< Back to Issue 7 Neuralink: Mind Over Matter? by Kara Miwa-Dale 22 October 2024 edited by Weilena Liu illustrated by Aisyah Mohammad Sulhanuddin What if I told you that you could control a computer mouse with just your thoughts? It sounds like something straight out of a sci-fi movie, doesn’t it? But this isn’t fiction… Welcome to the brain-computer interface, a device which is able to record and interpret neural activity in the brain, enabling direct communication between your mind and a computer. Tech billionaire Elon Musk founded ‘Neuralink’, a company developing coin-sized brain-chips that can be surgically inserted into the brain using a robot. Neuralink made headlines a few months ago by successfully implanting their brain-chip, dubbed ‘Telepathy’, into their first trial patient, Noland Arbaugh. While there were a few technical glitches, it seems to be working relatively well so far. Noland has been able to regain some of the autonomy that he lost following a devastating spinal cord injury. He is even able to play video games with a superhuman-like reaction speed, thanks to the more direct communication route between the Neuralink implant and his computer. But it doesn’t stop there; Elon Musk’s ultimate vision is to have millions of people using Neuralink in the next 10 years, not only to restore autonomy to those with serious injuries, but to push the boundaries of what the human brain is capable of. He thinks that Neuralink will allow us to compete with AI and vastly improve our speed and efficiency of communication, which is ‘pitifully slow’ in comparison to AI. Neuralink implants may seem like an incredible leap in scientific technology, but what will happen if they become normalised in our society? Let’s imagine for a moment … Jade, April 7th 2044 Shoving my jacket into my bag, I dart out of the hospital and pull onto the main road in my Tesla. As I speed past the intersection, I see a giant advertisement plastered on a sleek building: ‘Neuralink: Seamless Thoughts, Limitless Possibilities’. When I signed up to get a Neuralink implant, all I’d thought about were the infinite possibilities of how it would change my life – not what could go wrong. I wish I could say that I was brainwashed into getting a Neuralink, or that I had no choice in the matter. But the truth? I got an implant so that I could be ‘ahead of the crowd’ and because I was so frustrated at feeling inadequate compared to the other doctors at my hospital. When I graduated medical school, at the top of my class, people told me that I would do ‘great things’ and ‘change the world’. I followed the standard path, landing my first job and climbing the ranks one caffeine-fuelled shift at a time. I loved my job. Every time I saved a life, it felt like all my effort had paid off. Then Neuralink happened. I still remember the day Dr Maxwell - a doctor I worked with - proudly announced that he’d ‘bitten the bullet’ and gotten the implant. Over the coming weeks, we watched in awe: his diagnoses were quicker and more accurate than any human could imagine, and he went home as energetic as he’d arrived. Now, the extra hours I spent figuring out tricky cases were no longer a representation of my work ethic, but a symptom of my inadequacy compared to the Neuralink-enhanced doctors. One by one, my colleagues signed up for the implant. I hated the thought of having something foreign nestled in my brain, recording my brain’s neurons every second of the day. I told myself I wouldn’t let peer pressure get to me. But, as I watched those around me get promoted while I continued to work endless days, the frustration started to build. One afternoon, the department head came into my office to tell me that they were reconsidering the renewal of my contract. I wasn’t ‘keeping up’ with my Neuralink-enhanced colleagues. “We respect your personal decision, of course,” she said with hollow politeness. I wasn’t keen on being pressured into it, but at the same time, I genuinely believed that the implant would improve my life. When I told my friends and family about getting an implant, they were concerned. They tried to list all the things that could go wrong, but I came up with enough reasons to convince myself that it was the right decision. Once they saw how incredible the Neuralink device was, I thought, they would want one too. *** I’m jolted back to reality as the car veers slightly left, and I manually yank the wheel to correct it. Perhaps my implant glitched for a second… *** Everything changed after I had my Neuralink implanted. I was the only person in my family who had one, although a couple of friends did. At first, I felt invincible. The phenomenal speed with which I was able to come up with previously challenging diagnoses was thrilling. I was able to process enormous amounts of data and draw connections that I had never been able to before. It was addictive to feel that I was working at my full potential, using my newfound ‘superpower’ to save more lives than ever. About a month in, my thoughts began racing uncontrollably, until I felt like I was drowning in a flood of information. Sometimes, the input was so overwhelming that my head pounded and I struggled to breathe. My thoughts didn’t even feel like mine anymore. Family and friends started to grow more and more distant from me. This device was stuck inside my brain like superglue, and sometimes I just wanted to dig it right out of my skull. When I asked the doctor about removing it, he looked at me and smirked, “Why on earth would you want to get rid of such a game-changing device? Neuralink’s the new normal, honey. Get used to it.” *** A honk startles me as a car zooms past, nearly colliding with mine. I turn into a quieter street to regain my composure. But then – suddenly – thoughts of accelerating the car bombard my mind – so loud that I can barely hear myself think. The speedometer rises from 60 to 80 to 100 km an hour. I desperately try to disconnect my Neuralink from the car, to manually override the system – anything that will slow the car down. I start pushing random buttons hoping that I will get some kind of response. A red light flashes on my dashboard. ERROR. SIGNAL DISRUPTED BY UNKNOWN USER. I look up and meet the panicked eyes of a woman pushing a man in a wheelchair. Noah, April 7th 2044 The sun makes its final, glorious descent below the horizon, painting a beautiful array of pinks and oranges across the sky. I take a deep breath as Sophia, my support worker, pushes me along the road. We’re on our way to the grocery store, just in time for the end of day specials, which are all I can afford right now. Since my accident, I’ve tried my best to appreciate what I have, but it isn’t easy. Some days, I’m filled with rage as I struggle to complete daily tasks that I did on autopilot before my accident – back when I wasn’t confined to a wheelchair. It’s been hard to come to terms with this new body that I’m stuck with, and all the ways it seems to betray me. I miss the simple things – going to the grocery store by myself or playing board games with friends. But most of all, I miss working as an architect. I loved seeing my clients’ faces light up as they imagined the memories they would make in the new homes I had designed. This sense of satisfaction was taken from me the moment I was paralysed from the neck down. It’s why I’m so desperate to get a Neuralink implant. I would get one right this second if they weren’t so expensive. The Neuralink device isn’t covered by my insurance because the government claims that it wouldn’t be ‘cost effective’. While it won’t restore movement in my arms and legs, this implant would give me some precious freedom back. Maybe if I keep saving and take out a loan, I’ll have just enough to cover it and get my life back … *** “God, these Tesla drivers think they own the road!” I chuckle at Sophia, as a Tesla races towards the crossing in this 40km zone. As we begin to cross the road, I realise that the Tesla is showing no signs of slowing down. The car swerves violently, hurtling towards us without mercy. Sophia’s face pales as she frantically tries to push me out of the road. I squeeze my eyes shut, bracing for impact. Bibliography: Cernat, M., Borțun, D., & Matei, C. (2022, April). Human-Computer Interaction: Ethical Perspectives on Technology and Its (Mis) uses. In International Conference on Enterprise Information Systems (pp. 338-349). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-39386-0_16 Fridman, Lex. (Host). (2024, August 3rd). Elon Musk: Neuralink and the Future of Humanity (No 438). [Audio podcast episode]. In Lex Fridman Podcast. https://lexfridman.com/elon-musk-and-neuralink-team/ Jawad, A. J. (2021). Engineering ethics of neuralink brain computer interfaces devices. Perspective , 4 (1). https://doi.org/10.23880/abca-16000160 Oravec, B. Neurotechnology, Ethical Privacy, and Information Technology. Knighted , 36. https://www.mga.edu/arts-letters/docs/knighted-journal/Issue-6.pdf#page=37 Youssef, N. O. A., Guia, V., Walczysko, F., Suriyasuphapong, S., & Moslemi, C. (2020). Ethical concerns and consequences of Neuralink. Natural Science. https://rucforsk.ruc.dk/ws/files/75503337/NIB3_Group1_Neuralink.pdf Previous article Next article apex back to

< Back to Issue 10 Terrible Lizards and their Terrible Reconstructions by Kaya Czerwinska 2 June 2026 Illustrated by Esme MacGillivray Edited by Vicenta Wheatley This comes as a surprise to nobody, but it isn't the easiest task in the world to figure out an extinct creature’s appearance, habitat and behaviour from a few bones. Our understanding of animals is constantly evolving with new discoveries and technology, much like the species themselves. Yet, no matter how cunning we are to glean all kinds of fascinating history about those who lived so long before us, we humans can't always get it right. Let’s take a walk down memory lane to look at some of history’s more eccentric paleontological reconstructions! Stegosaurus Figure 1 W.H. Ballou’s Vision of a Flying Stegosaurus. Note. Image reproduced from (3). Stegosaurus is one of the more well-known dinosaurs and can be easily spotted among a child’s plastic figurine set. When presented with something Stegosaurus -shaped, one is left with very little doubt in their mind that it is, indeed, a Stegosaurus . There’s no modern animal quite like it. However, this distinctness is exactly what gave scientists trouble when they first discovered it. More specifically, why did it have plates on its body, and where were they supposed to go? Othniel Charles Marsh, the paleontologist who discovered it, initially believed that the plates sat flat over its back like armour or roof tiles (1). This is where its name, which translates to ‘roofed lizard’, came from. The confusion did not end after realising the plates were supposed to stand upright, though. Imaginations ran wild as their function remained unclear. One 1912 edition of the Cincinnati Enquirer claimed that they were used for defence against predators, calling Stegosaurus the ‘most grotesque animal’ and ‘a freak of nature’ (2). Another article, written by William Hosea Ballou, was published in the Ogden Standard-Examiner in 1920, suggesting that it used its plates like wings for gliding or flight (3). This was considered absurd even for the time, but was certainly charming to picture. To this day, what our spiky friends used their plates for is up for debate. Some of the more recent hypotheses are that they assisted with regulating temperature or colourful displays, which have been supported by the discovery of channels inside the plates that might have held blood vessels (4). However, even once we conclusively figure out what their true function was, flying Stegosaurus will remain a whimsical and creative interpretation. Elasmosaurus Figure 2 Cope’s Initial Reconstruction of Elasmosaurus with its Head on the Wrong End. Note. Image reproduced from (5). Sometimes, one can get so distracted by workplace drama that they can’t make head nor tail of the work they’re supposed to be doing - literally. This was the case for Edward Drinker Cope, a rival of Othniel Charles Marsh (who described Stegosaurus ). Both paleontologists competed to discover more new species, often criticising and even sabotaging each other’s work. In 1869, Cope attempted to describe a new marine creature called Elasmosaurus , which had four flippers and a long neck, almost like the Loch Ness monster (5). Unfortunately, he made one crucial error. In his reconstruction, he had mistakenly attached the head to the tail end instead of the neck. While it was quickly pointed out and fixed, Cope’s blunder was much to the amusement of Marsh, who frequently mentioned it in order to call Cope a ‘careless’ scientist who rushed his work (6). People tend to use this moment as an example