I S S U E 4
S
T
E Z
M I
D E C E M B E R 2 0 1 9
N
E
A science, technology, engineering, and mathematics zine by students for students
ISSUE 4 Contents
1 The Revolutions of Johannes Kepler Sophia
3
Personalityi n Non-human Animals Amelia
2
The Viability Of Mammoth De-Extinction Holly
4 How FIRST Changed My Life Alexandra
5 How STEM Could Improve the Quality of Developing Countries Joanna
6 Underlying Algorithms: The Decision-Makers You Never Considered Madison
THE REVOLUTIONS OF
JOHANNES KEPLER “If I have seen further, it is because I have stood on the shoulders of giants.” Isaac Newton
Written by Sophia Holmes Designed by Katie Lau
All scientists build off of the work of others, and Johannes Kepler was no exception. What made his discoveries so powerful and unique, however, was the manner in which he set about finding them. Kepler not only revolutionised astronomy as we know it, but he also played a significant part in shaping the scientific method itself. His work was unprecedented in its own right, but it becomes almost unbelievably so when one considers the context in which he lived.
Kepler began as an assistant to Tycho Brahe, the official imperial astronomer to the Danish royal family in the 1500s. Brahe was a master of quantitative observation, and he gathered massive volumes of data from his royal observatory, carefully watching celestial bodies and tracking their movement. It was only upon Brahe’s death in 1601 that Kepler finally gained full access to this archive of information and was able to use it for his own study.
Unlike Brahe, Kepler was a heliocentrist and believed that the planets orbit around the sun. However, he struggled while working with the Copernican model, which incorrectly assumed that the planets orbit the sun in a perfect circle. He spent much time attempting to work with regular polygons and certain three-dimensional solids to perfect a geometric relationship for the universe- and here is where we begin to see the initial emergence of Kepler’s greatness.
In the sixteenth and seventeenth centuries, science could be a rather inaccurate process. Often, if a scientist came up with a solution to a question that was deemed “good enough”, they would publish it anyways, even if their data did not exactly seem to line up. Kepler refused to do the same. Despite spending countless hours rearranging his prisms and shapes to fit his initial theory, he found that the formula he was working with simply was not precise enough.
Just like that, he discarded it.
Perhaps it seems obvious now, but for his time period, this was a major breakthrough. Kepler’s dedication to the integrity of his results set a precedent for science and made him one of the first champions of empiricism in the field - the theory that all knowledge is derived from what we can observe and record. He long praised the powers of experience and always “felt the need to seek observational support for his model of the Universe”, a determination which caused him to continually toss out old ideas in favor of newer, more accurate ones. By his willingness to reject a long-believed and long-studied theory that the planets have a circular orbit, he was set on the path towards becoming one of the greatest astronomers of all time. When his ideas did not match his data, he did not stretch the numbers or attempt to say he was correct anyways. He simply went back to the drawing board, determined to find a better solution. With the help of Brahe’s data, Kepler eventually realized that the planets revolve around the Sun in an elliptical orbit - not the perfect circle that had previously been assumed. He was then able to formulate his three famous laws, forever earning him a major place in the history of astronomy. Kepler’s laws essentially define planetary motion and have been so accurate, that even to this day, they have only required infinitesimally small adjustments. And this is the other reason why Kepler’s work was so astonishing. He worked only with naked-eye astronomy - without the use of telescopes which hadn’t been invented yet.
Gravity had also been yet to be understood, and it was in fact Kepler’s discoveries that helped spur Sir Isaac Newton to formulate his gravitational laws. Despite lacking these tools, despite lacking fundamental knowledge of one of the most important ideas of physics, Kepler still managed to wrap up the motion of the planets into three simple, beautifully elegant laws, linked together with a single mathematical equation. To say the man was ahead of his time is an understatement. Johannes Kepler brought about not only a new understanding of the revolution of the planets, but he also brought about a revolution of his own. The scientific method, inspired by Kepler’s example, became more refined and eventually reached the process of “trial, error, rethink the problem” that Kepler stood by. His dedication to precision and discovering a true solution to his long-pondered problem helped him to set a new standard for scientists everywhere, contributing far more to modern research methods than only his laws of planetary motion. His diligence was well rewarded, and his brilliant discovery has certainly earned him a permanent place among scientific giants.
