I dived deeper than ever,
feeling less and less human
in the lake’s little twilight zone,
only metres deep but fully expecting
creatures from books to shine
through the blackening water.
As the light left me,
my lungs throbbed coldly,
meaningfully,
and fear forced retreat.
I was distraught. Teasingly,
lovingly, older relatives
made things up:
An old nymph,
a known thief
this side of the lake,
had stolen my cap,
thinking it a vessel
of what I was,
hoping to gain
some of my youth.
She gripped the cap
and prayed, but the wrinkles
only continued to blossom.
Sold, the cap became the property
of goose grandees or the plaything
of drunken bears or the crown
of Canadian Crusoes
at midnight mountaintop revelries.
In my dreams, the saga went on:
after a storm, the thing spent
an autumn up a tree. The marvel
of the season, it barely escaped
the iconoclasm of beavers,
for whom the faux-fur maple leaf design
brought to mind the fur-mad butcher men
of their past. Furious,
they made beaver history
by building a dam up a tree,
but history was spoiled
by the wind.
Such was my fancy;
and when ants did donuts
on the car window,
I saw Herodotus’ giant ants
carving out the mountainsides,
and wondered why
whoever made the myths
forgot the ants
who carved Alberta
into dappled towers,
amphitheatric not just
in size and shape but more
in the way faces grin from the rock,
short-lived characters won and lost
with the changing of the light,
webbed into each other,
Siamese cast members
forming real-time Rushmores.
I was young:
a sudden distant glint
was not just a car,
but the desperate Morse
of lost Americans
imprisoned by a cabal
of cursed bipedal moose;
howls at bedtime
were not wolves
but wolf-nursed
wild men of other centuries;
the angry bear reported in the area
was not just hungry or rabid
but a woman willed into a bear
by revanchist treefolk sorcerers,
mourning her lost breasts,
fumbling to approximate
the opposable thumb,
stirring potions, buying
caps containing humanity.
As the rental car grumbled
toward S Half Diamond Ranch,
perhaps wanting to stretch our legs,
but more likely because
we understood that
the winner would
briefly become a man,
the right to jump out
and open the gate
was squabbled over
by me and my brothers
with the wide-eyed whirl
of the brawling dragonflies,
heralds of the Canadian summer.
At that age,
I often thought about
a school project where we
tagged plastic teddy bears
and mixed them back into the bowl:
the easiest way of counting.
You could capture and release
a thousand blue dragonflies
and never see one you tagged:
for they’d sped away
to join their confreres
at the noisy nodding logs,
lounging midair at happy hour,
forming secret dragonfly societies,
I supposed, loving and hating
each other before dying
after two weeks in little graves
near the shore, abdomens
thinning into twigs,
wings whitening into petals;
or expiring on the water
and drifting into the night
like war-weary Vikings;
except for the dragonfly
which died on me,
who my brothers
and I honoured
with a proper funeral:
daisies propped in the dust,
reeds looped into an arch,
a libation of pink lemonade.
***
Yesterday, I jumped into the lake
with the nostalgia of the nymph
and the recidivism of the nymph
and the perseverance of giant ants
carving mountains and the hardihood
of the faces at the Banff amphitheatre
and the frustration of the bear woman
and the ambition of bickering brothers
and the insistence of dragonflies
who won’t stop being reborn
from twigs and petal,
and, ignoring
what books say
about underwater creatures,
I dove far down and scratched
at the spot from eight years ago,
and, sure enough, rising hugely
from the ancient mud,
disturbing the quiet life
of the seaweed, creating
little avalanches over my fingers,
the long-lost maple leaf
is brought to light,
its colours restored
by the silent pillars of sun,
and the hat and I rise
smiling to the surface.
Comments Off on Decoding ChatGPT: What lies below the surface and what lies in the future?
It’s hard to believe that ChatGPT was only launched a little over a year ago. In such a short span of time, it’s completely transformed the way we study, work, and even live to some extent. Whether you’ve personally used conversational artificial intelligence or simply heard of it, its impact on the world is undeniable.
When interacting with ChatGPT, it’s easy to forget that you’re talking to a meticulously designed piece of software and not an extremely knowledgeable friend. The AI’s casual and humanistic tone, combined with its smooth integration of language nuances and contextual understanding, blurs the line between an artificially intelligent tool and a genuine conversational partner.
However, amidst all these seamless conversations, have you ever wondered how ChatGPT actually works? What lies beneath the surface of the chatbot that we’re so familiar with? Where does its intelligence come from, and how intelligent is it?