of the many insults and arguments Marsh and Cope threw at each other during their lifelong feud. However, an animal like Elasmosaurus had not been seen before, and it’s very common for lizards to have long tails. Deciding that the longer end must be the tail wouldn’t have been a completely unreasonable guess at the time. At the end of the day, it’s important to remember that paleontologists during their time were working from much less information than we have today. Hallucigenia Figure 3. Initial Reconstruction of Hallucigenia Walking Using Spines. Note. Image reproduced from (7). Hallucigenia ’s name means ‘hallucination’ or ‘dream producer’, which is a good indicator of the experience scientists had while attempting to figure this creature out. It lived around 505 million years ago during the Cambrian era, a time when evolution was being particularly experimental (7). All kinds of strange, worm-like creatures were wandering the ocean floor, and many of them were very small. This certainly doesn’t help scientists trying to interpret the vague and cryptic shapes these animals can create when they become fossils. The first proposed idea about Hallucigenia was that it moved on a set of stiff, straight legs, with tentacles coming out of its back (8). If that wasn’t confusing enough, there was also a mysterious stain near one end of the initial fossil’s body, prompting debate about which side was the head. The mystery was finally solved when a second specimen was discovered, sitting in the rock at a different angle that allowed its legs to be seen more clearly. The ‘legs’ were actually spines on its back, and its real legs were the ‘tentacles’ (9). Scientists had been looking at it upside-down the whole time. While we finally know roughly what it looked like, Hallucigenia continues to be somewhat of an enigma to this day, with many things left to figure out about its place in the tree of life and its relatedness to other species. Oviraptor Figure 4. Oviraptor Embryo from Flaming Cliffs. Note. Image reproduced from (12). As a fossilised animal’s behaviour can’t be observed in action, scientists often rely on context clues from the environment that the fossil was found in. This was the case for a dinosaur discovered on top of a nest of fossilised eggs in 1924. The new species was named Oviraptor , meaning ‘egg thief’, in reference to the belief that it preyed on the eggs of another dinosaur called Protoceratops (10). However, some later analyses revealed that Oviraptor didn’t have teeth well-suited for eating eggs, and probably didn’t include them in its diet (11). It was later discovered that the eggs from the original specimen contained not Protoceratops , but baby Oviraptor embryos - Oviraptor had been framed for eating its own children (12). While the mistake has been rectified for several decades by now, it is still food for thought that humanity’s first instinct was to assume this dinosaur was hunting the eggs and not incubating them. There has, first through our knowledge gaps and later through pop culture portrayals, persisted an idea of dinosaurs as nothing more than scaly, destructive beasts. Dinosaurs are unintelligent and run purely on impulse. Dinosaurs kill on sight. Dinosaurs would never take care of their children. Yet, they did. Humans are not the only animals capable of caring or compassionate acts, and Oviraptor is a reminder to be careful of anthropocentrism. Woolly Rhinoceros Figure 5. Reconstruction of the ‘Unicorn’ by Gottfried Wilhelm Leibniz. Note. Image reproduced from (13). Almost the holy grail of paleontological blunders is the Magdeburg Unicorn. Not knowing how to put together a Woolly Rhinoceros skeleton is understandable, but this specific reconstruction of one has many notable issues, including a lack of back legs and a completely missing torso. The glaring inaccuracies can be attributed to the fact that the fossil was discovered and reconstructed in the 1600s, long before any other examples in this article (13). Paleontology as a discipline was still in its infancy, and beliefs in creatures such as unicorns were still common. Thus, when a number of woolly rhinoceros and woolly mammoth bones were discovered in a cave, inexperience and superstition combined to manifest them into a brand new creature. The origin of the horn is somewhat dubious but was most likely a narwhal tusk (14). As paleontology advanced, the unicorn’s status as a plausible reconstruction gradually slipped away. However, on a bad day, it’s still helpful to picture a living Magdeburg Unicorn frolicking through fields in all its bizarre glory. Perhaps if this article had been written a few years from now, there would be a few new entries about animals that we think we understand well today. The only constant truth in science is that it never stops moving forward. With every step, we leave behind a piece of what we thought the truth was, and it’s only fair to show some appreciation for those who laid the path. However, two things can be true at once. We can respect the hard work of each scientist in history who has made attempts to improve humanity’s understanding of the world around us. And we can also laugh at the fact that in hindsight, many of those attempts turned out to be spectacularly strange. References Marsh OC. A new order of extinct Reptilia (Stegosauria) from the Jurassic of the Rocky Mountains. Zenodo [Internet]. 1877 Dec 1; Available from: https://zenodo.org/record/1450038#.YoPJRIjMLrc The Ogden standard-examiner. (Ogden, UT), Aug. 15 1920. https://www.loc.gov/item/sn85058393/1920-08-15/ed-1/ . "Was Most Grotesque Animal" Newspapers.com . The Cincinnati Enquirer, 22 June 1912. https://www.newspapers.com/article/the-cincinnati-enquirer-was-most-grotesq/113116207/ . Farlow JO, Hayashi S, Tattersall GJ. Internal vascularity of the dermal plates of Stegosaurus (Ornithischia, Thyreophora). Swiss Journal of Geosciences. 2010 Aug 24;103(2):173–85. Cope ED. The Fossil Reptiles of New Jersey (Continued). The American Naturalist. 1869 Apr 1;3(2):84–91. Davidson JP. Bonehead mistakes: The background in scientific literature and illustrations for Edward Drinker Cope’s first restoration of Elasmosaurus platyurus. Proceedings of the Academy of Natural Sciences of Philadelphia. 2002 Oct;152(1):215–40. Conway Morris S. A new metazoan from the Cambrian Burgess Shale of British Columbia. Palaeontology. 1977;20(3):623–40. Stephen Jay Gould. Wonderful life : the Burgess Shale and the nature of history. New York: W.W. Norton & Company; 1989. Ramsköld L, Xianguang H. New early Cambrian animal and onychophoran affinities of enigmatic metazoans. Nature. 1991 May;351(6323):225–8. Henry Fairfield Osborn. Three new Theropoda, Protoceratops zone, central Mongolia. American Museum Novitates. 1924 Jan 1;144:1–12. Barsbold, R. "Khishchnye dinosavry mela Mongoliy" [Carnivorous Dinosaur of the Cretaceous of Mongolia]. Transactions of the Joint Soviet-Mongolian Paleontological Expedition . 1983 19: 5–119. Norell MA, Clark JM, Demberelyin D, Rhinchen B, Chiappe LM, Davidson AR, et al. A Theropod Dinosaur Embryo and the Affinities of the Flaming Cliffs Dinosaur Eggs. Science. 1994 Nov 4;266(5186):779–82. Gottfried Wilhelm Leibniz. Protogaea. University of Chicago Press; 2008. Kolfschoten, Thijs. THE WOOLLY RHINOCEROS FROM SEWECKENBERGE NEAR QUEDLINBURG (GERMANY). 157. 39-48. doi:10.11588/propylaeum.868.c11306. Previous article back to Fact & Fiction Next article

< Back to Issue 9 It’s Dangerous to Go Alone by Julia Lockerd 28 October 2025 Illustrated by Jason Chien Edited by Luci Ackland It’s safe to say that as a species, we have done a fair bit of thinking over the years. From microbes to mammals, to mapping the stars, we have always searched for ways to make meaning of the world and its many mysteries. Every day, the amount of knowledge possessed grows, building on the ideas we learn from each other. But what is knowledge without someone to know it? And how can we build a reliable foundation upon which to amass this knowledge? Many modern philosophers take a ‘what’s mine is mine’ approach to epistemology – the development of knowledge – with ideas like trust and collaboration altogether excluded from the recipe for ‘good science’ (1). Philosopher John Locke suggests that an ‘autonomous knower’ (2) – that’s you! – should only accept input from someone existing outside the self if she already possesses empirical evidence confirming that input is true (3). That is to say, don’t believe anything you read online, or in a book, or hear from your friend, or your professor alone. Basically, don’t believe the sky is blue unless you can look outside and see it for yourself. This seems like a hard way to live and makes it nearly impossible to make any headway on scientific advancement. If there is truly no way to build on previous knowledge, how do we measure anything at all? When considering scientific disciplines, the (presumably brooding) ‘autonomous knower’ must give up her lone wolf life and finally make some friends. This is not only for her emotional benefit, but also because science simply cannot occur without it. Epstein (2006) argues that the three main drivers of scientific collaboration are as follows: 1. The topic demands it. This applies to fields such as cognitive psychology, where the topic is an amalgam of different specialisations. 2. To gain a new perspective. Researchers interviewed by Epstein highlighted how collaboration helps them gain new approaches and techniques. 3. To provide additional knowledge. Although it’s all well and good to assert you should only believe what you can prove yourself (looking at you, Locke), collaboration is crucial to avoid ‘reinventing the wheel’ every time you want to learn something new (4). This last reason, by its very nature, proves that, despite my best efforts, no one person can possess the whole of human understanding by herself. Thus, the ‘many-headed knower’ makes her appearance on stage. This version of the knower exists as an alternative to Locke’s Autonomous Knower, where multiple individuals can share fragments of a greater epistemic idea. Without it, whole scientific disciplines can be reasoned away as no single person possesses the evidence to prove the scientific idea exists (2). For example, many medical devices could not be realised without input from both clinicians and engineers. If knowledge cannot be shared between these two groups, MedTech might cease to exist at all. With the multiheaded knower by your side, you can now solve scientific conundrums with the power of friendship (or, begrudging teamwork if it’s 11.59pm and you’re still working on that group project due at 12.00am). To fully grasp how systems of collaboration function, we need to investigate the interpersonal relationships that make up the heads of the knower. Generally, these relationships are of two kinds: Moral and Epistemic trust. Returning to our old friend, the multi-headed knower, epistemic trust allows multiple heads to exist, while moral trust in social bonds between researchers keeps her many heads attached. Epistemic trust involves the acceptance of knowledge provided by an external source as true. While trustworthiness often evokes a sense of superior moral value, epistemic trust has far more to do with the perceived competency of the individual providing information. Wagenknecht calls these relationships ‘Epistemic Dependence’ (5). The word dependence here is interesting, as it reveals a certain vulnerability in the relationship between researchers. Wagenknecht likens it to someone asking for directions in a foreign city. Simply, it is a blind trust that one's partner knows the way to go and is capable of leading them there. But where does this trust come from? If trust were truly blind, I could justify my lab results with a simple ‘Trust me bro,’ and my supervisor would go ‘Fantastic. Nobel prize for you.’ Unfortunately, this isn’t how it works, and my career trajectory will (probably) look a little more complicated. It is instead proposed that there are ‘shades of trust and distrust’ that can be influenced by external modifiers, such as accurate conduct of experiments, analysis of results, and epistemic authority. In this model, trust is a dynamic concept that builds or deteriorates between trustees over a chain of interactions (5). If a series of interactions is positive and trust is progressively built up, at some point, an asymptotic limit of trust will be reached. However, the level of epistemic trust between any two researchers is high but never complete, even when there is no reason to doubt the other's testimony. This is good news for Locke, as there still might be a space in which his autonomous knower can exist in happy isolation. Moral trust, the far less popular younger brother of Epistemic trust, is the scrappy underdog in the world of scientific relationships. It is argued that morality shouldn’t even get a seat at the big kids' table, as there is no place for it in scientific collaboration (2). This raises the ever-devious question: why not lie? A little fudge of the numbers could make you the next Elizabeth Holmes, minus the jail time and general disgrace (6). To find an answer, I turn to T.M. Scanlon’s ‘What We Owe Each Other’ (7). Specifically, in chapter five, he discusses the ever-sexy ‘structure of moral contractualism’. Scanlon explores a set of moral requirements that must be accepted or rejected based on the concern we hold for another's well-being, their own personal values, and perspective. Simply, academic falsification is rare because one researcher owes it to another to give a truthful testimony. Returning to the analogy of being lost in a foreign city, what keeps the locals from sending a tourist in the wrong direction out of laziness or fun? I argue that it is the acceptance of a moral principle out of concern for another person's well-being. Immanuel Kant believed lying was always wrong, in every situation (a stance I’m sure made him suuuuuuuuper fun to be around) (8). If this is true, the structure of scientific collaboration must surely crumble in the absence of moral trust (9). Interestingly, Scanlon discusses the place of ‘impersonal values’ in the development of moral code. This relates to reasons for adherence to a moral code that does not pertain to the well-being or status of any one individual. He uses the preservation of the Grand Canyon as an example. We do not deface the Grand Canyon because it would harm any particular group of people, and we cannot argue that this principle is 'what we owe to others', as the canyon doesn't have any personal feelings (that we know of). Instead, only the value we have tied to the land itself stops us from turning it into the biggest lazy river in the world (7). In the context of research, not only do we owe it to each other to adhere to truthfulness, but we also owe it to science as a concept. Essentially, if you’re not doing science with a pure and truthful heart, you’re not doing science at all. Someone needs to tell Dr. Evil about this. As scientific communities have relied more and more on each other to produce collaborative results, science as a whole has become somewhat of a team sport. I argue that while epistemic and moral are two different forms of trust – or even the same form of trust applied to different issues – they both contribute to the social basis of scientific collaboration. Trust in itself is a purely social concept; just as knowledge cannot exist without a 'knower', trust cannot exist without two people, between whom that trust can exist. Therefore, whether you subscribe to the idea that moral trust has any place in scientific collaboration, it is indisputable that there is a social level to any interaction between researchers. This is to say nothing about the more 'frivolous' aspects of collaboration in which personal opinions, egos, and attitudes have been anecdotally proven to affect the quality of collaborative work. Science, at its core, is about understanding. It makes sense that we can’t even get off the ground if we don't start by understanding each other. References 1. J. Locke. An Essay concerning Human Understanding. www.gutenberg.org , 1689. Available: https://www.gutenberg.org/files/10615/10615-h/10615-h.htm 2. J. Hardwig. The Role of Trust in Knowledge. The Journal of Philosophy . 1991;88(12):693. doi: 10.2307/2027007 3. R. W. Grant. John Locke on Custom’s Power and Reason’s Authority. The Review of Politics. 2012;74(4) 607–629.doi: 10.2307/23355688. Available: https://www.jstor.org/stable/23355688 4. S. Epstein. Making Interdisciplinary Collaboration Work. Available: https://www.cs.hunter.cuny.edu/~epstein/papers/collaboration.pdf . [Accessed: Mar. 29, 2024] 5. S. Wagenknecht. Facing the Incompleteness of Epistemic Trust: Managing Dependence in Scientific Practice. Social Epistemology . 2014;29(2):160–184. doi: 10.1080/02691728.2013.794872 6. E. Fricker. Testimony and Epistemic Autonomy. The Epistemology of Testimony . 2006:225–245. doi: 10.1093/acprof:oso/9780199276011.003.0011 7. T. M. Scanlon. What We Owe to Each Other. 1998. Available: https://www.hup.harvard.edu/file/feeds/PDF/9780674248953_sample.pdf 8. T. L. Carson. Kant and the Absolute Prohibition against Lying. Lying and Deception . 2010:67–87. doi: 10.1093/acprof:oso/9780199577415.003.0004 9. Immanuel Kant. An Answer to the Question: What is Enlightenment? by Immanuel Kant 1784. Marxists.org , 1798. Available: https://www.marxists.org/reference/subject/ethics/kant/enlightenment.htm Previous article Next article Entwined back to

By Julia Lockerd Meet the New Kid By Julia Lockerd 23 March 2022 Edited by Caitlin Kane Illustrated by Quynh Anh Nguyen ‘Machines Enrol in Art Class!’ The title of the American Scientist article (1) I’m currently reading is droll take on the process of artificial intelligence (AI) learning. I imagine the first art class I ever attended had a robot classmate. “I want everyone to be very welcoming to our new student! Class this is DALL-E.” DALL-E’s name is a clever blend of surrealist painter Salvador Dali and robot character WALL-E. It is the most popular AI art platform in the world, as well as the face of a quickly expanding industry. The purpose of DALL-E is evident in its namesakes: simply, it is a robot that creates art. Artificial intelligence is described as "the science and engineering of making intelligent machines (2).” More specifically “machines that think like humans.” AI art is an application of this wider machine learning. In short, it is art created by a “thinking” computer. In mid-2022 the world of AI art became a monster of industry, with AI art platform Midjourney reporting over 12 million users since its launch in July 2022 (4). However, as with any quick advancement in technology, there are issues that come with the new power we’ve been given; there is a question we must ask ourselves: how far is too far? Back in art class, other students and I share uneasy glances as our strange companion clicks and whirrs behind his desk. I smile at him and reach out a hand. He breaks my finger and steals my Snoopy drawing right off my desk. Ouch. This is the first impression many artists had when AI art was first introduced. For years we had been told that truck drivers, factory workers and other industry roles would be fully automated in the future. This was an issue in itself, but an inevitability as the wheels of advancement turned over. Few expected that the creative industries would so quickly slip under the control of automated technology. With AI on the rise, many artists fear for their livelihoods, job prospects and their intellectual and creative property. To both create and vet the art for our personal viewing experience, AI uses tools called Generative Adversarial Networks (5). Imagine two little robots hunched over side-by-side desks. One’s job is to create images and fool the other into believing its art is original. If the second robot is fooled half the time, the first is performing as it should, creating art the public will believe is genuine. Fool me once. The definition of “genuine” art is vague at best and still under heavy debate. I believe that “genuine” is a feeling you get when you look at the art in front of you. It’s up to you to decide, can AI art ever really be genuine? Another issue arises from AI art: usually when you go to an art class, the teacher knows they’re teaching. My robot classmate begins to shuffle through its filing cabinet of pre-existing works made by humans. It’s been fed these images, paintings, photographs and learnt to reassemble the input as AI-created art (1,6,7). I can’t help but bristle in contempt as he examines my sketch of Snoopy and adds it to the ever-growing collection of “borrowed” art. As public use of AI continues to rise, we will inevitably have more ethically grey tundra to cross. In 2018 the Portrait of Edmund Belamy, sold for 432,500 USD at Christie’s Auction house. The controversy surrounding the piece stems from the fact that it was painted by an AI that had been fed 15,000 portraits from 20th century artists (7). Edmond De Belamy is not a real person, nor is the person who painted his portrait. Both are simply amalgamations of the people who came before. Which begs the questions, who deserves to be rewarded for this artistic feat? Is this painting even original? Once upon a time it was something genuine; it is up to us to decide how many times we can take the derivative of a piece of art before it loses its emotion. Or is it simply always the case that every artist takes inspiration from those who came before? When each creation is the derivative of a piece, it’s critical to examine what it’s deriving from. It is both fascinating and alarming that social biases have even made their way into the creative and malleable minds of machines. Dark-skinned people and hijab wearers have taken to social media to report their selfies, which they had run through an AI software, had returned distorted, warped or whitewashed (8). AI learns from the dataset that its human trainers provide, and it's important that we consider who and what are represented in that training. It is a strange sort of embarrassment to know that these machines and their endless learning have picked up on our shortcomings. In a world that already rejects difference and shame people for their deviation from unachievable standards, we have taught machines to do the same. Like a child passively taking up its parents' opinions. In this way, some consequences of our technological development aren’t so much AI art issues as they are societal issues. The only fix is to work to include and recognise all people in creative spaces so that machines can learn to think like all humans. Despite criticism and philosophising, we cannot stop the march of progress. AI will continue to advance, to become better at thinking and emulating us. Perhaps our responsibility will just be to give them something good to copy. As for traditional artists left behind by the AI advance? I believe we’ll be okay. We differ from machines, and there will always be something more rewarding than just an output. The joy is in the creation, the connection, and the humanity of art. Half of my art class is robots now, churning out hundreds of creations per second. I hold up a half-finished picture to my desk mate to see their smile. That moment of connection is why it’s worth staying until the end of the class. References Elgammal A. AI Is Blurring the Definition of Artist [Internet]. American Scientist. 2019. Available from: https://www.americanscientist.org/article/ai-is-blurring-the-definition-of-artist McCarthy J. What is AI? [Internet]. Stanford.edu. 2012. Available from: http://jmc.stanford.edu/articles/whatisai.html Midjourney Discord Interface [Internet]. docs.midjourney.com. Available from: https://docs.midjourney.com/docs/midjourney-discord Hughes RT, Zhu L, Bednarz T. Generative Adversarial Networks–Enabled Human–Artificial Intelligence Collaborative Applications for Creative and Design Industries: A Systematic Review of Current Approaches and Trends. Frontiers in Artificial Intelligence. 2021 Apr 28;4. Goodyear S. Why those AI-generated portraits all over social media have artists on edge [Internet]. CBC. 2022. Available from: https://www.cbc.ca/radio/asithappens/artificial-intelligence-ai-art-ethics-greg-rutkowski-1.6679466 Christie's. Is artificial intelligence set to become art’s next medium [Internet]. Christies.com. Christies; 2018. Available from: https://www.christies.com/features/A-collaboration-between-two-artists-one-human-one-a-machine-9332-1.aspx GANs. Edmond De Belamy, From La Famille de Belamy [Internet]. Caselles-Dupré H, Fautrel P, Vernier G, editors. original gilded wood frame. 2018. Available from: https://www.christies.com/lot/lot-edmond-de-belamy-from-la-famille-de-6166184/?from=salesummery&intobjectid=6166184&sid=18abf70b-239c-41f7-bf78-99c5a4370bc7 AI selfies — and their critics — are taking the internet by storm. Washington Post [Internet]. Available from: https://www.washingtonpost.com/technology/2022/12/08/lensa-ai-portraits/ Previous article Next article

