Liars, Cheats and Copycats: Trickery and Deception in Nature" (Columbia University Press, 2026), biologist James O'Hanlon turns to tactical deception aimed at manipulating what another animal believes — and whether we can consider this as lying.

Live Science spoke with O'Hanlon about his book, and why so many scientists are reluctant to say "yes, animals can lie."

Read an excerpt: Can animals lie? This sneaky bird might be proof.

Olivia Maule: The chapter opens with a moment from a talk you gave, where a woman at a senior citizens' club asked you a question about orchid mantises that left you stumped: "How does the mantis know to look like a flower?" Why did that moment stick with you enough to open the chapter with it?

James O'Hanlon: Because it was such a simple, straightforward question that I couldn't give a simple, straightforward answer to. At the time, I was thinking about what's going on in the brains of the animals I was looking at — does a camouflaged animal actually know it's camouflaged? Does an insect that looks like a leaf know what a leaf even is?

And it got me thinking: they don't need to. This stuff just sort of works because it works. That's a completely different type of deception to the other things dealt with in this chapter, which is: Do animals actually know that they can lie? Can they intentionally deceive, like we can?

OM: So would you say you have an answer to that question now? And if so, what would it be?

JO: If I had to answer, it would be yes. It looks like it. But scientists are paid to be pedantic, so it's always going to be a "yes, but" or a "possibly." There's a ton of behaviors that look like animals can lie, and they're really good at it, but with any type of science, we're never going to know for certain what's going on in their brains. It's a best-guess situation.

OM: How would you help readers hold those two ideas at once — that this is genuine deception in an evolutionary sense, but not necessarily lying in the way we mean it as humans?

JO: When we talk about lying in humans, there's a value judgment attached. We're judging each other on whether we're good or bad people, doing right or wrong things. We kind of have to relax that judgment a bit when we're talking about other animals.

I guess it becomes an ethical question — we look at deception as being right or wrong, morally good or bad, and that's a very human-centric way of thinking. Ethics and morals are things we've developed to help us get along in our own societies. Who knows what's going on in animal societies?

There's an example in the book of golden snub-nosed monkeys that use deceptive alarm calls to scare off other members of their group and steal their food. After a while, those monkeys start to get ignored, and the group stops responding to their calls. So maybe there is some sort of animal-society rules and regulations keeping lying in check. Maybe. We'll see.

OM: I do want to ask about the chimpanzee study, in which chimpanzees intentionally misled competitive handlers to boxes without food, and compare it to the 2017 dog study, where dogs learned to mislead handlers much faster than the chimps did. What did that result do to the assumption that big brains equal better lying?

JO: There's always been this idea that lying is a really cognitively complex task — you need the brains not just to realize what's going on in the real world but to imagine a false possibility, and then to describe that false possibility as if it were real. We talked that up as something you need big brains to do, and there was also a bit of patting ourselves on the back for being such smart animals — maybe we lie a lot because we're such smart animals. But the more we learn about animals and what they're capable of, the more we realize they can do so much more than we thought was possible with the brains they've got.

OM: Does that suggest lying is less about raw intelligence and more a byproduct of needing to survive in a group?

JO: As far as all the examples of tactical deception in the book that look like they're intentional, they all, or mostly all, come from social animals. We don't seem to see it in solitary animals. That's a big sign that maybe it's something that's evolved because individuals can exploit it in a social setting. But it's still such early days, so it's hard to say for definite how different levels of sociality, and how bonded individuals are within groups, correlate with more deception.

OM: Could you elaborate on the distinction between deception and something like the camouflage you introduce in the book with the tiger's stripes?

JO: Compared to the intentional deception we've been talking about, things like camouflage still work regardless of whether the animal doing it is aware of it or not. The idea behind lying and tactical deception is that it only works because it's intentional — there's some sort of choice to do it.

Whether the animals are aware of that choice is another question. Think about the way we do it as humans — are we always aware of it? Whenever your friend asks whether you like their new haircut and you just go, "Yeah, it's great," you don't really think about the fact that you're probably lying. It's just part of our social norms. So it becomes a very blurry gray area very quickly.

OM: It sort of boils down to the choice of it all — whether they can choose to do it or not, which raises the question of whether it's conscious or unconscious.