***
The AI field has a well-known ‘black box’ concept, which refers to a lack of transparency and understanding of an artificial intelligence system. Whilst an AI may be able to provide useful outputs as needed, the actual mechanisms and processes that dictate just how it produces such an output may remain opaque and unclear to users. Many scientists have warned against the “black box” AI system, as insufficient understanding of the AI’s reasoning and decision-making may lead to concerns regarding control, accountability, and bias. Thus, new precautions and efforts are being made to reduce the likelihood of ‘black box’ AIs being developed as scientists seek to better understand the systems they are producing.
In a similar logic, it is important for us, as responsible users of ChatGPT and other AI systems, to have a fundamental understanding of how these systems work. While you don’t need to have a detailed knowledge of the software, it’s useful to have a basic comprehension of this clever piece of technology and not just view it as the aforementioned mysterious ‘black box’.
***
ChatGPT was developed by OpenAI, an AI research lab founded in December 2015 by Elon Musk, Sam Altman, Greg Brockman, Ilya Sutskever, Wojciech Zaremba, and John Schulman. As an app, ChatGPT is powered by an underlying language model, which provides it with its intelligence. The ‘GPT’ in ChatGPT stands for Generative Pre-trained Transformer, which is the name of this model.
The model is constantly being updated and improved, but the current versions are GPT-3.5 Turbo and GPT-4. Interestingly, these models have been around for a while, powering other tools like Bing’s AI features, Jasper, and chatbots from across the Internet. However, ChatGPT really brought these models to the public, enabling everyone to interact with and use an AI text generator.
***
So, how do these language models work? Firstly, something important to understand is that machine learning is all about data, training and — you guessed it — learning. To put it in simple terms, the model trains by passing through data and using mathematical algorithms to “learn” from it and then fine-tuning itself so that it can be more effective. On the Internet, an almost incomprehensible amount of information and data is available. A vast amount of this data was fed to GPT to train it, and through its programming and carefully designed mathematical algorithms, the model was able to learn and then improve itself.
Interestingly, before GPT, the best AI models used ‘supervised learning’, which is when the model learns from data that is categorised and labelled with descriptions. Since the datasets provided are labelled, these models can use them to train their algorithms to recognise patterns and predict outcomes by comparing the data it has labelled itself with the ‘true’ labels provided.
However, GPT employs a technique called generative pre-training, which is when the model is given some ground rules and then fed unlabelled data. The unsupervised model is then allowed to go through the data independently, developing its own patterns and relationships in the datasets.
***
All this training creates a deep-learning neural network, which is a multi-layered and complex algorithm. The neural network is reminiscent of the brain, allowing GPT to develop intelligence and mimic human responses.
GPT’s network uses a transformer architecture, which is a specific type of network. The core concept distinguishing transformers from other network types is a process called “self-attention”, which refers to the ability of transformers to read every word in a sentence at once instead of simply reading from left to right like older networks. Transformers have this ability as they can do multiple computations in parallel. This enables GPT to focus on the most relevant words and form more complex and nuanced connections between different words in the sentence, leading to a better understanding. In addition, this ability significantly reduces training times, making AI models both faster and cheaper.
***
But how can text be understood by an AI model? The answer lies in something called “tokens”.
Tokens are simply chunks of text encoded in number form, more specifically as vectors. The closer the two vectors are, the more related the text is. The model itself maps the tokens in a vector space, which allows it to assign meaning to tokens and predict follow-on text. Thus, tokens enable the models to take in text and convert it to a form that is usable for them.
***
Before GPT was deemed suitable for public release, it underwent additional refinement. A technique called RLHF (reinforcement learning with human feedback) was used to help improve ChatGPT’s dialogue abilities. Demonstration data with expected responses for different situations was created and fed to the model to help it learn the best response to different scenarios. This more supervised approach was essential for fine-tuning and optimisation.
***
Now that we better understand how ChatGPT and other large language models work, we can start to theorise about what might lie in the future for these powerful tools. While ChatGPT and other language models are far from perfect, it is undeniable that they will continue to improve and have an increasingly influential impact on the world. New models are currently being developed with higher accuracy and faster adaptation times, enabling them to provide better responses and keep up with the rapidly changing language patterns of humans. As language models advance their dialogue systems, they will likely be incorporated into a broader range of applications.
For example, some scientists believe that ChatGPT has the potential to revolutionise education, as it can provide more personalised and interactive experiences that match specific needs. In the future, language models could be used as virtual tutors to provide instant feedback and tailored teaching. Furthermore, ChatGPT can help increase accessibility in education, giving students in remote and regional locations the same access to expert knowledge as students in metropolitan areas.
In addition, ChatGPT may also be used to enhance personal productivity by providing virtual assistant services and playing vital roles in project management. Some experts have even suggested that ChatGPT be used as a virtual therapist or counsellor in mental health treatment to provide more accessible and cost-effective help.