< Back to Issue 7 Soaring Heights: An Ode to the Airliner by Aisyah Mohammad Sulhanuddin 22 October 2024 edited by Lauren Zhang illustrated by Esme MacGillivray A smile at your neighbour-to-be, a quick check and an awkward squeeze as you sidle into your seat: 18A. Window seat, a coveted treasure! A clatter . Whoops! As you fumble for your dropped phone, your feet–which jut out ungracefully onto the aisle, end up as a speed bump for the wheels of someone’s carry-on. Yeowch! It isn’t without more jostling that everyone finally settles into their seats, and with a scan at the window, the tarmac outside is looking busy. Hmm. It makes sense–this flight is just one of the 36.8 million trips around the world flown over the past year (International Air Transport Association, 2024). Commercial aviation has clocked many miles since its first official iteration in 1914: a 27-km long “airboat” route established around Tampa Bay, Florida (National Air and Space Museum, 2022). Proving successful, it catalysed an industry and led to the establishment of carriers like Qantas, and the Netherlands’ KLM. Mechanics of Ascent (and Staying Afloat) As said Qantas plane pulls up in the window view, its tail dipped red with the roo taxies ahead of you on the tarmac. Your plane is now at the front of the runway queue and the engines begin to roar. You’re thrusted backwards as gravity moulds you to your seat. For a split second, as you look out the window, you can’t help but wonder– how on earth did you even get up here? How is this heavy, huge plane not falling out of the sky? The ability for a plane to stay afloat lies in its wings, which allow the plane to fly. The wings enable this through generating lift (NASA, 2022). Lift is described as one of the forces acting on an object like a plane, countering weight under gravity which is the force acting in the opposite direction, according to Newton’s Third Law ( figure 1a ). A plane's wings are constructed in a curved ‘airfoil’ shape with optimal aerodynamic properties: as pressure decreases above the wing with deflected oncoming air pushed up, the velocity increases, as per Bernoulli’s principle. This increases the difference in pressure above and below the wing, which remains high, generating a lift force that pushes the plane upwards (NASA, 2022) ( figure 1b ). Figure 1a. Forces that act on a plane . Note. From Four Forces on an Airplane by Glenn Research Centre. NASA, 2022 . https://www1.grc.nasa.gov/beginners-guide-to-aeronautics/four-forces-on-an-airplane/ . Copyright 2022 NASA. Figure 1b. An airfoil, with geometric properties suitable for generating lift. Note. From Four Forces of Flight by Let’s Talk Science. Let’s Talk Science, 2024. https://letstalkscience.ca/educational-resources/backgrounders/four-forces-flight . Copyright 2021 Let’s Talk Science. Looking laterally, the thrust of a plane’s engines counters the horizontal drag force that airfoils minimise, all whilst maximising lift. Advancements in plane design over the mid-20th century focused on optimising this ‘Lift to Drag ratio’ for greater efficiency, a priority stemming from the austere, military landscape of World War II (National Air and Space Museum, 2022). Influenced by warplane manufacturing trends, the commercial sphere saw a transition from wooden to durable aluminium frames. In conjunction with this, double-wing biplanes were superseded by single-wing monoplanes ( figure 2a, b ), which had a safer configuration that reduced airflow interference whilst maximising speed and stability (Chatfield, 1928). Figure 2a. A biplane, the De Havilland DH-82A Tiger Moth. Note. From DH-82A Tiger Moth [photograph] by Temora Aviation Museum. Temora Aviation Museum, 2017 . https://aviationmuseum.com.au/dh-82a-tiger-moth/ . Copyright 2024 Temora Aviation Museum. Figure 2b. A monoplane, an Airbus A310. Note. From Airbus A310-221, Swissair AN0521293 [photograph] by Aragão, P, 1995. Wikimedia Commons . https://commons.wikimedia.org/wiki/File:Airbus_A310-221,_Swissair_AN0521293.jpg CC BY-SA 3.0. Taking a Breather Without really noticing it, you’re somewhat upright again. Employing head shakes and gulps to make your own ears pop, you can also hear the babies bawling in discomfort a few aisles back. Blocked ears are our body’s response to atmospheric pressure changes that occur faster than our ears can adjust to (Bhattacharya et al., 2019). Atmospheric pressure describes the weight of air in the atmosphere above a given region of the Earth’s surface (NOAA, 2023), which decreases with altitude. Our bodies are suited to pressure conditions at sea level, allowing sufficient intake of oxygen through saturated haemoglobin within the bloodstream. Subsequently, the average human body can maintain this intake until 10000 ft (around 3000 m) in the air, with altitudes exceeding this likely to result in hypoxia and impairment (Bagshaw & Illig, 2018). Such limits have had implications for commercial flying. Trips in the early era were capped at low altitudes and proved highly uncomfortable: passengers were exposed to chilly winds, roaring engines, and thinner air, and pilots were forced to navigate around geographical obstacles like mountain ranges and low-lying weather irregularities. However, this changed in 1938 when Boeing unveiled the 307 Stratoliner, which featured pressurised cabins. Since then, air travel above breathing limits became possible, morphing into the high-altitude trips taken today (National Air and Space Museum, 2022). Via a process still relevant to us today, excess clean air left untouched by jet engines in combustion is diverted away, cooled, and pumped into the cabin (Filburn, 2019). Carried out in incremental adjustments during ascent and descent, the pressure controller regulates air inflow based on the cockpit’s readings of cruising altitude. Mass computerisation in the late 20th century enabled precise real-time readings, allowing safety features like sensitive pressure release valves, sensor-triggered oxygen mask deployment, or manual depressurisation. However, the sky does indeed dictate the limits, as pressure conditions are simulated at slightly higher altitudes than sea level to avoid fuselage strain (Filburn, 2019). This minor pressure discrepancy plays a part in why we feel weary and tired whilst flying–our cells are working at an oxygen deficit for the duration of the flight. Your yawn just about now proves this point. Time for your first snooze of many… Food, Glorious Food A groggy couple of hours later and it’s either lunch time or dinner, your head isn’t too sure. You wait with bated breath, anticipating the arrival of the flight attendant wheeling the bulky cart through the narrow aisle... Only to be met with a chicken sausage that vaguely tastes like chicken, with vaguely-mashed potato and a vaguely-limp salad on the side. Oh, and don’t forget the searing sweetness of the jelly cup! You’re far from alone in your lukewarm reception of your lunch-dinner. Aeroplane food remains notorious amongst travellers for its supposedly flat taste. Whilst airlines like Thai Airways and Air France have employed Michelin-star chefs to translate an assortment of gourmet cultural dishes to tray table fare (De Syon, 2008; Thai Airways, 2018), the common culprit responsible for the less-than-appetising experience remains – being on a plane. As Spence (2017) details, multiple factors play into how you rate your inflight dinner, many relating to the effects of air travel on our bodies. The ‘above sea level’ air pressure within the plane coincides with higher thresholds for detecting bitterness at 5000-10000 ft (around 1500-3000m), heightening our sensitivity to the tart undertones of everyday foods. Dry pressurised air that cycles through the cabin is about as humid as desert environments, which hampers our smell perception and thus taste. Less intuitively, the loud ambient noise of the plane’s engines also appears to hinder olfactory perception, though the reason as to why remains unclear. Nevertheless, alleviating the grumbling passenger and stomach is an area of interest with a few successful forays. One angle of approach involves food enhancement. Incorporating sensory and textural elements into meals such as chillies and the occasional crunch or crackle can compensate for impaired perception. Interestingly, umami has been observed as the least affected taste sense mid-air (Spence, 2017), inspiring British Airways’ intense and aromatic umami-rich menus – though with the unwitting drawback of threatening to stink up the plane on multiple occasions (Moskvitch, 2015). Meanwhile, Singapore Changi Airport houses a simulation chamber for food preparation in a low-pressure environment, taking it up a notch in both quality and cost (Moskvitch, 2015). Alternatively, passengers can be psychologically tricked into perceiving food to be more appetising than it is in reality. Some examples of this include the use of noise-cancelling headphones, cabin lighting designed for enhancing the appearance of food, or appealing language for describing meals. Both off-ground and in air, it was found that humans were inclined to respond more positively to dishes described in an appetising and detailed manner (Spence, 2017), rather than the vague choices of “sausage or pasta”. Whilst these innovations have covered some ground, De Syon (2008) also notes that sociology can influence our perceptions of food on a plane. The enjoyment of meals is dependent upon core social rituals like dining communally or comforting meal-time habits–both of which are tricky to navigate and achieve on a packed plane with front-on seating. What Goes Up Must Come Down Not long now! Accompanied by the movies you’ve played for the first time in your life and oodles of complimentary tea, there’s about half an hour left until landing. Jolt! The seatbelt sign is bold and bright as you can feel the plane gradually descending–it’s getting bumpy! As your plane rocks about and the airport comes into view as a speck in the distance, your descent is at the mercy of the crosswinds… and turbulence? Not only do these vortices of air cause havoc mid-flight, near cloud bands and thunderstorms (National Weather Service, 2019), they also pose a challenge during landing in the form of local, “clear-air” convection currents invisible on radar. These currents often occur in summer months and in the early afternoon when incoming solar energy is at its highest. In particular, they emerge when the surface of the earth is unevenly heated, including across regions such as the oceans, grassland, or in this case, the pavement near the airport. Consequently, this creates pockets of warm and cool air that rapidly rise and fall, creating downdrafts, thereby trapping planes ( figure 3 ). Luckily, pilots are specifically trained to recognise these surface winds, and can adjust their landing glidepath to suit local conditions forewarned in Terminal Aerodrome Forecasts for a steady, controlled descent (BOM, 2014). Figure 3. Varying glidepath due to local convection currents - note the different types of surfaces. Note. From Turbulence by National Weather Service. National Weather Service, 2019. https://www.weather.gov/source/zhu/ZHU_Training_Page/turbulence_stuff/turbulence/turbulence.htm . Copyright 2019 National Weather Service. Even with its bumpier experiences that draw endless complaints, it is undeniable that commercial aviation has grown tremendously over the century to deliver the safe, efficient and comfortable flights we are accustomed to today. Building upon a history of ingenuity and scientific discovery, it's almost certain that the industry will soar to even greater heights in our increasingly globalised world. Enough talk–you’re finally here! It’s a relief when you clamber from your seat, giving those arms and legs a much needed stretch. Now, time to trod along on solid ground… …and onto the connecting flight. Cheap stopover tickets. Darn it. References Aragão, P. (1995). Airbus A310-221, Swissair AN0521293 . Wikimedia Commons. https://upload.wikimedia.org/wikipedia/commons/9/9b/Airbus_A310-221%2C_Swissair_JP5963897.jpg Bagshaw, M., & Illig, P. (2019). The aircraft cabin environment. Travel Medicine , 429–436. https://doi.org/10.1016/b978-0-323-54696-6.00047-1 Bhattacharya, S., Singh, A., & Marzo, R. R. (2019). “Airplane ear”—A neglected yet preventable problem. AIMS Public Health , 6 (3), 320–325. https://doi.org/10.3934/publichealth.2019.3.320 BOM. (2014). Hazardous Weather Phenomena - Turbulence . Bureau of Meteorology. http://www.bom.gov.au/aviation/data/education/turbulence.pdf Chatfield, C. H. (1928). Monoplane or Biplane. SAE Transactions , 23 , 217–264. http://www.jstor.org/stable/44437123 De Syon, G. (2008). Is it really better to travel than to arrive? Airline food as a reflection of consumer anxiety. In Food for Thought: Essays on Eating and Culture (pp. 199–207). McFarland. Filburn, T. (2019). Cabin pressurization and air-conditioning. Commercial Aviation in the Jet Era and the Systems That Make It Possible , 45–57. https://doi.org/10.1007/978-3-030-20111-1_4 International Air Transport Association. (2024). Global Outlook for Air Transport . https://www.iata.org/en/iata-repository/publications/economic-reports/global-outlook-for-air-transport-june-2024-report/ Let’s Talk Science. (2024). Four Forces of Flight . Let’s Talk Science. https://letstalkscience.ca/educational-resources/backgrounders/four-forces-flight Moskvitch, K. (2015, January 12). Why does food taste different on planes? British Broadcasting Corporation. https://www.bbc.com/future/article/20150112-why-in-flight-food-tastes-weird NASA. (2022). Four forces on an Airplane . Glenn Research Center | NASA. https://www1.grc.nasa.gov/beginners-guide-to-aeronautics/four-forces-on-an-airplane/ National Air and Space Museum. (2022). The Evolution of the Commercial Flying Experience . National Air and Space Museum; Smithsonian. https://airandspace.si.edu/explore/stories/evolution-commercial-flying-experience National Weather Service. (2019). Turbulence . National Weather Service. https://www.weather.gov/source/zhu/ZHU_Training_Page/turbulence_stuff/turbulence/turbulence.htm NOAA. (2023). Air pressure . National Oceanic and Atmospheric Administration. https://www.noaa.gov/jetstream/atmosphere/air-pressure Spence, C. (2017). Tasting in the air: A review. International Journal of Gastronomy and Food Science , 9 , 10–15. https://doi.org/10.1016/j.ijgfs.2017.05.001 Temora Aviation Museum. (2017). DH-82A Tiger Moth . Temora Aviation Museum. https://aviationmuseum.com.au/dh-82a-tiger-moth/ Thai Airways. (2018). THAI launches Michelin Star street food prepared by Jay Fai for Royal Silk Class and Royal First Class passengers . Thai Airways. https://www.thaiairways.com/en_ID/news/news_announcement/news_detail/News33.page Previous article Next article apex back to