JO: It's tricky, because as soon as you start talking about it being a conscious decision these animals make, you start painting pictures of squirrels twirling their mustaches, giggling at how evil they are for pretending to hide nuts. And you start to think, maybe this isn't the right exact way to think about lying and deception.

OM: The drongo — a bird renowned for its ability to deceive meerkats — doesn't just have one trick, it cycles through different alarm calls and borrows calls from other bird species. Does that put it in a different category of liar than squirrels or monkeys, or is it the same trick with a different toolbox?

JO: It could just be the same trick with a different toolbox. It's essentially doing the same thing as the golden snub-nosed monkeys we were talking about before. But birds are incredible singers and have very flexible call structures, and there are tons of birds that can mimic other birds. Maybe you just pair that ability with this deception adaptation, and it looks a bit different, but it's the same kind of trick.

OM: Do you think these behaviors are inherited, or just innate characteristics of the drongos themselves?

JO: I don't know — I'd be interested to find out. The evolutionary aspect would be that the ones who can do it get more food and are better able to survive and reproduce. Whether they learn it from their parents, it's entirely possible. We know from birds in general that they learn calls from their parents and their social groups, and there are even studies showing birds will start learning calls while they're still in the egg, listening to their parents' calls. So it's entirely possible they learn this trick socially, as far as I know.

OM: In writing this book, what did you find is the best way to approach understanding animal behavior as it relates to human traits like lying or deception?

JO: I think there's still a little bit of baggage from old-school thinking, that you need bigger brains to be deceptive and tricky in this way, and there are still people who think it must be things like the higher apes and great apes that are capable of this stuff.

As soon as you start studying that in something like an invertebrate, it's really hard to get the idea out there — other scientists will come back and say, "No, that couldn't be possible, this must be some other type of behavior, or it just looks like tactical deception, but it's not." This happened with the researchers who did the work on cuttlefish that change one side of their body to look like a male and the other to look like a female — there was a lot of resistance to that idea, seemingly just because it was a cuttlefish, this little invertebrate, so it couldn't possibly be capable of such cleverness. But as far as the actual evidence goes, and what we can see, it's really no different from what we see in these big-brained mammals, so why not assume the same thing is going on?

A lot of it comes down to the culture and practice of science, and the people doing the science. We're supposed to be as objective as possible, but we're still humans, we're still animals. It takes a while for ideas to change.

OM: Is there a risk that this caution has become its own kind of bias, where we assume human specialness by default until proven otherwise?

JO: Yeah, definitely. It's important, as part of scientific practice, to be as objective as possible, and as a general rule, to not anthropomorphize. But at the same time, we're just animals too — we're just another one of the great apes. We share characteristics with lots of different animals, so it's not a huge stretch to think that what's going on in our brains is also going to be similar to what's going on in other animal brains.

It's just a question of when we apply that kind of thinking, and when it's useful or not. Something similar happened in the field of understanding pain in animals — scientists studying this were always trying not to anthropomorphize, not to assume animals experienced pain the way we did. Then, the more we understood it, it became quite clear that they probably did, and it almost became an ethical question to stop with the anti-anthropomorphizing and instead go, no, we know what pain feels like, we can say that.

We're never going to be able to see what's going on in their brains, but that doesn't excuse us from recognizing what's going on. So I think it became okay not to anthropomorphize but to recognize the similarities between humans and other animals, as opposed to always hinging on the differences between us.

OM: At the end of the chapter, you say that if you buy a scientist a few drinks, they'll eventually admit that animals can lie. I obviously can't buy you a drink over email, so I'll just ask you directly — do you think animals can lie?

JO: Yeah. I'll give a straightforward yes, because I can.

You need to get scientists out of their professional mindset, where they're trained to give the most correct answer that they can. And yes is a bit of a broad-stroke answer for a scientist when they're in professional mode, which is why you need to get them out of the lab and out to a bar or a cafe, and get them talking in human terms again.

OM: What would you say is your favorite example in the book — what are you most excited for readers to walk away with?