***
However, as with all new and exciting technologies, it is vital that we do not forget the ethical implications of ChatGPT and new artificial intelligence models. I’m not referring to the risk of ChatGPT and artificial intelligence taking over the world – although I do have a friend who starts every ChatGPT conversation with ‘Hey babe’ as he wants ChatGPT to spare him if it does one day decide to end humanity. Instead, I’m referring to issues related to bias and the potential misuse of these powerful technological tools.
As ChatGPT and other AIs become more advanced, the possibilities for misuse also grow. If not properly monitored, these open-source models could be used to spread misinformation or portray certain opinions. Regarding the issue of bias, ChatGPT’s output is dependent on its input data. And so, if the input data for ChatGPT contains certain biases, then the output will reflect them. Thus, it’s essential to ensure that open-source models remain objective and trustworthy sources of information, as they have the potential to shape public opinion. Other issues, such as privacy and the ethical considerations related to ChatGPT replacing human workers, must also be carefully evaluated.
It is vital to ensure that as technology and language models like ChatGPT advance, our laws and regulations do not fall behind. Ultimately, these new laws and regulations must be built upon understanding, which is why it is so important not to just let new artificial intelligence technologies become a black box. We need to dive below the surface in order to properly predict what is to come.
At any given moment in time, there are countless ripples travelling through spacetime, traversing the very fabric of our universe. These ripples are known as gravitational waves, and were first predicted by Albert Einstein in 1916 in his general theory of relativity.
Almost a century later in 2015, direct evidence of gravitational waves was finally obtained when the Advanced LIGO (Laser Interferometer Gravitational-wave Observatory) detectors, located in Hanford, Washington and Livingston, Louisiana, USA detected the long-awaited signal.
The 0.2 second audible signal, which was described to resemble the “chirp” of a bird, was actually the product of a black hole collision. This event occurred more than 1 billion years ago. Two massive black holes merged into one, warping the fabric of spacetime and sending ripples through the universe which were eventually detected on Earth as tiny vibrations.
The successful LIGO experiment sent its own waves through the science community. The search for gravitational waves had consisted of decades of unrelenting hard work by over a thousand physicists around the globe and billions of dollars of investment, so the news was both extremely exciting and highly anticipated.
Now you might be wondering what is next for gravitational wave research. After all, the amazing detection of gravitational waves was already accomplished in 2015.
However, in reality, the exploration of gravitational waves has only just begun as researchers continue to use LIGO and a growing network of detectors around the world (e.g. LIGO-Virgo-KAGRA collaboration) to investigate the nature of our universe. In exciting news, the ANU, as part of the LIGO Scientific Collaboration (LSC), will play a central role in this global venture.
Last year I was lucky enough to get the chance to interview Dr Lilli Sun and Dr Jennie Wright, astrophysicists from ANU’s Centre for Gravitational Astrophysics to gain some further insight into the current field of gravitational wave research and ANU’s new LIGO remote control room.
Firstly, could you explain what a gravitational wave is in simple terms?
Jennie: A gravitational wave is a sort of stretching and squeezing of spacetime itself. When we have mass in the universe, it causes spacetime to curve, as explained in the theory of General Relativity. A gravitational wave is like a ripple instead of just a curve that stays still.
Lilli: You can also think of an analogy like a water wave – for example, dropping a stone in water and then seeing ripples spreading out. When we have something very heavy, like black holes that collide, they trigger those ripples in spacetime.
What are your specific research focuses and what are you currently working on?
Lilli: I do mostly astrophysics; using gravitational waves to study black holes, neutron stars, and even searching for dark matter. I do a lot of data analysis to see what the gravitational-wave signals tell us – e.g. whether it tells us that Einstein and his general theory of relativity is right or if there is something unexpected.
One of my projects is about searching for dark matter particles using gravitational waves – we don’t know if they exist or not, but analysing gravitational wave signatures is one possible way to look for them. I also work a bit on detectors, working with instrumentalists like Jennie.
Jennie: What I work on is somewhat related. I’m an instrumentalist as Lilli said, so I’m an experimental physicist and my job has two parts. Half of my time I spend at ANU, working on technologies that we can use to improve gravitational wave detectors of the future. We’re making them more sensitive so they can see further out into the universe and also can see a wider range of signal frequencies. And so, I work on developing technology that basically tries to distinguish things near the detector that look like gravitational wave sources, but actually aren’t – like a truck breaking near the detector, or just air moving near it.
The other part of my job is to help improve the current detectors. Since we use light in the gravitational wave detector to measure the stretching and squeezing of spacetime, we want to have as much light in there as possible. But, because mirrors and optical systems aren’t perfect, we sometimes lose quite a lot of light, so I look at those diagnostic measurements to try to figure out where we’re losing light.
Now that gravitational waves have already been detected, what is next for the field of gravitational wave research?