< Back to Issue 4 The Power of Light by Serenie Tsai 1 July 2023 Edited by Yasmin Potts and Tanya Kovacevic Illustrated by Pia Barraza Light is often a symbol of greatness, and rightly so, with its ability to be both visible and invisible. It exists in the form of wavelengths, which we view as a multitude of colours. However, the powers of light extend beyond that: light has the potential to manipulate the way we see things, resulting in mesmerising and sometimes mind-boggling illusions. Colour is nothing without light Light is a form of electromagnetic radiation that lies on a spectrum. Due to our limited ability to see these electromagnetic waves, we are only able to see what is characterised as visible light [1]. Colours exist as different wavelengths in a rainbow-coloured order, with red being the longest wavelength and violet being the shortest wavelength, and these colours are detected by cone-shaped cells in our eyes [2]. There are two types of common light rays outside of our visible light range, ultraviolet and infrared light, positioning animals who can detect these to have superior vision [3]. Moreover, as colours and lights exist in the form of wavelengths, temperature can affect what is seen. For example, hot objects radiate short wavelengths, changing the colour we see, such as a hot flame having a range of red to blue colours, because of the way heat radiates from it [1]. Role of light in the mirage There is an age-old question: what would you do with the power to be invisible for a day? Well, the ability to do this is not that far into the future, with many scientists developing methods to make this a reality. Magicians use a common trick of placing mirrors strategically for a disappearing act. The use of mirrors reflects light away from the object so all we see is empty space because our eyes are programmed to view light as a straight line, so we struggle to process it any other way [4]. So far, this has worked successfully to disappear objects on a small scale. However, scientists are finding ways to amplify this technique to disguise larger items or even a person. A recent viral TikTok video is baffling people as to how a mirror can reflect an object hidden behind a piece of paper. Let’s unpack the science behind this trick. When light rays hit an object, photons of light are reflected off it in all directions, and some of these rays will hit the mirror. So, when you look at the object at a certain angle, you can also see it being reflected into the mirror, despite having a boundary in-between [5]. Similarly, this sort of illusion can be seen in nature itself. There is an optical phenomenon in the desert, which produces a mirage image on the ground. Because heat affects wavelengths of light, a warm surface on the ground can bend the rays of light from the sun upward, creating what is known as an inferior image. For example, this could make it seem like there is water on the ground, when in fact it is a reflection of the sky because an image of a distant object can be seen below the actual position of the object. Likewise, if there was cool air underneath, it would create a superior image [6]. This is all due to a temperature gradient created between the ground and the atmosphere above it [7]. Invisibility in the movies Violet from The Incredibles and the Fantastic Four heroine, the Invisible Woman, can both become invisible at their own will. While these examples are only in the movies, there is some truth here. Light can be manipulated to create an illusion, although it is unlikely to appear as realistic as an invisibility cloak. A more theoretically possible form of light manipulation would be the advanced technology portrayed in movies such as Marvel and Harry Potter. It features hovercrafts and a flying car, respectively, that possess the ability to camouflage themselves against their background. This is done through reflective plates, which become a mirror to match the surrounding objects and reflect light away to conceal the object. Another example of a cinematic light-based mirage is in the movie Now You See Me, which includes a series of magic tricks. In one scene, a character is shown to stop rain mid-air and control its movement with his hands. Sorry to ruin the magical illusion, but this one is merely a simple trick of strobe lights flashing repeatedly at the right frequency which makes it seem like the rain is stopped in mid-air. It also requires some movie magic and a large-scale rain machine to control the droplets [8]. There has been so much progress on movie-making to make creative imaginations a reality. For example, there is a new focus on transformation optics, the application of metamaterials to manipulate electromagnetic radiation. Metamaterials are designed with unique patterns to interact with light and other energy forms artificially. For example, Pyrex glass and oil have the same refractive index, so if you put these items together, the refraction of light against these objects can make it disappear out of view [9]. This is an easy trick you can try at home. Overall, light has a multitude of abilities that are still untapped. However, there is hope in society's ability to take advantage of technology and discover more uses for light, and its ability to evade the human eye. We could soon be having magic shows worthy of contending with even the most bizarre movies. References Visible Light | Science Mission Directorate [Internet]. science.nasa.gov . Available from: https://science.nasa.gov/ems/09_visiblelight#:~:text=WAVELENGTHS%20OF%20VISIBLE%20LIGHT Fara P. Newton shows the light: a commentary on Newton (1672) “A letter ... containing his new theory about light and colours...” Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 2015 Mar 6;373(2039):20140213–3. Animals See a World That’s Completely Invisible to Our Eyes [Internet]. All About Vision. [cited 2023 Jun 26]. Available from: https://www.allaboutvision.com/eye-care/pets-animals/how-animals-see/ David R. Smith Group [Internet]. people.ee.duke.edu . Available from: http://people.ee.duke.edu/~drsmith/transformation-optics/cloaking.htm Nicholson D. How does the mirror know what’s behind the paper? Explained! [Internet]. Danny Nic’s Science Fix. 2023 [cited 2023 Jun 26]. Available from: https://www.sciencefix.co.uk/2023/04/how-does-the-mirror-know-whats-behind-the-paper-explained/ Richey L, Stewart B, Peatross J. Creating and Analyzing a Mirage. The Physics Teacher. 2006 Oct;44(7):460–4. Li H, Wang R, Zhan H. The mechanism of formation of desert mirages. Physica Scripta. 2020 Feb 11;95(4):045501. Now You See Me 2 [Internet]. Framestore. 2016 [cited 2023 Jun 26]. Available from: https://www.framestore.com/work/now-you-see-me-2?language=en Puiu T. Human-sized invisibility cloak makes use of magic trick to hide large objects [Internet]. ZME Science. 2013 [cited 2023 Jun 26]. Available from: https://www.zmescience.com/science/physics/human-sized-cloak-hide-large-objects-543563/ Previous article Next article back to MIRAGE

< Back to Issue 4 Talking to Yourself: The Biology of Hallucinations by Lily McCann 1 July 2023 Edited by Arwen Nguyen-Ngo and Yasmin Potts Illustrated by Zhuominna Ma What is consciousness? No small question. To this day it hasn’t been entirely satisfied. Consider a conversation: There are voices from the outside, stimuli that talk to all the sensory receptors that we have. They pass on messages to our fingertips that we are touching something cold; they tell our eyes that we are seeing certain wavelengths of light; and they tell the cochlea of our ears what sounds we are hearing. The sensory circuits of our bodies bring these words from outside and turn them inward, presenting them to the centre of our consciousness: Here - this is what we are experiencing. This is what we are taking from the world outside. But already, at the base of this consciousness, an idea of the world has been established. The central experience of our mind is built upon prediction: we are constantly conjuring up an estimate of how the outside world will be. The ‘Predictive Processing’ model of consciousness states that it is the conversation between this predictive perception of the world and the feedback from our sensory experience that defines what it is to feel consciousness (1). In 1971, Nature published the conclusions of a study titled, ‘Preliminary Observations on Tickling Oneself’ (2). In this experiment, a device was used to compare the experience of being tickled by an experimenter to the experience of tickling oneself, and both were compared to the intermediate of passively following the experimenter’s arm as they tickled the participant. The study concluded that the action of tickling oneself produced no effect as the planned action of tickling cancelled out the sensation of being tickled; the lack of an action in the case of the experimenter tickling the subject’s hand, allowed for a full ‘tickle’ sensation. Interestingly, the third process of passively following the tickling action was rated at a level in between these two responses. This showed that it was not the action of tickling alone that cancelled out the sensation of the stimulus as tickling, but that a knowledge of the tickle, a prediction of it, were enough to reduce the effect. This experiment reflects the idea that it is not just our planned actions and our sensory perception that drive consciousness, but that it is prediction that has a core place in driving experience. For centuries, hallucinations have been recognised as distortions of our sense of being conscious in the world. In 1838, Esquirol wrote in his ‘Mental Maladies: A Treatise On Insanity’ that the experience of a hallucination is “a thorough conviction of the perception of a sensation, when no external object, suited to excite this sensation, has impressed the senses.” (3) Anything that distorts our ‘perception’ or ‘sensation’ can therefore give rise to a hallucination. This can occur in the context of infection, psychosis, delirium, use of certain drugs - and the aptly named ‘exploding head syndrome’. Contrary to popular opinion, hallucinations are not a feature of psychotic disorders alone. In fact, analysis has shown that no single aspect of schizophrenia-related hallucinations is specific to this disease (4). In 2000, the idea of the ‘Tickling’ study was elaborated with respect to hallucinations in an investigation comparing the experience of self-produced and externally implemented stimuli for those who both did and did not suffer from hallucinations. It was shown in this study that for participants with hallucinatory disorders, there was a breakdown in the ability to differentiate between stimuli produced externally and internally (5). This study is in line with a certain theory of hallucination purported by Frith, who suggests in his discussion of positive symptoms of schizophrenia that the foundation of hallucination is a “fault in the system which internally monitors and compares intentions and actions” (6). There is another interesting theory that describes hallucinations as memories released from suppression. The authors suggest that the hallucination itself is a cacophony of memory signals set loose, where normally they are shut out of our conscious mind. One study described auditory