WORKS CITED 9Di Liscia, Daniel A. “Johannes Kepler.” Stanford Encyclopedia of Philosophy, Stanford University, 21 May 2015, plato.stanford.edu/entries/kepler/#Emp. Gould, Alan. “Johannes Kepler: His Life, His Laws and Times.” NASA, NASA, 24 Sept. 2016, www.nasa.gov/kepler/education/johannes. “Johannes Kepler.” Wikipedia, Wikimedia Foundation, 8 Nov. 2019, en.wikipedia.org/wiki/Johannes_Kepler. “Planetary Motion: The History of an Idea That Launched the Scientific Revolution.” NASA, NASA, earthobservatory.nasa.gov/features/OrbitsHistory/page2.php. Redd, Nola Taylor. “Johannes Kepler: Unlocking the Secrets of Planetary Motion.” Space.com, Space, 20 Nov. 2017, www.space.com/15787johannes-kepler.html. Images: Diagram of Kepler's Theory of Planetary Motion. Digital Image. Universe Today. 11 February 2010, https://en.wikipedia.org/wiki/Johannes_Kepler Portrait of Johannes Kepler. Digital Image. Wikipedia. 9 September 2001, https://en.wikipedia.org/wiki/Johannes_Kepler
The diversity of the phenomena of nature is so great, and the treasures hidden in the heavens so rich, precisely in order that the human mind shall never be lacking in fresh nourishment. ~Johannes Kepler
Grey Glacier, Chile. Photo by Ciprian Morar on Unsplash
T H E
V I A B I L I T Y
O F
MAMMOTH D E - E X T I N C T I O N
WRITTEN BY: HOLY VAUX D E S I G N E D
B Y :
E M I L Y
Y U
Glaciar Perito Moreno, El Calafate, Argentina. Photo by AgustĂn Lautaro on Unsplash
The woolly mammoth is a creature held in our minds like a distant memory. With tremendous tusks, thick fur and a life traversing the tundra, their existence sounds almost fictional, yet the woolly mammoth sat on the cusp of modern humanity.
4000 years ago, the last woolly mammoth walked on this Earth. After facing a population bottleneck, loss of habitat and a change in climate, the continental woolly mammoth populations were extirpated. Yet woolly mammoths served a key ecological purpose, fulfilling a role as ecosystem engineers that contributed to maintaining the mammoth steppe; a once extensive biome characterised by its dry, cold climate and herbaceous-level plants. The woolly mammoths prevented succession from occurring in the mammoth steppe through grazing and trampling which prevented trees and shrubs from growing. The lack of vegetation surface area ensured heat reflection, reducing ground temperatures and maintaining permafrost layers. However, as the mammoth population declined, other organisms were unable to fulfill their functions and the vast majority of mammoth steppe was lost. This subsequently caused the permafrost to be threatened. 4000 years on, as the global climate becomes more humid and temperatures increase, areas which the mammoths once occupied are becoming more vulnerable to the release of greenhouse gases via the melting permafrost. As permafrost thaws, a global warming feedback loop occurs: permafrost melts and the carbon stored within it is released, leading to global temperature increases and in turn more permafrost thaw, creating a cycle of rising temperatures. Woolly mammoths were the creatures that once prevented this loop thousands of years prior, and without an alternative organism to overtake this role, we are losing permafrost at a rapid rate. This is predicted to cause irreversible ecological damage.
In order to prevent the melting
the Pyrenean Ibex was de-extinct for a few
permafrost from having a negative impact on
minutes before the clone died from lung
the planet, scientists have looked towards
failure. Despite the inability to create a long-
creating solutions. The large scale removal of
surviving individual through cloning, the
trees needed to prevent permafrost melt is
method has shown plausibility. However,
currently underway in areas of Siberia,
issues do still arise when applying cloning to
however the process is slow and lacks
the concept of mammoth de-extinction. The
financial support. As an alternative, de-
Pyrenean Ibex was able to be cloned due to
extincting the woolly mammoth has been
the well-preserved DNA from skin biopsies, a
presented as a possible method to prevent
luxury less attainable for mammoths. Even
permafrost thaw from rapid climate change.
the most well-preserved woolly mammoth
However, de-extincting the woolly mammoth
remains have degenerated DNA. Furthermore,
presents scientific and ethical issues, raising
cloning is still a flawed science; cloned
the question: is it truly the most viable method
individuals often riddled with defects that
to preserve the imperil permafrost?
lead to a short and painful life. Cloning techniques are progressing, though they are
De-extinction may seem utterly
currently infeasible.Ultimately, cloning is an
incomprehensible at first - how is it possible to
unlikely method to solve the issue of the de-
bring a species back from the dead? One must
extinction of the woolly mammoth.
consider the fact that it has already been accomplished (albeit briefly) through cloning.