Lilli: There are many aspects actually: the 2015 discovery was only the beginning. The 2015 event for two black holes colliding into each other and the famous 2017 event for a two neutron star collision are very highlighted events, but now we are collecting many more of them including some special systems. The large number of detections will bring us important information of the population.
There are other types of gravitational waves. For example, we are looking for very faint gravitational waves from a single spinning neutron star. Neutron stars are not perfect spheres, so when they rotate they can generate very weak gravitational waves, which is something we are searching for. Another example is to probe dark matter using gravitational waves. So, we need more sensitive detectors and more of them in the network.
Moving onto the ANU remote control room, what exactly is a control room and how specifically would the remote control room work?
Jennie: So, a control room is usually a room you have next to a lab with an experiment in it: usually one that needs to be in either a really clean environment, or a slightly dangerous environment. So, you set all the physical parts of it up, so you can obtain electronic signals through to your control room that tell you what is happening. And then you can do all the data-taking and analysis from that control room.
In LIGO, they have the control rooms right next to the detector because they don’t want to be walking around next to the detector while it’s running, as they might introduce noise to it. They also have a whole bank of screens which decipher how each sub-system is working.
About the remote control room: whilst we don’t have a gravitational wave detector in Australia, many Australian scientists have been involved in gravitational wave detection from the start, and so this allows us to participate in improving the detector remotely. So, you can see on some of the screens here, I have a read-out of the different sub-systems and if they’re working correctly. For example, green tells us that they’re observing data and red tells us that they’re down and need to be fixed. And this is all in real time.
That’s really useful, because before we had this, we just had the little screen on our computers, and you had to try to view everything simultaneously and it was quite difficult. My colleagues and I will also occasionally do shifts when the detector is running, because we might have to call up people in other countries. If there’s an exciting gravitational wave event, we sometimes need to announce things to other astronomers, so they can point their telescopes to certain parts of the sky.
Lilli: Although it’s a ‘remote’ control room, you can still control some of the sub-systems of the detector. It’s just that we need to be very careful, especially during observation. There will be someone in charge in the real control room, and we can collaborate with them. The advantage of having the remote control room is that it makes it much easier for Australian colleagues, as we are not close to the detector, but we can read off the real-time information in a much more convenient way, on the other side of the world.
So, the detector isn’t always on all the time?
Jennie: There’s a trade-off between the physicists who work on improving it, and the astronomers who want to collect data using it. If you improve the sensitivity, you’re more likely to see really exciting events we haven’t seen before. But if you increase the time the detector is on for, you’re also more likely to see more events. So, there are sometimes periods where we’re not touching the detector for around 18 months, and periods where there is no data collection for a year, and maintenance and upgrading occurs.
From a bigger perspective, what role is Australia and ANU playing in the further research of gravitational waves?
Lilli: Australia is one of the major collaborators in the large international LIGO-VIRGO-KAGRA collaboration. There is a large group here working on gravitational wave astrophysics and detector science. These days, Australian scientists also want to propose and work towards building an Australian detector in the future, which is pretty exciting.
Right now, we are also thinking about the next generation detectors – like what kind of design and technology is needed that can give us a one-order of magnitude increase in sensitivity, which can get us much deeper into the universe. Australian colleagues are working on both the existing science of gravitational waves, but also the future.
Jennie: In the past, Australia has developed sub-systems which are now used in the detector, contributing mirrors for example. Also, Lilli is in charge of the calibration group for LIGO, and that’s just an example, but we have a lot of staff in Australia who are leading some aspect of the LIGO scientific collaboration’s research. We’ve also been instrumental in the design of something called the Squeezer which is used in LIGO to improve its sensitivity, making the detectors the quantum instruments that they are.
Lilli: Regarding astrophysics and data analysis, there are quite a few large groups from different Australian universities within OzGrav working on the data being collected these days. A lot of studies are carried out in Australia, but we also work very closely with international colleagues.
What are some benefits of these large-scale projects, e.g. do they help bring countries closer together and encourage international cooperation?
Lilli: I think yes, definitely. These days, it’s getting difficult to do small narrow research projects by yourself. With projects like gravitational wave detectors, you have large instruments, and that involves many different aspects: you need to work with engineers on different sub-systems, theoretical physicists to understand how the astrophysics work, software engineers and data analysts for dealing with huge amounts of data, and also astronomers who do different kinds of follow-up observations. All these people are playing important roles, and they come from different countries, different parts of the world. Close collaboration is critical.
Jennie: I think it’s really useful to have these big projects, because any falling out between countries can get in the way. It also definitely broadened my horizons, as I’m from Scotland, which isn’t as multicultural. Without science, I definitely wouldn’t have travelled and experienced different cultures as much.
Last question, what’s your advice for students looking to get into this field or just interested in your research?