hallucinations in those with hearing loss as an “uninhibition syndrome”. They argued that in the cases studied, a lack of sensory auditory input seemed to “uninhibit neuronal groups storing auditory memory” (7). The brain is an incredibly complex organ and theories regarding consciousness and hallucinations abound. The question of greatest practical importance is what part of the process of hallucinations can we understand and therefore, what can be targeted when we are called to treat this system in a medical setting. Recent investigations have linked various molecules, receptors and genes to hallucinatory disorders or states, whilst imaging studies demonstrate networks and regions of the brain activated during hallucinations. Investigation of certain receptor-modulating drugs has revealed the place of certain molecules in delusion and sensation; and the association of certain genes to hallucination-prone phenotypes has established a genetic cause for susceptibilities to hallucination. This research yields molecular and genetic targets for therapies that can help reduce the burden of hallucinations on an individual. It is a remarkable faculty of our minds, the ability to create a world - or aspects of the world - for ourselves and convince our own consciousness that it is real. Hallucinations reveal the capacity of the human brain for imagination; they show that all we experience is indeed creative, merely restricted by what we see as truth. But the grounding fact of knowing what is real is essential to functioning in society. Losing the ability to check our own creative experience of consciousness is exceedingly frightening and disempowering. Anything that helps us to maintain the right balance of conversation between the experiences we create and those we feel allow us to maintain a sense of self in the world. Elucidating the biology behind these conversations and the effects of hallucination itself can bring us closer to a definition of consciousness. References Hohwy J, Seth A. Predictive processing as a systematic basis for identifying the neural correlates of consciousness. Philosophy and the Mind Sciences. 2020;1(2). 3. https://doi.org/10.33735/phimisci.2020.II.64 Weiskrantz L, Elliot J, Darlington C. Preliminary observations on tickling oneself. Nature. 1971 Apr 30. 230: 598–599 https://doi.org/10.1038/230598a0 Esquirol J. Mental maladies: A treatise on insanity. France: Wentworth Press; 2016 Waters F, Fernyhough C. Hallucinations: A systematic review of points of similarity and difference across diagnostic classes. National Library of Medicine. 2016 Nov 21. doi: 10.1093/schbul/sbw132 Blakemore S.J, Smith J, Steel R, Johnstone E.C. The perception of self-produced sensory stimuli in patients with auditory hallucinations and passivity experiences: Evidence for a breakdown in self-monitoring. Psychological Medicine. 2000 Oct 17. 30(5): 1131-9. https://doi.org/10.1017/S0033291799002676 Frith C. The positive and negative symptoms of schizophrenia reflect impairments in the perception and initiation of action. Psychological Medicine. 1987 Aug. 17(3): 631-648. Doi: 10.1017/s0033291700025873 Goycoolea, M., Mena, I. and Neubauer, S. (2006) ‘Spontaneous musical auditory perceptions in patients who develop abrupt bilateral sensorineural hearing loss. an uninhibition syndrome?’, Acta Oto-Laryngologica, 126(4), pp. 368–374. doi:10.1080/00016480500416942. Previous article Next article back to MIRAGE

< Back to Issue 10 Are Truths Possible Under AI? by Vanessa Cheng 2 June 2026 Illustrated by Saraf Ishmam Edited by Rita Fortune In the era of artificial intelligence (AI), humans are capable of generating wonders within seconds. Yet, isn’t it also destroying the sense of human intuition and authenticity that we are born with? The development of AI dates back to the pre-20th century when Jonathan Swift’s novel “Gulliver’s Travels” initially introduced the idea of an engine — a mechanical system used to assist the academics to generate new ideas. Throughout the 2000s, scientists have been continuously inventing “generations” of AI and discovering its applications. For instance, in 2000, MIT scientist Cynthia Breazeal invented a robot that interacts with humans, capable of reading emotional cues. In 2009, scientists at Northwestern University developed “Stats Monkey”, an engine capable of generating sports news stories without human intervention. Finally, throughout 2021 to 2023, OpenAI’s ChatGPT model DALL-E was introduced to society (1). It changed how we interpret information, how we communicate, and how we seek knowledge. Furthermore, the development of DALL-E 2 and 3 enabled us to generate visual content without traditional graphic skills. These models sparked debate surrounding ethics within the fields of politics and entertainment. On January 22, 2026, The White House posted a digitally altered photo of a woman arrested at the ICE protest, with her facial features appearing hysterical, sparking intense audience emotions (2). AI is no longer a tool, but rather a weapon with endless possibilities. The development of AI has the ability to fundamentally alter how we interact with reality. It changes how we understand knowledge and understand the world. New AI models, such as DALL-E 3, can generate hyperrealistic images, human-like texts, and even synthetic voices. Thus, the ways we can traditionally look for deception, such as hearing, seeing, and reading could no longer be a valid way of helping us understand the world. When we see something, we tend to believe that it exists; when we hear something, we assume that the voice is authentic. A photo is a proof of a scene, and our voice is our identity. However, AI disrupts this ancient relationship between how humans perceive information and reality. In fact, in Essay Concerning Human Understanding published in 1689 by the infamous philosopher John Locke, he pointed out that individuals typically understand reality through what they see and perceive, and that human knowledge originates from sensory experience (3). Our sensory experience becomes the foundation of truth itself. However, AI has disrupted this centuries old assumption. In a world where even emotions can be artificially generated, sensory perception does not guarantee authenticity. In his first text The Phenomenology of Perception , published in 1945, French philosopher Maurice Markeau-Ponty argues that human perception is our primary way of experiencing reality (4). However, with AI, traditional philosophical claims are threatened. In fact, in 2025, The New Yorker pointed out that AI models such as ChatGPT are becoming increasingly accurate in generating preferred text responses based on predictions of the user’s preference (5). Additionally, in some scientific fields, large language models predict patterns in brain activity. If such human things as thoughts, choices, and the very activity in our brains can be so easily manipulated by AI, we may have much less autonomy than we imagined. Our perceptions of reality are increasingly altered by these systems which we have created. The collapse of truth and our ability to trust our own sentences is leading to the collapse of humanity's free will. This dramatic change in how humans think and behave sparks further discussion on how we should view the ethics of AI. According to the Harvard Division of Continuing Education, AI systems raise significant ethical concerns regarding privacy, transparency, and accountability (6). Algorithms may inherit political biases and social inequalities within the training data scientists “feed” to the model. The development of deepfake images and synthetic voices not only creates ethical concerns surrounding misinformation, but also the erosion of social trust. The article also highlights the importance of “transparency and explainability”. Without transparency, AI risks being a “black-box” system in which “responses” that affect how humans live and make decisions are made through processes that cannot be fully explained by professionals (6). During the US-Iran War, AI has again been used as a weapon to manipulate public opinion and emotions. AI was used to generate videos and images of the Iran War that attracted millions of views, and these were used to make misleading claims about the conflict. For instance, BBC detected that a video of missiles striking the city of Tel Aviv in Israel, with sounds of explosions, was AI-generated (7). Timothy Graham, a digital media expert at the Queensland University of Technology, pointed out that “the scale [of AI generated videos] is truly alarming and this war has made it impossible to ignore now” (7). Mahsa Alimardani, a researcher specialising in Iran at the Oxford Internet Institute, also claimed that “fake videos like these have a detrimental impact on people's trust in the verified information they see online and make it much harder to document real evidence” (7). Moreover, AI doesn’t stop with just misleading humans in their daily life. The increasingly military adoption of the use of AI is concerning. On the morning of 28th February 2026, American army forces struck the Shajareh Tayyebeh Primary School in Minab, a girls elementary school in southern Iran, and killed between 175 to 180 people, with most of them girls aged between 7 to 12 years old. What is the most shocking point is that the American forces blame this strike on a decision made by Claude, a chatbot by Anthropic, which selected the school as a target. In fact, as early as 2024, the US Department of War already outlined how the American forces have been adopting the AI-powered Maven Smart System to help soldiers identify and strike military targets (8, 9, 10). While supporters argue that such systems could improve efficiency, critics warn that delegating life-and-death decisions of hundreds of people should not be risked through allowing algorithms to make such decisions. The growing militarisation of AI also raises other ethical issues, such as who should take responsibility for such an action – the programmer, the commander, or AI? Ultimately, the danger of AI lies not only in its potential to “replace human brains”, but also in its ability to fabricate truth, challenging and reshaping centuries of respected philosophical beliefs. AI’s capacity to distance humans from taking moral responsibilities for their actions is also extremely concerning. Now, can you still believe your eyes and ears? What is the truth? Is truth even possible? References IBM. The History of Artificial Intelligence . IBM Think. https://www.ibm.com/think/topics/history-of-artificial-intelligence The Guardian. First Thing: White House posts digitally altered image of woman arrested after ICE protest . The Guardian. 2026. https://www.theguardian.com/us-news/2026/jan/23/first-thing-white-house-posts-digitally-altered-image-arrested-woman-ice-protest Locke J. John Locke . In: Internet Encyclopedia of Philosophy . https://iep.utm.edu/locke-kn/ Merleau-Ponty M. The Phenomenology of Perception . In: EBSCO Research Starters . https://www.ebsco.com/research-starters/literature-and-writing/phenomenology-perception-maurice-merleau-ponty Somers J. The Case That A.I. Is Thinking . The New Yorker. 2025. https://www.newyorker.com/magazine/2025/11/10/the-case-that-ai-is-thinking ( newyorker.com ) Lizzie S. Harvard Division of Continuing Education. Ethics in AI: Why It Matters . Harvard Professional & Executive Development. 2026. https://professional.dce.harvard.edu/blog/ethics-in-ai-why-it-matters/ ( professional.dce.harvard.edu ) BBC News. AI-generated Iran war videos surge as creators use new tech to cash in . BBC News. 2025. https://www.bbc.com/news/articles/ckg8wvz427vo Amaral N. The Iran war highlights the creeping use of AI in warfare . Chatham House. 2026. https://www.chathamhouse.org/2026/03/iran-war-highlights-creeping-use-ai-warfare Baker KT. AI got the blame for the Iran school bombing. The truth is far more worrying . The Guardian. 2026. https://www.theguardian.com/news/2026/mar/26/ai-got-the-blame-for-the-iran-school-bombing-the-truth-is-far-more-worrying The Week. Could the Iran war pop the AI bubble? The Week. 2026. https://theweek.com/world-news/iran-war-ai-artificial-intelligence-bubble-collapse Previous article back to Fact & Fiction Next article