JO: I'll go with the cuttlefish example — the one where a male cuttlefish will put male color patterns on one side of its body and female patterns on the other, to trick other male cuttlefish. It might be my favorite because, as a young student, I worked on this particular species of cuttlefish. We were studying them, watching all of their crazy color-changing abilities, and just wondering what on earth they must be talking about, what was going on there. Then, years later, seeing the aforementioned research come out was this sort of lightbulb moment — that's what I was watching them do all along. I think that has a personal connection for me. I spent so much time looking at these creatures, being mesmerized by what they were doing, with no idea what was going on. So it was great to see scientists come in and figure it out, and answer those questions.

This interview has been condensed and edited lightly for clarity.

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'> 'You start painting pictures of squirrels twirling their mustaches': A biologist on whether animals can lie John Maisey, the curator-in-charge emeritus of fossil fish at the American Museum of Natural History in New York, told Live Science. "The takeaway is that the shark lineage within the fishes generally does go back further than trees. But it really depends on how you define what we mean by shark."

The modern sharks we see today first emerged around 195 million years ago, during the Jurassic period. Fossils of ancient sharks from this time can be traced to living lineages, namely Hexanchiformes, an order of sharks identified by their six or seven gills and single dorsal fin.

This means that modern sharks, at least, are not older than trees. Experts generally agree that trees first evolved in the Middle Devonian epoch, around 380 million to 390 million years ago. "I think it's not very controversial, when we had the first trees," Cindy Looy, a paleobotanist at the University of California, Berkeley, told Live Science.

For instance, the first true tree in the evolutionary record is considered to be Archaeopteris, an extinct genus discovered in a 385 million-year-old fossil forest near Cairo, New York. Looking at these fossils, Archaeopteris has many characteristics of trees we have today, including a tall, woody trunk; leaves; and a deep root system. Other early trees ‪—‬ such as Eospermatopteris found in ancient forests near Gilboa, New York, and Calamophyton in southwest England ‪—‬ also appeared in the fossil record 390 million and 393 million years ago, respectively.

But when we look at the extinct relatives of modern sharks, "that's where it gets a bit wobbly," Maisey said. There are fossils from the sister groups of modern sharks that can be traced back through the Permian period and into the Devonian period (around 359 million to 420 million years ago). The most abundant group are hybodonts, an extinct group of spiny fish that have a unique calcification pattern in their cartilage that is similar to that of modern sharks.

"It’s called tessellated calcified cartilage, and that's a very important hallmark of most of the shark-like fishes and their ancestors," said Maisey, who has studied a spiny fish fossil called Doliodus problematicus from the early Devonian. If this definition is used, these sharks first appeared around 400 million years ago, before trees emerged.

Sharks' rough skin can be traced even further back, with the dermal denticles — the tooth-like scales that roughen a shark's skin — first appearing in the fossil record around 450 million years ago.

These transition fossils, where fish were evolving into sharks and gaining shark-like traits, introduce a gray area in the definition of sharks. "When you get back into the ancient past, when you're not dealing with things that we have living examples to compare with anymore, then it becomes a bit more tricky [to figure out what they are]," Maisey said.

Fossils also present a very limited picture. Many contain only fragments of an animal, like a fallen tooth, so scientists are still piecing together the clues of exactly how and when sharks arose. That means every fish fossil discovery often leads to more questions about what other transition fossils could be out there, Maisey said.

There is also much to be discovered about trees, Looy added. Terrestrial fossils, especially ones that clearly show parts of a tree, are quite rare. Finding a fossil forest requires a lot of luck, she said, although there is little indication that trees were present before the Middle Devonian.

"That's why I think the fossil record is so intriguing," Maisey said. "Because it may not give us all the answers, but it certainly raises questions."

How much of a shark fan are you? Find out with our shark quiz!

'> Are sharks really older than trees?

The study's results could have practical benefits, said Daniel Morris, a cognitive neuroscientist at Northwestern University who studies dreams and was not involved with the work. "Lucid dreaming can benefit people with nightmares by allowing them to transform their nightmares into positive dreams and feel greater agency in their dreams," Morris told Live Science in an email.

