern in the data has been replicated^[11] several times. Lying tends to be rare, except in the case of a small group of frequent liars.

Does the medium make a difference?

Might lying become more frequent under various conditions? What if you don’t just consider face-to-face interactions, but introduce some distance by communicating via text, email or the phone?

Research suggests the medium doesn’t matter much. For instance, a 2014 study by Northwestern University communication researcher Madeline Smith^[12] and her colleagues found that when participants were asked to look at their 30 most recent text messages, 23% said there were no deceptive texts^[13]. For the rest of the group, the vast majority said that 10% or fewer of their texts contained lies.

Recent research by David Markowitz at the University of Oregon successfully replicated earlier findings that had compared the rates of lying using different technologies^[14]. Are lies more common on text, the phone or on email? Based on survey data from 205 participants, Markowitz found that on average, people told 1.08 lies per day^[15], but once again with the distribution of lies skewed by some frequent liars.

Not only were the percentages fairly low, but the differences between the frequency with which lies were told via different media were not large. Still, it might be surprising to find that, say, lying on video chat was more common than lying face-to-face, with lying on email being least likely.

A couple of factors could be playing a role^[16]. Recordability seems to rein in the lies – perhaps knowing that the communication leaves a record raises worries about detection and makes lying less appealing. Synchronicity seems to matter too. Many lies occur in the heat of the moment, so it makes sense that when there’s a delay in communication, as with email, lying would decrease.

Does the audience change things?

In addition to the medium, does the intended receiver of a potential lie make any difference?

Initially you might think that people are more inclined to lie to strangers than to friends and family, given the impersonality of the interaction in the one case and the bonds of care and concern in the other. But matters are a bit more complicated.

In her classic work, DePaulo found that people tend to tell what she called “everyday lies” more often to strangers than family members^[17]. To use her examples, these are smaller lies like “told her (that) her muffins were the best ever” and “exaggerated how sorry I was to be late.” For instance, DePaulo and her colleague Deborah Kashy reported that participants in one of their studies lied less than once per 10 social interactions^[18] with spouses and children.

However, when it came to serious lies about things like affairs or injuries, for instance, the pattern flipped. Now, 53% of serious lies were to close partners^[19] in the study’s community participants, and the proportion jumped up to 72.7% among student volunteers. Perhaps not surprisingly, in these situations people might value not damaging their relationships more than they value the truth. Other data also finds participants tell more lies to friends and family members^[20] than to strangers.

Investigating the truth about lies

It is worth emphasizing that these are all initial findings. Further replication is needed, and cross-cultural studies using non-Western participants are scarce. Additionally, there are many other variables that could be examined, such as age, gender, religion and political affiliation.

When it comes to honesty, though, I find the results, in general, promising. Lying seems to happen rarely for many people, even toward strangers and even via social media and texting. Where people need to be especially discerning, though, is in identifying – and avoiding – the small number of rampant liars out there. If you’re one of them yourself, maybe you never realized that you’re actually in a small minority.

What does it mean to be a good thinker? Recent research suggests that acknowledging you can be wrong plays a vital role.

I had these studies in mind a few months ago when I was chatting with a history professor about a class she was teaching to first-year students here at Wake Forest University. As part of my job as a psychology professor who researches character^[1] – basically, what it means to be a good person – I often talk to my colleagues about how our teaching can develop the character of our students.

In this case, my colleague saw her class as an opportunity to cultivate character traits that would allow students to respectfully engage with and learn from others when discussing contentious topics. Wanting to learn about and understand the world is a distinctive human motivation^[2]. As teachers, we want our students to leave college with the ability and motivation to understand and learn more about themselves, others and their world. She wondered: Was there one characteristic or trait that was most important to cultivate in her students?

I suggested she should focus on intellectual humility^[3]. Being intellectually humble means being open to the possibility you could be wrong about your beliefs.

But is being humble about what you know or don’t know enough?

I now think my recommendation was incorrect. It turns out good thinking requires more than intellectual humility – and, yes, I see the irony that admitting this means I had to draw on my own intellectual humility.