Lilli: I think there are lots of chances for students to talk to us and do small projects. If they’re really interested there are lots of ways to get into the field. We do lots of summer/winter projects and we also teach undergraduate courses, where we discuss gravitational waves at a more basic level. Many students are interested, and we have extended discussions and they come to us for small projects or Honours and end up staying for PhD.
Jennie: I think definitely the best way is just to email someone who works in the fields. Academics love students being interested in their research, otherwise they wouldn’t be working at a university and teaching. I’m really happy whenever a student asks me, and I think that’s how I got involved in the field too.
Lilli: Yes, definitely talk to academics and lecturers in the field if you’re interested.
Jennie: And I think that’s the same in all areas of science as well, people are super keen to tell you about their research, you just have to ask them.
Photograph of some of the screens in the control room.
Dr Jennie Wright (left) and Dr Lilli Sun (right) in the remote control room.
A huge thank you to Dr Lilli Sun and Dr Jennie Wright for taking the time to do an interview and for so generously sharing their knowledge.
Kneel with me, smell here: dirt turned red from white.
Look up at the open canopy, shadows
You made for us. It’s the hellfire of night
Where the ouroboros ends and rage grows.
I inherited this anger chest-to-chest with my mother,
As we watched the hillside, the eagles, burn–
Listening to the cries of ancestors
Holding hot leaden breath, waiting our turn.
Call me an animal? I’ll grow canines.
Didn’t your forefathers tell you, warn you:
Don’t bring a dog leash to a genocide.
I want to hollow out your chest, fill you
With the scorching ash of my matriarchs–
Them ones you insist you left in the past.
I often hear Western scholars preach about the ouroboros, without knowing how it feels to lose a beginning. Black Summer is the story of the displacement of my family. At 16, I wanted nothing more than to see somebody else suffer for what happened to us. I wished that the boiling force inside me — that one everybody kept calling ‘teenage angst’ — could cheat time and blow apart the hull of the first ship to touch these shores. These days, my matriarchs tell me how proud they are, that I choose to unleash my rage one day at a time.
Let yourself be whole now
With your hands in the Earth
Your feet in the crystal shallows
Your core grounded and unshakeable
Let yourself be swallowed
Taken entirely
By the evanescent tide of you as complete
With no gleam or hesitation
Saunter on
To the greatest motion with no name
Where you do not have the answers
Only the tools
To carve and make space
For your wholeness
To breathe
Originally published in Woroni Vol. 72 Issue 2 ‘To Be Confirmed’
Think your name would look good in print? Woroni is always open for submissions. Email write@woroni.com.au with a pitch or draft. You can find more info on submitting here.
In 1977, NASA launched two Voyager spacecrafts, the first of their kind ever to leave the solar system and venture into the vast, infinite space beyond. Within each of these spacecraft is a gold-plated record, a relic meant to convey to any other life-form it might encounter the entire human experience. On this record are images ranging from simple geometric shapes to complex, abstract works of art. And there are also 90 minutes of audio.
90 minutes.
90 minutes to capture all the sounds of the human species. How do you capture something so complex in sounds that might be incomprehensible to any other organism? How do you capture human emotion and convey it to something that might not even experience it?
Despite this monumental task, Carl Sagan and his team attempted to capture our sounds, our languages, and our music onto the record. Those 90 minutes are an intricate tapestry of audio from across time and space. There is a message from the UN General Secretary and greetings in 55 different languages. There is Mozart, and there is Beethoven. There are the fundamentals of sound itself, and there are those who have supposedly mastered it. Yet amongst these iconic, universal pieces of music is a blues song by a relatively unknown artist, Blind Willie Johnson. His song, ‘Dark was the Night, Cold was the Ground’, nestles amongst giants to capture one of the most integral emotions of what it means to be human, or as Carl Sagan put it, “cosmic loneliness.”
We know very little about Blind Willie Johnson. So little that there exists only one confirmed picture of him. We know he was born in 1897 in Texas and that his mother passed away shortly after. As a child, we know his stepmother blinded him by throwing lye into his eyes.
We know he then turned to playing the guitar, travelling around the state, preaching the Christian faith of which he was a devout follower. Johnson lived in poverty his entire life and struggled until the very end. When his house burned down in 1945, he had nowhere to go. So, he slept in the charred ruins where his bed once lay. Here, he contracted a disease; sources differ on whether it was pneumonia or malarial fever. When brought to the hospital, he was refused treatment. He died shortly after. His wife Angeline alleges that he was denied treatment due to his disability, while other sources say it was because he was black.