Before this study, published Sept. 28 in the journal Frontiers in Psychology, neuroscientists tried to induce lucid dreaming with various methods. These included meditation exercises and so-called reality checks, in which participants ask themselves while awake whether unusual phenomena they encounter — such as people wearing odd Halloween costumes — are real or if they're dreaming. The idea is that they will ask themselves the same question in their sleep during bizarre dreams.

However, "for most people, our day-to-day lives may not feel 'dream-like,'" Morris said, explaining why reality checks have had mixed results and don't reliably trigger lucid dreaming.

Since dream-like scenarios are rare in waking life, the neuroscientists behind the new study used VR simulations of bizarre situations to complement reality-check exercises.

The team, based at the University of Trento in Italy, recruited university students and asked them to meditate and then perform the VR training. The meditation was intended to increase students' awareness of what they were thinking about in a given moment. Each time they encountered bizarre happenings in the VR environment, such as objects or people violating laws of physics or rapid switches from one scene to another, they performed reality checks.

After the training, participants went home and were asked to keep a dream diary that they wrote in every morning. They also filled out daily questionnaires, citing the number of dreams they recalled and how many they remembered being lucid.

The participants experienced lucid dreams four times more often than participants did in a second group that did reality checks without performing any meditation or VR training. The study also included another comparison group, in which participants carried out reality checks during realistic rather than dream-like VR simulations; these participants were over eight times less likely to report lucid dreams. This latter comparison ensured that the results were not caused solely by the use of VR, the researchers said.

It was particularly surprising to find that such little training with the dream-like VR simulations was needed to develop lucid dreaming as a skill, said study co-author Nicola De Pisapia, a neuroscientist at the University of Trento. His team ran the experiment for only a month because any longer would have been too demanding for the participants, De Pisapia noted.

Study co-author Andrea Signorelli, a doctoral student in De Pisapia's lab, thinks the VR intervention is at the heart of why the approach worked. People often don't realize that they're dreaming because the dreams "fool" your senses and feel realistic in the moment, he explained.

"Virtual reality is the technology to fool you on stereoscopic vision and auditory information," he said. The term "stereoscopic" refers to techniques that create 3D illusions from 2D images by mimicking how human eyes see.

"It's basically the most immersive technology that we have at the moment," making it a good intervention for reality check exercises, Signorelli said.

The team also compared the number of lucid dreams participants reported against their total number of recalled dreams, which revealed an interesting pattern. On average, participants in each group recalled more dreams after starting the experiment than they did beforehand. However, the dream-simulating VR group recalled the fewest dreams overall after entering the experiment, even though they had the highest number of lucid dreams.

Signorelli speculated that perhaps it takes a lot of energy to have lucid dreams, which could divert resources away from recalling other dreams. Morris argued that, alternatively, participants in the lucid-dream VR group "may have been less motivated to report non-lucid dreams than the control groups." So there may have been some bias in the reporting.

The study had some limitations, such as its small sample size of 38 participants. Plus, neither of the two control groups were asked to meditate, so it is impossible to say whether the meditations or the dreamlike VR sessions had more influence over lucid dreaming in the test group.

The team is now doing a follow-up study in which the meditation part has been removed, Signorelli said, to reveal whether the VR dream scenarios are the critical factor, as suspected.

Signorelli said that he would like to see lucid-dream training tailored for each individual. For example, the VR simulations could be personalized to simulate a recurrent nightmare that a given person experiences, training them to recognize triggers specific to that dream, he said.

"Other future research could explore the potential therapeutic benefits of this intervention for people with nightmares, anxiety, or PTSD [post-traumatic stress disorder]," Morris suggested.

This article is for informational purposes only and is not meant to offer medical advice.

How much do you know about sleep and dreams? Find out with our sleep quiz!

'> Neuroscientists reveal method to train people to have lucid dreams — and it involves virtual reality and meditation

The findings, published Sept. 21 in The Astrophysical Journal Letters, could change our understanding of what kinds of exoplanets orbit certain stars.

In about 5 billion years, the sun will balloon outward as a red giant after exhausting all of the hydrogen in its core. During this red giant phase, our star will swell to 100 times its present-day size, gobbling up Mercury, Venus and possibly even Earth in the process, Nathan Kaib, a planetary scientist at the University of Oklahoma who wasn't involved in the new research, told Live Science in an email. Following this violent swelling, the sun will crumple into a collapsed core called a white dwarf.