< Back to Issue 10 That Protein is AI, Dude by KJ Srivastava 2 June 2026 Illustrated by Ciara Dahl Edited by Aimee Fogarty-Bennett For decades, scientists used a glowing jellyfish protein called Green Fluorescent Protein (GFP) to light up living cells. This protein emits a bright green light when exposed to UV light, and is used to visibly ‘tag’ cells for all sorts of experiments. Then, researchers used AI to generate a protein that serves the same function. And… it worked? The resulting protein, esmGFP, is so different from known natural fluorescent proteins that researchers compare the gap between them to roughly half a billion years of evolution. This protein is widely marketed as ‘AI simulating evolution’; but how much evolution is actually happening here, how does this work, and why is this being AI generated a big deal? Before this, evolution was the only protein designer we had. A jellyfish glows because evolution happened to stumble onto a protein called GFP that can absorb and emit light (1). Over millions of years, random mutations, that is, changes in DNA, slightly altered proteins. Natural selection, however, kept the versions that still worked. In the same sense, biology uses trial and error to build things, and nature keeps what works. This means every protein on earth is part of a gigantic, evolutionary family tree. Scientists can compare proteins by looking at sequence identity (2) – the percentage of amino acids that match between two proteins. Usually, closely related proteins have similar sequences and similar functions. The farther apart two proteins are evolutionarily, the more likely the chemistry fails and the protein stops functioning entirely. If you try to mutate or engineer a protein to match the function of a very different, distantly related protein, the chemistry is highly likely to fail. Because their sequences and structures have drifted too far apart, you can't easily swap parts or force them to interact without losing the necessary biochemical function! Why? Proteins are unbelievably sensitive to shape. They are made up of units called amino acids, and only work if they fold into an extremely precise and stable 3D structure. A few bad mutations can completely ruin the fold. Some examples of this in humans are cystic fibrosis, Alzheimer's, Sickle Cell Anaemia, and Huntington’s (3). The model researchers used to generate this protein is called ESM3 (4). It was trained on enormous databases of natural proteins, like a large language mode (LLM), but for biology. ChatGPT predicts plausible next words. ESM3 predicts plausible amino acids, structures and functions. Give it part of a protein sequence and it can iteratively fill in the gaps, adjusting the molecule until the chemistry and structure begin to make sense together. One of these generated proteins is esmGFP! Now this is when stuff starts getting really weird: esmGFP shares around 58% sequence identity with the closest natural fluorescent protein. In evolutionary terms, that is an enormous gap. For context, you share 60% of your DNA with a banana (5). No, I’m not lying to you. This is an astonishing number, and researchers estimate the difference could correspond to roughly half a billion years of evolution. After reading the frankly ridiculous 58% number, I immediately thought that's weird. It is, in fact, comical to assume that a machine that only has 58% of the parts of another would behave in the same way. It's the same in biology. Normally proteins that are this different are not expected to behave in the same way. Proteins are incredibly dependent on structure, and structure depends on sequence! Change too much and the entire fold usually destabilises – the protein misfolds, clumps together or just stops working. The fact that esmGFP can glow is even weirder. Forgive the ‘nerd talk’ that will take over the rest of the paragraph, but glowing for a protein is not an easy feat. GFP glows because part of the protein folds inward and creates a tiny chemical structure called a chromophore (6). Inside this pocket, three amino acids – serine, tyrosine, and glycine – react together to form a ring-like structure capable of absorbing and emitting light. In other words, the amino acids all need to be at the right angles, surrounding proteins need to stabilise the structure, the fold has to protect the chromatophore from the outside environment, and more. A model, without simulating any atoms like a physics engine, iteratively predicted something that works out. This is fascinating because the AI model appears to have internalised some of the deeper rules that connect protein sequence to behaviour – rules that even biologists still don’t fully understand. Moreover, scientists can explain how esmGFP functions chemically. They can map the fold. They can identify the chromophore. They can experimentally confirm that the protein fluoresces. But they can’t explain how artificial intelligence made it to this protein. Inside models like ESM3, there's still a major interpretability problem for scientists and biologists. The model learned from huge amounts of biological data and somehow developed an internal representation of what ‘working proteins’ look like; however, that representation is mostly hidden from us. The logic the model used to navigate this protein space and propose sequences that evolution may never have encountered at all is a black box (7). Maybe biology has a hidden schema where functional proteins follow deeper statistical or geometric rules. A schema which AI models can learn before we can clearly articulate it ourselves. Nature is an incredible engineer, but it's also deeply conservative. Evolution does not search for the best possible molecule, only whatever is good enough to survive right now. If a protein helps an organism reproduce, it stays. If not, it disappears. As a result, biology is full of accidents and compromises. Proteins can be inefficient, unstable, or bizarrely complex simply because evolution had no reason, or no viable path, to improve them further. AI hence creates a different approach to biological design. Instead of searching nature for useful molecules, researchers can generate proteins tailored to human needs: enzymes that break down plastic, proteins that capture carbon more efficiently, medicines aimed at specific targets, or even synthetic underwater adhesives inspired by mussels and barnacles (8) (find the link to this incredibly cool project here !). The deepest implication of this discovery is philosophical; life on earth is a sample size of one. This means everything we call “biology” comes from the same evolutionary tree, shaped by chance, constraint, and what was “good enough” to survive. esmGFP works, even with a sequence drifted far from known fluorescence proteins. Unsettlingly enough, maybe life isn’t defined by specific molecules at all, but by the rules that make those molecules work. Thank you for reading and I hope I could convince you that esmGFP matters beyond “AI made a glowing thing.” Check it out and play with esm yourself here ! References University of Queensland. How the jellyfish revolutionised brain science. 2020. https://qbi.uq.edu.au/brain/nature-discovery/how-jellyfish-revolutionised-brain-science RCSB Protein Data Bank. Data P. Sequence Similarity Search. 2017. https://www.rcsb.org/docs/search-and-browse/advanced-search/sequence-similarity-search Valastyan JS, Lindquist S. Mechanisms of protein-folding diseases at a glance. Disease Models & Mechanisms. 2014;7(1):9–14. doi: 10.1242/dmm.013474 EvolutionaryScale. Evolutionaryscale.ai . 2024. https://www.evolutionaryscale.ai/ Pfizer. How Genetically Related Are We to Bananas? Pfizer. 2022. https://www.pfizer.com/news/articles/how_genetically_related_are_we_to_bananas Craggs TD. Green fluorescent protein: structure, folding and chromophore maturation. Chemical Society Reviews. 2009;38(10):2865. doi: 10.1039/b903641p Kosinski M. What is black box artificial intelligence (AI)? IBM. 2024. https://www.ibm.com/think/topics/black-box-ai Liao H, Hu S, Yang H, Wang L, Tanaka S, Takigawa I, et al. Data-driven de novo design of super-adhesive hydrogels. Nature. 2025;644(8075):89–95. doi: 10.1039/b903641p Previous article back to Fact & Fiction Next article

< Back to Issue 10 Dating Isn’t Physics – Opposites Don’t Attract by Elva Assisan 2 June 2026 Illustrated by Jessica Walton Edited by Cady Jacobson The opposites attract trope has a history of being very popular in our media, appearing quite literally everywhere from Pride and Prejudice by Jane Austen to 10 Things I Hate About You by Gil Junger. Its popularity is undoubtedly a result of the conflict and passion that this dynamic brings to a narrative. Popular culture portrays high contrast couples as those with more exciting, balanced and emotionally fulfilling lives. However, while it often looks like “you bring me out of my shell” when an introvert and extrovert meet in the beginning, it often ends in arguments about going out and staying in. Despite how popular the trope is, science suggests that opposites, in fact, do not attract. The ‘Similarity Attraction Affect’ theory proposes that individuals feel more attracted to those who are similar in attitudes (1). When people encounter those with similar attitudes, they feel affective attractions. They find that their interactions are smoother and therefore more enjoyable. Even in daily life, individuals find that they have more satisfying interactions with those that they have similarities with. When another person shares similar opinions or behaviours, it creates feelings of acceptance and emotional security. This validation strengthens self-esteem and encourages emotional closeness (1), as successful long-term relationships are usually built on compatibility and mutual understanding, rather than dramatic contrast. In addition to similarity increasing feelings of acceptance due to shared values, similarity has also been found to make communication easier. Couples who share values and lifestyles generally experience fewer misunderstandings and conflicts, as they approach situations in much the same way. If two people agree on major life decisions, such as family expectations, finances, and future goals, decision making becomes less stressful (2). On the other hand, relationships with more extreme differences become more exhausting over time as more major issues have to be resolved. Montoya, Horton and Kirchner conducted a meta-analysis examining attraction and found that both actual and perceived similarity significantly increased interpersonal attraction (3). Essentially, people are more likely to enjoy spending time with those who remind them of themselves by having shared humour, hobbies, and values. Building on this, it is not just about having similarities with another person, but having a dynamic where you are invited to act on your core traits and behaviours. For example, dominant people prefer to interact with partners who invite them to be dominant, and submissive people prefer to interact with partners who invite them to be submissive. When people have different qualities which work in conversation, that same mutual understanding is found. Another example of this is having an organised partner who remembers appointments, while the spontaneous partner ensures life contains fun, instead of colour-coded spreadsheets. Individuals are also naturally drawn to environments and relationships that reinforce their self-concept and worldview (4). Indeed, the idea that opposites attract may actually originate from this notion of complementarity. Importantly, the claim that similarity matters does not mean couples have to be the exact same. Healthy relationships still require individuality, compromise, and respect for differences. Minor differences can improve relationships by encouraging personal development and preventing boredom (2). While the idea that “opposites attract” sounds romantic and makes great material for movies, psychological research suggests that similarity is usually what keeps relationships alive, particularly once the excitement wears off. Ultimately, successful relationships are less about finding your complete opposite and more about finding someone whose weirdness matches your own closely enough that neither of you end up arguing about how to load the dishwasher every night. References Byrne D. An Overview (and Underview) of Research and Theory within the Attraction Paradigm. Journal of Social and Personal Relationships . 1997; 14 (3):417–431. doi:10.1177/0265407597143008 Luo S, Klohnen EC. Assortative Mating and Marital Quality in Newlyweds: A Couple-Centered Approach. Journal of Personality and Social Psychology . 2005; 88 (2):304–326. doi:10.1037/0022-3514.88.2.304 Montoya RM, Horton RS, Kirchner J. Is actual similarity necessary for attraction? A meta-analysis of actual and perceived similarity. Journal of Social and Personal Relationships . 2008; 25 (6):889–922. doi:10.1177/0265407508096700 Dryer DC, Horowitz LM. When do opposites attract? Interpersonal complementarity versus similarity. Journal of Personality and Social Psychology . 1997; 72 (3):592–603. doi:10.1037/0022-3514.72.3.592 Previous article back to Fact & Fiction Next article