Acknowledging you might not be right

One reason for my focus on intellectual humility was that without acknowledging the possibility that your current beliefs may be mistaken, you literally can’t learn anything new. While being open to being wrong is generally quite challenging – especially for first-year university students confronting the limits of their understanding – it is arguably the key first step in learning.

But another reason for my response is that research on intellectual humility has exploded^[5] in the past 10 years. Psychologists now have many different ways^[6] to assess intellectual humility. Social scientists know that possessing a high level of intellectual humility is associated with multiple positive outcomes, like having more empathy^[7], more prosocial behavior^[8], reduced susceptibility to misinformation^[9] and an increased inclination to seek compromise^[10] in challenging interpersonal disagreements.

If you want to focus on one trait to promote good thinking, it seems that intellectual humility is hard to beat. Indeed, researchers, including those in my own lab^[11], are now testing interventions to promote it among different populations.

A single trait won’t make you a good thinker

However, was I right in recommending just a single trait? Is intellectual humility by itself enough to promote good thinking? When you zoom out to consider what is really involved in being a good thinker, it becomes clear that simply acknowledging that one could be wrong is not enough.

To provide an example, perhaps someone is willing to acknowledge that they could be wrong because “whatever, man.” They didn’t have particularly strong convictions to begin with. In other words, it’s not enough to say you’re mistaken about your beliefs. You also need to care about having the right beliefs.

While part of being a good thinker involves recognizing one’s possible ignorance, it also requires an eagerness to learn, curiosity about the world, and a commitment to getting it right.

What other traits, then, should people strive to cultivate? The philosopher Nate King writes that being a good thinker involves possessing multiple traits^[12], including intellectual humility, but also intellectual firmness, love of knowledge, curiosity, carefulness and open-mindedness.

Being a good thinker involves confronting multiple challenges beyond being humble about what you know. You also need to:

• Be sufficiently motivated to figure out what’s true.
• Focus on the pertinent information and carefully seek it out.
• Be open-minded when considering information that you may disagree with.
• Confront information or questions that are novel or different from what you’re generally used to engaging with.
• Be willing to put in the effort to figure it all out.

This is a lot, but philosopher Jason Baehr writes that possessing good intellectual character requires successfully addressing all these challenges^[13].

Additional ingredients for good thinking

So, I was wrong to say that intellectual humility was the silver bullet that can teach students how to think well. Indeed, being intellectually humble – in a way that promotes good thinking – likely involves being both curious and open-minded about new information.

Focusing on a single characteristic such as intellectual humility rather than the totality of intellectual character ends up promoting lopsided character development, similar to that of a bodybuilder focusing their efforts on one bicep rather than their whole body^[15].

My lab’s current work is now attempting to address this issue by defining the good thinker in terms of multiple intellectual traits. This approach is similar to work in personality science that has identified key traits of people who are psychologically healthy as well as those whose patterns of thinking, feeling and behaving cause enduring distress or problems. We hope to further understand how good thinkers function in daily life^[16] – for example, their personality, the quality of their relationships and their well-being – as well as how their intellectual character influences their thinking, behavior and sense of identity^[17].

I think this work^[18] is vital in order to understand the key characteristics of good thinking and to learn more about how to build these habits in ourselves and others.

If you live on the East Coast, you may have driven through roundabouts in your neighborhood countless times. Or maybe, if you’re in some parts farther west, you’ve never encountered one of these intersections. But roundabouts, while a relatively new traffic control measure, are catching on across the United States^[1].

Roundabouts, also known as traffic circles or rotaries, are circular intersections^[2] designed to improve traffic flow and safety. They offer several advantages over conventional intersections controlled by traffic signals or stop signs, but by far the most important one is safety.

I research transportation engineering^[4], particularly traffic safety and traffic operations. Some of my past studies^[5] have examined the safety and operational effects of installing roundabouts at an intersection. I’ve also compared the performance of roundabouts versus stop-controlled intersections.