Until now, scientists thought the four outer planets would escape this phase relatively unscathed. A 1998 simulation-based study suggested that the gas the sun spews from its outer layers will push this planetary quartet outward, doubling the radius of each planet's orbit. Only the gravitational impact of a runaway star could destabilize this new order, and such events are thought to occur only once every billion billion years.

Solar recoil

These predictions hinged on the assumption that the sun will eject its outer layers smoothly. However, recent observations of stars suggest a jerkier loss of mass, with gas clouds lofted by plumes of plasma in the sun — as though our star were spitting out mass blobs. "They're kind of like coronal mass ejections, except much larger," Jim Fuller, a professor of theoretical astrophysics at Caltech and co-author of the new study, told Live Science in an email.

Each "blob" pushes the star backward, similar to how a fired bullet causes a gun to recoil. Although every push is small, moving the sun just a few feet per second, many pushes can, over time, impart the equivalent of an enormous kick that alters the sun's speed by several hundred feet per second. In fact, astronomers have already seen white dwarfs suffer such kicks in other star systems.

When Fuller, who studied these kicks, described them to Konstantin Batygin, a professor of planetary science at Caltech and the study's first author, Batygin "realized this would have important consequences for the evolution of our own solar system," Fuller said. That's because the kicks change the sun's gravitational pulls on everything around it.

Chaos at the edge of town

To determine how the sun's mass loss would influence the giant planets, Batygin created computer-based simulations of the sun and the outer planets. The researchers considered three scenarios: if the sun lost its mass smoothly, if it spit out distinct mass blobs during its entire time evolving as a red giant, and if the sun spewed the blobs only during its last stages. The researchers also varied each ejected blob's mass.

The first scenario produced results similar to those of previous studies, with the outer solar system retaining almost all of its features for billions of years. In contrast, the other two cases had drastically different results. Using 672 simulations, the researchers found that if the sun lost mass in blobs, the giant planets would be thrown into chaos, switching places, developing weirdly oval-shaped orbits, and even getting ejected out of the solar system entirely. Most dramatically, in 96% of the simulations with the heaviest ejected mass packets, the planets get destroyed as they crashed into each other.

These developments also happened much more rapidly — less than a few hundred million years after the sun transformed into a white dwarf, or even during the red giant phase, in the most extreme scenarios.

The study's findings hint that analogues of the present-day outer solar system around white dwarf stars are less likely to exist than previously thought. Kaib noted that the study's results suggest that planets with oval-shaped orbits should dominate instead. It's thought that habitable planets could exist around white dwarfs, but this study's findings show that our understanding of those distant star systems may be incomplete, and that such worlds may, in reality, be unstable.

See how well you know our planetary neighborhood with our solar system quiz!

'> Jupiter, Saturn, Uranus and Neptune could destroy each other sooner than we thought, simulations hint

In the wake of this study, Live Science recently polled its readers on whether they felt AI was making them less motivated after using it.

More than 140 readers voted in the poll, with 30% of voters picking "No, I don't use AI at all, so this situation doesn't apply to me."

"If AI were only a tool, controlled by those who use it I might give it a try," said one commenter in response. "But it isn't under control at all. It gets into your bank accounts and moves money without authorization. It encourages suicide and self-harm. It is addictive and makes people lazy. I know someone who uses it to answer questions and while it is detailed, it makes her lazier, asking one question and getting the answer without her searching for it. AI Is a danger. It should not be allowed."

Other comments reflected this sentiment, with one reader writing, "Use of all automatic aids decrease[s] attention and retention. I see it in the use of navigation devices where drivers ought to recognize routes after a couple of times. AI helps research and cuts down lengthy searches, but over use of summaries weakens critical faculties."

Other commenters questioned whether AI is the problem, or if people are just inclined to take the easy option, asking "Would you get the same results if the answers to all but a few problems were provided on separate sheet of paper?" and another writing, "I think researchers should also investigate whether shovels decrease motivation to dig holes with one's hands. AI, like a shovel, is only a tool."

Do you agree with these readers? Let us know in the comments!

'> 'It isn't under control at all': Live Science readers respond to whether AI is making them lazy