Within his discography is that very song on the Voyager Golden Record, “Dark was the Night, Cold was the Ground.” Yet it is not Johnson’s own composition. It is his three-minute adaptation of a song layered with history and meaning – a hymn sung on slave plantations, in black churches by preachers, and at funerals in the American South. Johnson’s rendition does not sing the lyrics in English or any other language. Instead, he moans in an anguish that captures and echoes the history of the song, of his own life, and the collective suffering of both. A history that is conveyed in three minutes.
It is a song that echoes our deepest vulnerability, transcending any language to convey to the great beyond the insular depths of our sorrow and loneliness. That is the song’s thesis when considered in isolation, but when we peer behind the notes into the stories that have shaped it, we see perhaps a more prescient idea of what it represents – persistence.
Our species has faced great horrors and resisted great evil to survive. We bear those scars and share them as a collective. Willie Johnson endured a profoundly racist country that not only considered him unequal to those he performed for but also looked down upon him for his disability.
Yet he persisted.
A man who had sight cruelly taken away from him created and captured a testament to our perseverance. Our sorrow and the collective loneliness that pervades our existence now hurtles through the vast expanses of space, seeing more of our universe than our species ever has.
The Voyager Golden Record was designed with longevity in mind and will likely outlast human civilisation. Our existence, however, is inherently ephemeral. We are collections of stardust that dance in sorrow for the duration of our lifespan, capable of great kindness and destruction, only to return to dust when our dance ends. But through our creativity and passion, we can create what transcends our own mortality into great, immortalised art.
In however many years, if ever, should the Voyager Golden Record meet any other civilisation, it might witness that very testament to our perseverance. Or it might never do so and keep exploring the universe in the darkest of nights, and the coldest of spaces, forever cosmically lonely.
Originally published in Woroni Vol. 72 Issue 6 ‘Dive’
Think your name would look good in print? Woroni is always open for submissions. Email write@woroni.com.au with a pitch or draft. You can find more info on submitting here.
If you search ‘pandas’ on Youtube, you will find hundreds of videos with titles such as AWW SO CUTE!!! BABY PANDAS Playing with Zookeeper or Panda Funny Moment Videos Compilation. Instead of attending to my growing pile of uni work, I like to watch these adorable creatures cause havoc, tumble and roll around, and menace their keepers. They struggle to walk around without tripping on flat grass, are frightened by their own farts, and always inexplicably find a way to fall off literally anything. It’s like they’re trying to go extinct.
It made me wonder – how on earth did evolution fashion one of the most extinction-able animals possible?
The evolutionary biologist, Stephen J Gould, was thinking the same thing. He probably wasn’t watching Youtube in the 1980s but his book, The Panda’s Thumb, was inspired by boyhood trips to the zoo. Gould observed that pandas were capable of deftly stripping the leaves from bamboo stalks with the assistance of an apparently ‘flexible thumb’. This puzzled the young Gould who had learned in school that a supposed hallmark of primate superiority was the development of an opposable thumb. With this, chimps and the like could hold onto things to make the tools that differentiated them from other animals.
Yet the panda wields a seemingly identical structure. Upon closer inspection, the panda’s thumb isn’t actually a thumb at all. When you look at its paw, you would see that it actually has six digits, not five. So did the panda develop an extra finger? Not quite. The panda’s ‘thumb’ is actually an extension of a bone that we also find in humans, namely the radial sesamoid. This pseudo-thumb is also pretty terrible at its job. It is clumsy and characterised by a painfully limited range of movement. A first-year engineering student could have done a better job of designing an alternative.
Yet there are numerous examples of ‘poorly’ designed structures in nature. Gould argues in his book, however, that these embarrassing feats of biological engineering are more compelling evidence for evolution than the perfectly suited structures that are typically used in your biology textbook.
Briefly, evolution, as put forward in Charles Darwin’s seminal work The Origin of the Species, is a process of adaptation by natural selection. In other words, an organism featuring traits that are favourable for its environment is more likely to survive, have many offspring, and pass on its genes.
A common misunderstanding, however, is that an animal chooses to survive better. A cheetah cannot choose to have faster offspring. More accurately, a mutation, or several, that allow for stronger muscles arises spontaneously in one cub of a litter. That fast, young cheetah is more likely to catch prey and, in turn, more likely to produce offspring which will inherit this mutation and be fast little cheetahs and so on. Organisms, thus, adapt to their environment through almost a process of iterative testing to allow for a specific trait to dominate a population and eventually become a primary characteristic of that species.
Yet within this paradigm we still see so many supposedly poor examples of adaptation. How can we reconcile the panda’s simple pseudo-thumb with the almost divine excellence of the evolutionary process?
We might actually observe that the panda’s pathetic excuse of a thumb fits neatly into Darwin’s theory. A marvellous thumb does not arise spontaneously. Natural selection has to work with what it’s got. In a way it’s in the name – nature selects traits that are already in a population. At some point in the panda’s ancestry, a hypertrophic radial sesamoid in a random panda turned out to just get the job done and there was no real need for a structure with extra bells and whistles.