George Church, a scientist at Harvard
The Pyrenean Ibex; a species of wild goat,
University, is at the forefront of mammoth
possesses the morbid achievement of being
de-extinction. Church’s research attempts to
the only animal to become extinct twice. In
de-extinct woolly mammoths through genome
2000, the Pyrenean Ibex became extinct;
editing. This is a technique in which loci on
through skin biopsies collected prior to
the genome of the woolly mammoths closest
extinction, DNA was extracted and cloning
living relative, the Asian elephant, are
occurred. After several failed attempts, the
replaced with phenotypic woolly mammoth
experiment was eventually successful, and
traits, such as hair and ear size, to create
woolly mammoth-elephant hybrid. This hybrid would occupy the same function that woolly mammoths once did, therefore aiding in permafrost protection by reducing tree cover, preventing succession and reducing ground heat absorption. Church is confident in his methodology, expressing that he believes a viable hybrid will be created very soon. However, this is not a true de-extinction, though the woolly mammoth-elephant hybrid would aid in creating the mammoth steppe and present conservation benefits globally. Genome editing does not make a true woolly mammoth, but it presents a viable option for preventing permafrost thaw and acting as a sustainable conservation technique which is the fundamental goal of woolly mammoth deextinction.
In a some-what similar fashion to Church’s genome editing attempts, back-
Atlanta Botanical Gardens very own Mammoth Atlanta Botanical Garden, Atlanta, United States Photo by Christopher Alvarenga on Unsplash
breeding is a potential method of creating a woolly-mammoth from the Asian elephant. Back-breeding is a method used by the Heck
therefore there is no combination of traits that
Brother in the 1920s. they attempted de-
could be selectively bred to create an elephant
extinction
with the capabilities of surviving in the tundra
by using aurochs. the descendent
species were selectively bred into a cattle breed known as ‘Heck cattle’. However, Heck
climate. Woolly mammoth de-extinction is
cattle have no relation to aurochs and cattle
ultimately a plausibility, with Church’s work on
show large morphological differences. This
genome editing at the forefront. De-extinction
indicates the difficulties that back-breeding
is not a fanciful dream conjured by mammoth
has. The true behavioural and physiological
fanatics; it is a thought out solution for
traits of extinct species are not fully known,
economic and ecological issues that face our
therefore it is difficult to identify the goal
planet. Unfortunately, feasibility and ethical
traits to back-breed to. Although the Heck
dilemmas may hinder the chance for this
brothers were unable to recreate the auroch
natural conservation method. IUCN identified
through back-breeding, their work was highly
that approximately 27,000 threatened extant
rudimentary due their misunderstanding and
species still need protection, therefore wasting
simplification of the method and of aurochs
valuable resources on de-extinction projects
themselves. Despite the scientific
could be inhibiting successful ecological
developments since the 1920s, back-breeding
change. Furthermore, climate change is already
is fundamentally likely to be an unattainable
at our door, and reaching current conservation
method to recreate the woolly mammoth due
goals should be prioritised,. The de-extincion of
to the loss of morphological traits in their
the woolly mammoth may still be attainable,
living relatives. The distinctive hair that
though we must ultimately concentrate on
allowed woolly mammoths to survive in cold
immediately solving the issues which our planet
onditions is unseen in the Asian elephant,
is currently facing.
BIIB BL LO OG GR RA APPH HYY B
Ann Ran, F., Hsu, P. D., Wright, J., Agarwala, V., Scott, D. A. & Zhang, F. (2013) Genome engineering using the CRISPR-Cas9 system. Nature Protocols, 8(11), 2281-2308. Dabney, J., Meyer, M. & Pääbo, S. (2013) Ancient DNA Damage. Cold Spring Harbor Perspectives in Biology, 5(7), a012567. Folch, J., Cocero, M. J., Chesné, P., Alabart, J.L., Domínguez, V., Cognié, Y., Roche, A., Fernández-Árias, A., Martí, J. I., Sánchez, P., Echegoyen, E., Beckers, J. F., Sánchez Bonastre, A. & Vignon, X. (2009) First birth of an animal from an extinct subspecies (Capra pyrenaica pyrenaica) by cloning. Theriogenology, 71(6), 1026-1034. Gamborg, C. (2014) What’s so special about reconstructing a mammoth? Ethics of breeding and biotechnology in re-creating extinct species. In Oksanen, M. & Siipi, H. (eds) The Ethics of Animal Re-creation and Modification. Basingstoke, United Kingdom: Palgrave Macmillan, 60-76. IUCN (2019) IUCN Red List of Threatened Species. Available online: https://www.iucn.org/iucn-red-list-threatenedspecies-test-single-page [Accessed 08/04/2019] Shapiro, B. (2015) Mammoth 2.0: will genome engineering resurrect extinct species? Genome Biology, 16(228). Available online: https://genomebiology.biomedcentral.com/article s/10.1186/s13059-015-0800-4 [Accessed 06/04/2019]. Shapiro, B. (2017). Pathways to de-extinction: how close can we get to resurrection of an extinct species? Functional Ecology, 31(5), 996-1002.van Vuure, C. (2005) Retracing the aurochs: history, morphology and ecology of an extinct wild ox. Sofia, Bulgaria: Pensoft Publishers. Zimov, S. A., Zimov, N. S. & Chapin III, F. S. (2012) The past and future of the mammoth steppe ecosystem. In Louys, J. (ed) Paleontology in Ecology and Conservation. Berlin: Springer-Verlag, 193-225.