By Lily McCann Svante Pääbo: Talking to the Past By Lily McCann 23 March 2022 Edited by Caitlin Kane Illustrated by Quynh Anh Nguyen For a collection of numbers on a screen, the World Population Clock stirs a lot of emotions (1). Watch it tick on, recording a life, another life, a death, then more lives. The number — well past 8 billion now — reflects the extent of Homo sapiens’ conquest over the world. Evidence of our culture, with its complex language, society and infrastructure, is everywhere. But we seem to be the only earthly species to live in such a way, the only species to track our own numbers on a digital clock. We swarm the planet, all its continents and yet we are, essentially, alone. To challenge this isolation, scientists reach out in all directions, hoping for some kind of reflection that might shed light on who we are. Astronomers look to space; they probe the depths of the universe in search of life like our own. Others, like Svante Pääbo, look to the past. 300,000 years ago, when Homo sapiens first evolved, there was no paper, no writing, no human-like language with which to record stories, cultures, or day to day recounts. Scant traces of our ancestors are all that are left to tease us: fossilised footprints, makeshift tools, bones, grave sites. These markers are indecipherable whispers, slipping through in a hazy, broken form from a past era to our own. With a time machine or resurrection tool perhaps we could converse with the dead, but while these remain foreign to our current reality, how can we talk to the past? For Pääbo, the language of genetics is the key. Using the information carried in Palaeolithic bones, Pääbo has discovered links between present-day humans and prehistoric hominids that tell the story of our evolution and current condition. These incredible findings have earnt Pääbo the Nobel Prize for Physiology or Medicine in 2022 (2). Some of his most important achievements establishing the field of Paleogenomics include the full sequencing of the Neanderthal genome and the discovery of a whole new hominin species: the Denisovan (3, 4). But what fascinates me is his discovery of genetic interrelations between these prehistoric species and Homo sapiens themselves. Pääbo compared Neanderthal and Denisovan genetics to those of modern humans across the world. He discovered similarities and patterns that suggest a flow of genes took place between our ancestors and these hominid species: in other words, our predecessors mingled sexually with Neanderthals and Denisovans at some point in history, passing their genetics onto us as encoded evidence of this fact (5). Human genomes from Europe and Asia were most closely related to Neanderthal genomes, and Pääbo has shown 1-2% of modern non-African Homo sapiens genes are Neanderthal in origin (3). Similar patterns were observed for Denisovans, with the closest relation with modern humans from Pacific islands (6). This data exposes an intimacy between prehistoric hominids that challenges our idea of humans as a species confined to solitude. This conversation between genomes is not without implications for modern human physiology. When Homo sapiens moved into Eurasia, Denisovan and Neanderthal locals had already adapted to places in which Homo sapiens were mere tourists (7). Transfer of certain genes from local populations into the Homo sapiens line may have assisted in their survival. One example is a gene found in Denisovans that is important for survival at high altitudes and has been inherited by modern day Tibetans (8). Researching the discrepancies between modern and prehistoric genetics can thereby allow us to show the function and significance of these shared genes. It is hard to visualise the world in which Neanderthals and Homo sapiens first met. Did the scene play out as a peaceful interaction between two groups of equals? Perhaps it was more akin to the pattern of colonisation with which we are familiar in modern history. As the last species of our evolutionary branch, the Homo genus, we cannot now recreate such a meeting. However these prehistoric meetings played out, we now have evidence that Homo sapiens and local species of hominids in Eurasia communicated on the most intimate of levels. An optimist might argue that these groups of pre-humans shared a harmonious understanding that could be reproduced if humans find an analogous life form elsewhere in the future. Communication is a powerful tool after all, traversing species and millennia. Perhaps genetic insights into the past can remind us that we are not really as isolated as we might think. References Current world population [Internet]. Worldometer. 2023 [cited 2023Mar7]. Available from: https://www.worldometers.info/world-population/ Hedestam GK, Wedell A. The Nobel Prize in Physiology or Medicine 2022 [Internet]. NobelPrize.org. The Nobel Foundation; 2022 [cited 2023Mar7]. Available from: https://www.nobelprize.org/prizes/medicine/2022/advanced-information/ Green RE, Krause J, Briggs AW, Maricic T, Stenzel U, Kircher M, et al. A draft sequence of the Neandertal genome. Science. 2010May7;328(5979):710–22. Krause J, Fu Q, Good JM, Viola B, Shunkov MV, Derevianko AP, et al. The complete mitochondrial DNA genome of an unknown hominin from southern Siberia. Nature. 2010Mar24;464(7290):894–7. Villanea FA, Schraiber JG. Multiple episodes of interbreeding between Neanderthal and modern humans. Nature Ecology & Evolution. 2018May26;3(1):39–44. Reich D, Patterson N, Kircher M, Delfin F, Nandineni MR, Pugach I, et al. Denisova admixture and the first modern human dispersals into Southeast Asia and Oceania. The American Journal of Human Genetics. 2011Oct11;89(4):516–28. Rogers AR, Bohlender RJ, Huff CD. Early history of neanderthals and Denisovans. Proceedings of the National Academy of Sciences. 2017Jul7;114(37):9859–63. Huerta-Sánchez E, Jin X, Asan, Bianba Z, Peter BM, Vinckenbosch N, et al. Altitude adaptation in Tibetans caused by introgression of Denisovan-like DNA. Nature. 2014;512(7513):194–7. Previous article Next article

< Back to Issue 8 Thinking Outside the Body: The Consciousness of Slime Moulds by Jessica Walton 3 June 2025 Edited by Han Chong Illustrated by Ashlee Yeo Imagine yourself as an urban planner for Tokyo’s public transport system in 1927. Imagine mapping out the most efficient paths through dense urban sprawl, around obstructing rivers and mountains. And imagine meticulously designing the most efficient possible model, after years of study and expertise… only to find your design prowess, 83 years later, matched by a slime mould: a creature with no eyes, no head nor limbs, nor nervous system. Of course, this is anachronistic. For one, the Tokyo railroad system developed over time, not all at once. But it was designed to meet the needs of the city and maximise efficiency. Yet in 2010, when researchers exposed the slime mould Physarum polycephalum to a plate mimicking Tokyo city (with population density represented by oat flakes) it almost exactly mimicked the Tokyo railroad system (1). This became one of the most iconic slime mould experiments, ushering in a flood of research about biological urban design asking the question: Could a slime mould, or other similar organisms, map out human cities for us? But a slime mould doesn’t know what cities are. They’re single-celled organisms; they don’t understand urban planning, or public transport, or humans. They are classified as protists, largely because we’re not sure how else to categorise them, not because they’re particularly ‘protist-y.’ They have no brain and are single-celled for most of their life; so they can’t plan routes, have preferences, or make memories. Right? Except, perhaps they can. Slime moulds are extremely well-studied organisms because they exhibit precisely these behaviours. But how do they think? And what does it mean— to think ? Slime moulds have evidenced memory and learning. The protoplasm network they form is really just one huge cell that eventually develops into a plasmodium, growing and releasing spores. While plasmodial slime moulds (like P. polycephalum ) do this during reproduction, cellular slime moulds (dictyostelids) are able to aggregate together into one cell like this when food is scarce or environments are difficult (meaning they must be able to detect and evaluate if these things are true). Most slime mould behaviour is understood through cell signalling and extracellular interaction mechanisms; responding to chemical gradients using receptors along their membrane, which signal to the cells to move up the concentration gradient of a chemoattractant molecule and away from a chemorepellent. This makes sense; bacteria (like almost every other living organism) do this all the time and it’s the chief way that they make decisions . But what about memory and preferences? What about stimuli beyond the immediate detected chemicals? Slime moulds can, for example, anticipate repeated events and avoid simple traps to reach food hidden behind a U-shaped barrier (2,3). These are beyond input-to-output; something more complex must be happening. Something conscious? Thinking ? The idea of consciousness requiring complex neuronal processes is becoming rapidly outdated as we observe patterns of thinking in organisms that, according to classical definitions, really should not be able to. Using the slime mould as an example, Sims and Kiverstein (2022) argue against the ‘neurocentric’ assumption that an organism must have a brain to be cognisant. Instead, P. polycephalum is suggested to exhibit spatial memory, with cognition being suggested to sometimes include external elements (3). They showed it may undergo simple, habitual learning and hypothesised it uses an oscillation-based mechanism within the cell (3). Similarly, oscillator units along the slime mould’s extending tendrils oscillate at a higher frequency at higher concentrations of food source molecules (like some tasty glucose), signalling to the slime mould to move in that direction (4). Sims and Kiverstein (2022) also posit that the slime trail left by slime mould could function as an external memory mechanism. They found that P. polycephalum avoids slime trails as they represent places it has already been; suggesting a method of spatial memory (4). This was further proved as not a pure input-output response by showing that the avoidance response could be overridden when food is placed on or near slime trails (5). They suggest that the slime mould was able to balance multiple inputs, including oscillation levels and slime trail signals, exhibiting simple decision-making. Should we count these processes as thinking ? This topic is debated by philosophers as much as biologists. Sims and Kiverstein (2022) use the Hypothesis of Extended Cognition, being that mind sometimes extends into the environment outside of the brain and body, to argue firmly that it does count. But at the end of the day, despite understanding the chemical and electrical processes between neurons signalling and the cellular makeup of the brain, we still don’t understand how electrical signals through a series of axons make the leap to complex consciousness. Rudimentary and external cognition pathways, as seen with the slime mould, may also be an evolutionary link in the building blocks to more complex, nerve-based consciousness and decision making (3). We don’t yet understand the phenomena inside our own skulls—how can we hope to define it across all other organisms? Slime moulds clearly have something beyond simple chemical reactions. This begs the question: Aren't our own minds also fundamentally just made of simple chemical reactions? And if a slime mould is able to evaluate multiple inputs, how wonderfully complex must such processes be inside (and outside) a sea anemone, a cockroach or a cat? There’s no way to know what such a consciousness would look like or feel like to our frame of reference. When a slime mould, moving as a network around an agar plate, ‘looks up’ (or an equivalent slime mould action) and perceives unfathomable entities, how does it process that? What does the slime mould think of us? Bibliography 1. Kay R, Mattacchione A, Katrycz C, Hatton BD. Stepwise slime mould growth as a template for urban design. Sci Rep. 2022 Jan 25;12(1):1322. 2. Saigusa T, Tero A, Nakagaki T, Kuramoto Y. Amoebae Anticipate Periodic Events. Phys Rev Lett. 2008 Jan 3;100(1):018101. 3. Sims M, Kiverstein J. Externalized memory in slime mould and the extended (non-neuronal) mind. Cognitive Systems Research. 2022 Jun 1;73:26–35. 4. Reid CR, Latty T, Dussutour A, Beekman M. Slime mold uses an externalized spatial “memory” to navigate in complex environments. Proc Natl Acad Sci U S A. 2012 Oct 23;109(43):17490–4. 5. Reid CR, Beekman M, Latty T, Dussutour A. Amoeboid organism uses extracellular secretions to make smart foraging decisions. Behavioral Ecology. 2013 Jul;24(4):812–8. Previous article Next article Enigma back to