A brief history of roundabouts

As early as the 1700s, some city planners proposed and even constructed circular places, sites where roads converged, like the Circus^[6] in Bath, England, and the Place Charles de Gaulle^[7] in France. In the U.S., architect Pierre L'Enfant built several into his design for Washington, D.C.^[8]. These circles were the predecessors to roundabouts.

In 1903, French architect and influential urban planner Eugène Hénard was one of the first people who introduced the idea^[9] of moving traffic in a circle^[10] to control busy intersections in Paris^[11].

Around the same time, William Phelps Eno^[12], an American businessman known as the father of traffic safety and control, also proposed roundabouts to alleviate traffic congestion in New York City^[13].

In the years that followed, a few other cities tried out a roundabout-like design, with varying levels of success^[14]. These roundabouts didn’t have any sort of standardized design guidelines, and most of them were too large to be effective and efficient, as vehicles would enter at higher speeds without always yielding.

The birth of the modern roundabout^[15] came with yield-at-entry regulations, adopted in some towns in Great Britain in the 1950s. With yield-at-entry regulations, the vehicles entering the roundabout had to give way to vehicles already circulating in the roundabout. This was made a rule nationwide in the United Kingdom in 1966, then in France in 1983.

Yield-at-entry meant vehicles drove through these modern roundabouts more slowly, and over the years, engineers began adding more features that made them look closer to how roundabouts do now. Many added pedestrian crossings and splitter islands – or raised curbs where vehicles entered and exited – which controlled the vehicles’ speeds^[16].

Engineers, planners and decision-makers worldwide noticed that these roundabouts improved traffic flow, reduced congestion and improved safety at intersections. Roundabouts then spread throughout Europe and Australia^[17].

Three decades later, modern roundabouts came to North America. The first modern roundabout^[18] in the U.S. was built in Summerlin, on the west side of Las Vegas^[19], in 1990.

Ever since, the construction of modern roundabouts in the U.S. has picked up steam. There are now about 10,000 roundabouts in the country^[20].

Why use roundabouts?

Roundabouts likely caught on so quickly because they reduce the number of potential conflict points^[21]. A conflict point at an intersection is a location where the paths of two or more vehicles or road users cross or have the potential to cross. The more conflict points, the more likely vehicles are to crash.

A roundabout has only eight potential conflict points, compared to 32 at a conventional four-way intersection^[22]. At roundabouts, vehicles don’t cross each other at a right angle, and there are fewer points where vehicles merge or diverge into or away from each other.

The roundabout’s tight circle forces approaching traffic to slow down and yield to circulating traffic, and then move smoothly around the central island. As a result, roundabouts have fewer stop-and-go issues^[23], which reduces fuel consumption and vehicle emissions and allows drivers to perform U-turns more easily. Since traffic flows continuously at lower speeds in a roundabout, this continuous flow minimizes the need for vehicles to stop, which reduces congestion.

The Federal Highway Administration estimates that when a roundabout replaces a stop sign-controlled intersection, it reduces serious and fatal injury crashes by 90%^[24], and when it replaces an intersection with a traffic light, it reduces serious and fatal injury crashes by nearly 80%^[25].

Why do some places have more than others?

Engineers and planners traditionally have installed roundabouts in intersections with severe congestion or a history of accidents^[26]. But, with public support and funding, they can get installed anywhere.

But roundabouts aren’t needed in every intersection. In places where congestion isn’t an issue, city planners tend not to push for them^[27]. For example, while there are [around 750 roundabouts] in Florida, there are fewer than 50 in North Dakota^[28], South Dakota^[29] and Wyoming^[30] combined.

Roundabouts have been gaining popularity^[31] in the U.S. in recent years, in part because the Federal Highway Administration recommends them^[32] as the safest option. Some states, like New York and Virginia, have adopted a “roundabout first” policy, where engineers default to using roundabouts where feasible when building or upgrading intersections.

In 2000, the U.S. only had 356 roundabouts^[33]. Over the past two decades, that number has grown to over 10,000^[34]. Love them or hate them, the roundabout’s widespread adoption suggests that these circular intersections are here to stay.