Why do I Relate To My Cat So Much?
WRITTEN BY: AMELIA EDITED BY: YAFIAH
UHZ ELLEBASI YB DENGISED
Personality in Animals
As I walk into my study my cat purrs happily in greeting from his curled position on the sofa, stretching his limbs and turning his head to the side as I, unable to resist, come to give him a pet. He closes his eyes in satisfaction as I scratch his chin and behind his ears, soft purrs resonating through his fur. It wasn’t until I had owned three cats that I began to notice not-so-subtle differences between them. This one is a Mumma’s boy – he loves it when I give him attention, but he doesn’t like strangers and isn’t fond of being cuddled. In contrast, my other cat adores being picked up and held, she loves new people and weirdly their feet. She will happily sit in your lap and sometimes take a nap with you if she gets comfy enough. The youngest of the three, a little ginger rescue, my dad describes as “polite”. He sits patiently and lets you know when he wants something, he has a different meow for when he's hungry and when he wants to go outside, and he appreciates a scratch on his cheek or behind his ear. He’s not fond of being held, but he’ll tolerate it for a short while.
It seems obvious to me that my cats have personalities and feelings of their own. They even appear to bear a grudge against me when I leave home for long periods of time. But, to what extent am I just anthropomorphising them, and is it just domestic animals that appear to have personalities? The study of animal personalities focuses on individual differences in behaviour that are shown to be consistent across time and context (Wolf & Weissing, 2012). This is often difficult to measure and experimentally test, but it definitely appears that individual animals vary in terms of individual behavioural traits. Animal personality cannot be studied in exactly the same way as we study human personality, but we can use some of the same methods to attempt to validly and reliably test it. In 2013, Carter, Feeney, Marshall, Cowlishaw, and Heinsohn (2013) published a review assessing the methodology commonly used in animal personality research, suggesting an integrative framework based on current methods used in behavioural ecology and those used in the social sciences. Current problems in the field include having multiple tests for one trait or having one test for multiple traits (Carter et al., 2013), which makes it difficult to discern what is actually being measured.
Regardless, there is a large pool of research on personality across a wide range of taxa. We might be inclined to believe that something as specific and complex as personality would be restricted to humans and related taxa, but evidence for personality extends beyond mammalian groups (Bell & Stamps, 2004; Garamszegi, Eens, & Török, 2008; Huntingford, 1976; Riechert & Hedrick, 1993). Organisms we might never have considered to have personality appear to display within-group variation in many behavioural traits, and this appears to have consequences for how they interact with others and learn new information. The personality of different baboons appears to be linked to their social learning (Carter, Marshall, Heinsohn, & Cowlishaw, 2014), additionally Parsus major dispersal appears to affected by their individual personality type (Dingemanse, Both, Van Noordwijk, Rutten, & Drent, 2003) and this is at least partly heritable (Drent, Oers, & Noordwijk, 2003).
So, not only do non-human animals appear to have personalities, this also affects their behaviour in predictable ways and may be inherited. But why is this the case? From an evolutionary perspective, the existence of personality is difficult to explain because it is unclear what benefits it could confer (Bell, 2007). Additionally, natural selection should act to remove variation in a population by “selecting for” the best strategy and “removing” unfavourable ones, where the best strategy would be adapting behaviour flexibly depending on the situation. However, we see behavioural variation in many groups, and it is not clear how this variation is maintained. Wolf, Van Doorn, Leimar, and Weissing (2007) explain how personality can be adaptive as it is likely related to the fitness trade-offs individuals encounter within their lifetime. This specifically concerns investment in future reproduction, as opposed to the decision to reproduce now. Individuals investing into their future reproduction have more to lose, and so are likely to be adopt more risk-averse personality types (Wolf et al., 2007).