We can see examples of poor adaptations in ourselves too. Before we dive into these, it’s first important to understand that evolution is characterised by a never-ending struggle between organism and environment. As the environment changes, the organism tries to catch up. Sometimes there’s a bit of a lag which has led to a number of distinctly modern ailments as humans change their environment with incredible momentum. A clue to these organism-environment mismatches can be seen in conditions whose prevalence is growing with astonishing speed.
As an example, autoimmune conditions such as inflammatory bowel disease, lupus, and arthritis are thought to be increasing in prevalence by a dizzying 3–9% a year. With no obvious changes in our genetic makeup within the past few decades, the culprit seems to be a change in our environment. In this case it might be linked to the consumption of fast-food. This stark jump in the evolutionary timeline from fibre-rich whole foods to burgers containing more sugar than protein is thought to have altered our gut microbiome which might trigger autoimmune diseases. This is just one of a number of examples where the human body and our modern lifestyles appear to be mismatched.
Perhaps our view of the panda’s supposed evolutionary inferiority is conceited. Why would they need an opposable thumb when their little stump will do? Why do they need to drive cars or run around really quickly when they can just look cute and let us bring the food to them? The most convincing argument for evolution is perhaps not the existence of the perfect animal, but rather the many examples of imperfections as a result of working with what they’ve got. Just like that uni assignment you’re supposed to be working on right now, nature sometimes realises that a mediocre job is still a finished job. As they definitely don’t say – while the panda works hard to go extinct, natural selection works harder.
Originally published in Woroni Vol.72 Issue 1 ‘Evolution’
Evolution occurs when animals adapt to better live in their environment. Climate change and the Anthropocene are changes to our environment. However, because they are happening so fast, we cannot evolve through our usual means of mutation. To survive, and, in many ways, to thrive, in a new era, we will have to evolve deliberately and collectively.
Often, when we talk about our Anthropocenic future, we speak with cynicism. We talk about how doomed we are, about how much we and the planet will lose. The signposts of our times seem to point in only two directions: what needs to be done by 2050, and the hellscape that awaits us afterwards. Fundamentally, a good portion of us seem to have lost a lot of hope. This is understandable. In many ways, it is a logical viewpoint. We are one of the most individualistic societies to ever exist, having to confront a problem caused by our collective actions and which can only be solved by our collective actions. If we were not living it, it would be fantastically ironic.
Increasingly though, people are understanding that this fatalism and odd schadenfreude is what hamstrings us. Proposals like the Green New Deal are solutions-orientated, but, in their wholesale view and in their intersectionality, they give us a better vision of the future. They give a third way of looking forward. The debate now is moving away from questions of needing to evolve, to the question of how do we evolve? What traits do we need to better suit the coming century?
In a word, systems. In two words, systems thinking. Just as individualism plagues us, so too does an obsession with taking ecological and economic cycles and processes and trying to make a graph out of them. The four lines required to make a supply and demand diagram are some of the most damaging you can draw. Not because they are inaccurate, but because of how much they leave out. If we’re trapped in Plato’s cave, then these bivariate models are the shadows on the wall. The fire is approaching the market as embedded in a broader social and environmental context. Oxford economist, Kate Ratworth, has attempted to create another way of visualising a single market: wherein the market is taken as a system, with supply and demand being feedback loops, not linear processes. This market also has a clear limit – environmental sustainability.
What we should evolve into is an understanding of our world as composed of systems. These systems have multiple components which replace the traditional independent variable, but each component is a keystone – if removed, the system teeters dangerously. The classic example we’d be familiar with is an ecosystem. Remove a producer organism, like plants, and the system crumbles, but remove also apex predators and herbivore populations explode unsustainably. When we attempt to break down the world into phenomenon Y as a cause of X, we stress the dependence of Y on X, but in doing so, we lose the interdependence of these two variables within a broader system.
When we reduce the world into models, choices are made about what to exclude and include. We exclude what we deem irrelevant which, as history warns us, is a dangerous game to play. Climate change challenges economics because it pushes and prods for putting the environment front and centre of these models. Otherwise, reality and economics will flee into the distance growing further and further apart, a phenomenon seen today in the celebration of economic growth built off future environmental collapse.
Systems thinking doesn’t stop with the economy. Just as we fail to embed the economy into other systems like the environment and society, so too do we fail to view ourselves as agents in a larger, broader system. This is not simply a criticism of the neoliberal “There are individual men and women and there are families…” It is about reworking the conception of humans as distinct from their natural environment. The West has long sat on this principle of othering; creating binaries and hierarchies of value. Race, gender and sexuality have all been catalogued and reduced to the accepted ‘status quo’ and the rejected other, to either be feared, patronised, or forced out. We do the same thing with the environment. We erect picket fences to distinguish between where we and our lawns end, and where the ‘wild’ begins. But we cannot be separated from our ecosystem; the idea of a human is meaningless without the global and local environment in which they live. Understanding this irrevocable connection is one of the most crucial steps in evolving into the Anthropocene and the reality of climate change.