Considering the evidence and theories, when I describe the personality of my cats, I do not really talk about them in terms of “boldness”, “exploratory behaviour”, “aggressiveness”, or other behavioural traits often used to describe animal personality. To many other people and I, personality feels like something more than a series of correlated behavioural traits that determine how an organism reacts to a certain situation. We infer feeling from other animals that are close to us in a similar way we infer feelings from other humans. We read their body language, we can tell when they are angry and want to be left alone (whether we choose to leave them alone or not is another matter) or when they are happy to see us. But when we seriously study animal personalities, we have to take ourselves out of the equation. Our main frame of reference is other people, other human beings, and what personality means in that context. To say anything meaningful about it, we have to strip it down to what is measurable and remove ourselves from our inherent anthropogenic stance. Finally, while examining the adaptive argument for personality in animals, another question arises. Did personality in humans evolve for the same reason? To us, it seems much more complex than that, as we tend to think of ourselves as “higher” organisms. However, we cannot forget that we too are animals and were once and still are subject to the same evolutionary pressures as the rest of life on Earth.
References Bell, A. M. (2007). Animal personalities. Nature, 447(7144), 539-540. doi:10.1038/447539a Bell, A. M., & Stamps, J. A. (2004). Development of behavioural differences between individuals and populations of sticklebacks, Gasterosteus aculeatus. Animal Behaviour, 68(6), 1339-1348. doi:10.1016/j.anbehav.2004.05.007 Carter, A. J., Feeney, W. E., Marshall, H. H., Cowlishaw, G., & Heinsohn, R. (2013). Animal personality: what are behavioural ecologists measuring? Biological Reviews, 88(2), 465-475. doi:10.1111/brv.12007 Carter, A. J., Marshall, H. H., Heinsohn, R., & Cowlishaw, G. (2014). Personality predicts the propensity for social learning in a wild primate. Peerj, 2. doi:ARTN e283 10.7717/peerj.283 Dingemanse, N. J., Both, C., Van Noordwijk, A. J., Rutten, A. L., & Drent, P. J. (2003). Natal dispersal and personalities in great tits ( Parus major ). Proceedings of the Royal Society of London. Series B: Biological Sciences, 270(1516), 741-747. doi:10.1098/rspb.2002.2300 Drent, P. J., Oers, K. V., & Noordwijk, A. J. V. (2003). Realized heritability of personalities in the great tit ( Parus major ). Proceedings of the Royal Society of London. Series B: Biological Sciences, 270(1510), 45-51. doi:10.1098/rspb.2002.2168 Garamszegi, L. Z., Eens, M., & Tรถrรถk, J. (2008). Birds Reveal their Personality when Singing. PLoS ONE, 3(7), e2647. doi:10.1371/journal.pone.0002647 Huntingford, F. A. (1976). The relationship between anti-predator behaviour and aggression among conspecifics in the three-spined stickleback, Gasterosteus Aculeatus. 24(2), 245-260. doi:10.1016/s0003-3472(76)80034-6 Riechert, S. E., & Hedrick, A. V. (1993). A test for correlations among fitness-linked behavioural traits in the spider Agelenopsis aperta (Araneae, Agelenidae). Animal Behaviour, 46(4), 669-675. doi:10.1006/anbe.1993.1243 Wolf, M., Van Doorn, G. S., Leimar, O., & Weissing, F. J. (2007). Life-history trade-offs favour the evolution of animal personalities. Nature, 447(7144), 581-584. doi:10.1038/nature05835 Wolf, M., & Weissing, F. J. (2012). Animal personalities: consequences for ecology and evolution. Trends in Ecology & Evolution, 27(8), 452-461. doi:10.1016/j.tree.2012.05.001
HOW FIRST CHANGED MY LIFE ALEXANDRA
FIRST:FOR
INSPIRATION
RECOGNITION AND
OF
AND
SCIENCE
TECHNOLOGY
- HOW FIRST CHANGED MY LIFE -
Computer assisted design prototype
For Inspiration and Recognition of Science and Technology (FIRST) is an international youth organization that operates robotics and research programs. FIRST has two major values: coopetition, a word they invented combining ‘competition’ and ‘cooperation’, and gracious professionalism. FIRST is the only competition that I have seen participants want others to do better; teams constantly offer genuine help, and this is never seen in other sports.
How did you hear about first?
What did that look like for you?
FIRST made its way into my life in the
During my sophomore year, I joined
seventh grade when I joined FIRST Lego
the FIRST Robotics Competition Team.
League (FLL), a club that ignited my
Knowing nothing about mechatronics
passion for science and construction. As
or programming but excited to learn,
an FLL member, I built and programmed Lego Mindstorms robots while developing solutions for world problems. Five years later, I am still involved in FLL as a mentor guiding three different teams. I want children to grasp the importance of these activities and the effect on the development and prosperity of our country. Through FLL, children are encouraged to think of viable solutions for some of the world’s most pressing problems.
the team took me in with open arms. The following year, I became software captain where I provided leadership to the Programming Sub-Team working on our robot's JAVA code and helped with the Computer Assisted Design (CAD) prototype. During that year, I worked hard to include more girls into the team as there were five times the number of boys; noticing the lack of girls joining our team, I organized several workshops to encourage girls to participate.
So what's your story like now? This year, I became General Captain where I am responsible for organizing all outreach activities, managing the progress of sub-teams, and working on the development of this season's robot. Thanks to my participation in the Robotics Team, I realized the potential I have for problemsolving and developing engineering-related solutions. With my team, I use my skills and creativity to build and code. As General Captain, I have learned from successful engineers how to excel in math and science in a country where these subjects are not prioritized, break barriers for girls in STEM, and inspire girls to join robotics.
I WANT CHILDREN TO GRASP THE IMPORTANCE OF THESE ACTIVITIES AND THE EFFECT ON THE DEVELOPMENT AND PROSPERITY OF OUR COUNTRY.
Lego mindstorms
HOW STEM COULD IMPROVE THE QUALITY OF DEVELOPING COUNTRIES. BY JOANNA PEGG
DESIGNED BY: JULIA FENG EDITED BY: HOLLY
01
The economy, our general well-being and everything in between, are all dependent on science, technology, engineering, and math - but what happens when a country doesn't have access to these? Poverty in its extremes consists of a lack of well engineered infrastructure (or dictatoresque tied aid projects), collapsing industries, a decline in health care advances and standards, negative economic growth and a lack of innovation. This problem is exasperated in developing areas where equity no longer means equity, and people's access to and interaction with key institutions are shaped by their wealth, gender, and the power they represent in society. These less economically developed countries (LEDCs) are often helped through foreign aid projects, but with the introduction of STEM education the country would be empowered to become self-sufficient and no longer dependent on aid. Although sustainable development goals have been put in place to increase wellbeing and decrease poverty, more emphasis needs to be placed on STEM and its role in improving the quality of developing countries. The economic stability of a country is dependent on the countries ability to innovate and produce new goods that are needed by the population or are in demand for exportation. In many LEDCs, industries lack development or are only developed through overseas development assistance (ODA) from other countries. If an ODA is in the form of tied aid, workers are sourced from the donor country which decreases local employment and therefore reduces local government profits. Industries act as an injection into the economy, providing an income for workers, profit for the government and the production of goods and services, however, for an industry to be created, personnel has to be trained and specialized. Once an industry is created, the country must then be able to sustain the industry itself which requires STEM-qualified workers to do so. However, a country with a poor economy has less circulation of resources which is worsened by prevalent hierarchical and gender gaps, meaning that for such a country to improve its economy and subsequently decrease poverty then STEM education is needed. STEM education would allow a country to develop effective industries, make a profit, innovate, create connections and raise the living standard of its people. Quality of life is measured by the human development index (HDI) which is an overview of the life expectancy, education and standard of living within a country. In LEDCs, the HDI ranges from 0.699 (medium human development) to 0.354 (very low human development). People that reside in areas of below substantial HDI scores go without basic infrastructure and engineering: living in their own waste, slum-like housing, having no access to facilities or sanitation, and dirty water. When help is provided to LEDCs by foreign countries it can often be detrimental, with forgein countries implanting infrastructure projects in an attempt to build an aid dependent country, business relations, and to provide employment for workers of the donor country. All without understanding how local people live.
In low HDI countries, there have been cases of teenagers constructing basic infrastructure, such as wells, to increase the standard of living, showing a motivation for improvement that would benefit from STEM education. Providing STEM education would provide a workforce of skilled locals who could provide infrastructure and industries that boost the economy without disrupting local life. Through STEM education, toilets, healthcare facilities, water pumps and more could all be constructed allowing a country to become self sufficient, stopping the continuous cycle of poverty and increasing overall wellbeing. Polio, malaria, diarrhea and pneumonia each result in a monumental number of fatalities in developing countries. Comparatively, the presence of these diseases in developed countries is significantly lower due to immunisation which averts 2 to 3 million deaths a year. Currently, immunisation treatments in LEDs are inadequate as they are usually administered through foreign agencies which often fail to immunize mass amounts of children, aren't fully equipped or aren't granted passage by local militia groups or local governments. These inequalities cause many fatalities; the highly populated areas in these developing countries are unsanitary and lacking considerate infrastructure,meaning that the spread of disease occurs easily.