Much of this is nothing new. It is the West that struggles with this. Many other cultures incorporate eco-centrism into their views, especially First Nations people and other Indigenous cultures around the world. For once, the West needs to take a backseat. Successful climate action will be paired with justice and sovereignty for Indigenous peoples.
One of the most dangerous myths of climate change is that we have no choices left. Whatever happens in the next two decades, it will be a series of decisions made by our society. Some will be undemocratic, made by elites in backrooms, while others may not even be presented as choices, only as unfortunate necessities. But with every step, through action or inaction, we will be choosing what we evolve into, we will force ourselves to adapt to the new landscape. To paraphrase Chomsky, it is better to choose optimism over despair, to choose through the ballot, but also to choose by approaching life as complex and vulnerable systems, needing to be comprehensively understood, with no factor excluded. By evolving towards a system outlook, we take a step to evolving into not just the new era, but into something better.
Originally published in Woroni Vol.72 Issue 1 ‘Evolution’
Science is frequently touted as an apolitical endeavour. It transcends social forces and trends, rising above the emotional and petty squabbling of politics in pursuit of a beautiful and pure object we call the ‘truth.’
At first glance this seems noble enough. Science should operate for the purpose of obtaining knowledge, not serving a political goal. Knowledge that has been acquired for the sake of knowledge has inadvertently made our lives better too. The serendipitous discovery of penicillin is a prime example. Scientific knowledge should not see geographical or political boundaries, it exists on a plane above the vicissitudes of human drama, waiting to be discovered and unravelled.
This idealism is perhaps largely a product of privilege. Science has never been apolitical, nor perhaps should it be. As much as we might like it to be a pure, unpolluted thing – science can be used to hurt, especially when we are not trying to. For example, scientists studying Darwinian evolution probably did not consider the implications of some of their work in propelling biological determinism which galvanised the eugenics movement and theories of racial superiority. For them, their work was only logically ‘following the science’ and avoiding these discussions elevated them from accusations of prejudiced thinking. Yet such inaction had consequences.
We like to think that science should only be conducted to discover the truth. Perhaps we might want to pause and think about what the consequences of those truths could be. This is not a defence of censorship, but rather an abnegation of the supposed lack of moral responsibility scientists are privileged with. In other words, perhaps scientists must factor the social and ethical implications of their work and ensure their findings are not used for harm. In the same vein, science might need to consider what it is not looking for and how that, too, can cause harm.
Medical research is a field that can be most visibly tied to historical harms to people through supposed a-politicisation. For example, individuals that are from underrepresented ethnic groups, low-socioeconomic status or are women, have repeatedly been the subjects of systemic biases in medicine. Ironically, we could suppose, conscious attempts to be ‘race-blind’ or apolitical have caused considerable harm. These areas are, however, notoriously difficult to navigate. Willful negligence of these factors as important considerations in research do measurably hurt those belonging to these identities in science. The race-blind classification of disease-causing variants in large-scale genetic screens ultimately has major consequences for ethnic minorities and excludes them from potentially lifesaving medical interventions. A putative disease-causing mutation could be erroneously identified as harmless when only examined in a dataset of European individuals. This is due to overlooking the complex interplay of a particular mutation and one’s genetic background which impacts the design of algorithms that are being increasingly used to assess risk for conditions such as heart disease.
An apolitical approach would champion being ‘race-blind,’ but this could be more harmful because it demonstrates a willingness to ignore the historic oppression and inequities to which these groups have been subjected. In fairness, it is absurdly difficult for any researcher to consider the almost endless potential consequences of their work. It is critical nonetheless to examine how one’s research could be used to do harm. Overall, we dangerously assume that science must operate within a political vacuum. This, in a way, is a political decision itself.
Originally published in Woroni Vol.72 Issue 1 ‘Evolution’
A girl imagines she could jump.
Despite a window in place,
and four metres of space.
Still, she imagines.
Above her,
the noise is –
Leaking.
Through his head
phones he can hear –
it.
It’s not quite a buzz –
he can hear it even though
it’s not quite a buzz and
He’s wearing his headphones and
it’s leaking.
The girl adjacent wants you to
Please excuse the pun.
As she speaks, the room
cannot find the pun.
Yet,
The room does not exist
but for his eyes,
Thinks a boy as he
lets his hand fall,
between their two chairs.
The man in the corner pulls at his hair
because he is looking at the girl looking
at the window
imagining she could jump.
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