02
.
03 In combination with the scarcity of full time doctors and clinics, inability to travel for extensive periods of time to see a doctor nor the money to pay for treatment, further inhibits development. By increasing industry through STEM education, factories and warehouses would also increase, allowing vaccinations to be stored and manufactured in developing countries which prevents them from becoming aid dependent. Aid could then be administered by locals, providing more reassurance to the child receiving the vaccine. With STEM education, shortages of immunization supplies will not affect how many children in the area will be vaccinated, and no more children will die from preventable diseases. Furthermore, residential areas will become more sanitary and waste efficient, helping to stop the spread of diseases and the quality of life. The developing country no longer needs to rely on donor companies for aid to treat it's impaired, and through its own trained professionals is self sufficient. Education in STEM fields is necessary in developing countries as it governs the pillars of a working society. Education is necessary in the creation of a successful economy, steadfast industries, developments in engineering, satisfactory infrastructure and advanced health care. Establishing these further leads to innovation, reduced unemployment rates, substantial wages and improved sanitation. Providing STEM education induces the shift from an aid dependent country to one of self sufficiency through a workforce that is qualified, employed and able to do what was once provided through foriegn aid. Innovation through the utilisation of the knowledge based off STEM centred education contributes benefits to many aspects of society, ultimately increasing overall wellbeing and powering the world into an age in which spatial inequality is lessened.
UNDERLYING ALGORITHMS: THE DECISIONMAKERS YOU NEVER CONSIDERED
WRITTEN BY: MADISON RAMOS D E S I G N E D
B Y :
E M I L Y
Y U
An algorithm can broadly be defined as “a step-by-step procedure for solving a problem or accomplishing some end.” In technological terms, an algorithm is the set of rules a computer will follow to reach a particular goal. And they are, in quite a literal sense, everywhere. Whether or not you personally have considered their role is a different story. Allow me to run you through a media-centric sliver of our lives. Bored, we contemplate an array of apps before finally settling on one. Let’s say, this time, we select Instagram. After catching up on your feed, where do you go? One click away: the Explore Page. Take a minute not only to scroll through these images but to look at the greyed out, unsuspecting line of text under every post’s description. “Based on photos you liked.” “Based on photos you saved.” “Based on videos you have watched.” Figure 1. An Instagram Explore Post
The Instagram Explore Page is your personal content-discovery hub. That, of course, should lead you to consider one thing: How is it that Instagram is able to personalize your Explore page?
RAMOS | PAGE 2
Instagram tells you, roughly, how each post makes it onto your Explore page. They even allow you to “See Fewer Posts Like This” by modifying their decisions. But, the true reality of what’s going on “behind the scenes” is an algorithm; Instagram is able to compile your various actions (e.g. likes, saves, and views) to generate a customized page comprised of content closely related to that which you’ve previously expressed interest in. This is all done to entice you and lead you to further interact with the app.
Cumulatively, Instagram is able to employ artificial intelligence and machine learning to amass data concerning the uses and employ said data towards the development of an “Explore Page” curated to their perceived interests ("Instagram Explore Page”, 2019). This curation of content is, clearly, not limited to Instagram’s usage. Similar algorithms are constantly in use courtesy of countless companies. For instance, consider Google’s Search algorithm. Without delving into it too much, here’s a quotation directly from Google:
“To give you the most useful information, Search algorithms look at many factors, including the words of your query, relevance and usability of pages, expertise of sources, and your location and settings. The weight applied to each factor varies depending on the nature of your query—for example, the freshness of the content plays a bigger role in answering queries about current news topics than it does about dictionary definitions” ("How Search algorithms work").
Then there’s the infamous YouTube Algorithm, known for confusing both the masses and seasoned content creators. Everyone is well-acquainted with YouTube’s recommendations, but we must all wonder: What does it take to get recommended?
Figure 2. YouTube Recommendations RAMOS | PAGE 3
At one point, a high view count was all it took to climb your way up into a user’s recommendation page. Then, there were alterations that consider watch time, view duration, and likes. In 2016, there was a literal paper, “Deep Neural Networks for YouTube Recommendations,” released on an improved algorithm. Today, it only continues to change ("The Infamous YouTube Algorithm, Explained"). .
Before we move further into our discussion about Algorithms, let’s talk about Artificial Intelligence, Machine Learning, and Deep Learning. People enjoy throwing these terms around, but they’re crucial to developing an understanding of the majority of today’s effective algorithms Artificial Intelligence (AI) is considered “the broad science of mimicking human abilities.” Machine Learning (ML) is, subsequently, a particular “subset of AI that trains a machine how to learn.” ML employs various methods (e.g. neural networks) to uncover insights in data without having explicit instructions concerning what to consider and conclude. Deep Learning is a branch of ML that employs massive neural networks with countless layers of processing units (Thompson, Li, & Bolen). Through deep learning, one is able to learn about complex patterns found in large subsets of data (e.g. learning which YouTube videos to recommend). If you’d like a brief, pictorial understanding of the most popular machine learning algorithms, I find this mind map to be rather useful:
Figure 3. Popular Machine Learning Algorithms (Brownlee, 2019) RAMOS | PAGE 4
However, since neural networks (NN) were touched upon the most, I will briefly describe them. Basically, neural networks are inspired by literal neural networks: your brain. They are made up of interconnected units (i.e. ‘neurons’) that respond to external input and relay information amongst one another. Data is processed multiple times as the network works to locate connections and form conclusions concerning the data.
Now, let’s get back into the algorithms. Where can we find them outside of social and search-related media? Well, for one, the Criminal Justice System. AI is widespread throughout this system, and pretrial risk assessment algorithms are used in most US states. Algorithms will take into account “socioeconomic status, family background, neighborhood crime, employment status, and other factors” alongside the crime at hand, to “predict future behavior by defendants and incarcerated persons” and an individual's overall “criminal risk” ("Algorithms in the Criminal Justice System").
Figure 4. “Trained a Neural Net” Photo Credit: xkcd
Generally, jurisdictions have been known to use one of the following: Correctional Offender Management Profiling for Alternative Sanctions (COMPAS), Public Safety Assessment (PSA), or Level of Service Inventory Revised (LSI-R). These algorithms range in the specific factors they consider, but most consider a combination of criminal history and personal characteristics.
Despite general accuracy, these algorithms can also be dubbed unreliable. A study done on the bias of the COMPAS recidivism (i.e. the tendency of a criminal to re-offend) algorithm found that the risk of black defendants was overestimated and that of white defendants underestimated (Larson, Angwin, Kirchner, & Mattu, 2019). There was even a court case in which a defendant took a case to the Supreme Court of Wisconsin, claiming that the use of a COMPAS risk assessment in sentencing was a violation of their due process right; however, the court found that the usage of a COMPAS risk assessment is not a violation of a defendant's due process right ("State v. Loomis"). Algorithms such as COMPAS remain in use. At the end of the day, AI and ML have allowed for the development of countless algorithms that underlie the software we use in our daily lives. Outside of deciding what ads to recommend you, these algorithms tackle serious realities such as criminal risk.
UNDERLYING ALGORITHMS
RAMOS | PAGE 5
Challenge yourself to recognize these underlying algorithms. Consider them. Understand them. Appreciate them. Criticize them. Maybe, one day, even take part in creating them.
WORKS CITED Brownlee, J. (2019, September 3). A Tour of Machine Learning Algorithms. Retrieved from https://machinelearningmastery.com/a-tour-of-machine-learning-algorithms/. EPIC - Algorithms in the Criminal Justice System: Pre-Trial Risk Assessment Tools. (n.d.). Retrieved from https://epic.org/algorithmic-transparency/crim-justice/. How Search algorithms work. (n.d.). Retrieved from https://www.google.com/search/howsearch works/algorithms/. Instagram Explore Page (Algorithms & more - 2019 Update). (2019, August 7). Retrieved from https://wolfglobal.org/instagram-explore-page/. Algorithm. (n.d.). Retrieved from https://www.merriam-webster.com/dictionary/algorithm.Larson, J., Angwin, J., Kirchner, L., & Mattu, S. (2019, March 9). How We Analyzed the COMPAS Recidivism Algorithm. Retrieved from https://www.propublica.org /article/how-we-analyzed-the-compas-recidivism-algorithm. State v. Loomis. (n.d.). Retrieved from https://law.justia.com/cases/wisconsin/supreme-court/2016 /2015ap000157-cr.html. The Infamous YouTube Algorithm, Explained. (n.d.). Retrieved from https://www.allgirlithm.org /blog/the-infamous-youtube-algorithm-explained. Thompson, W., Li, H., & Bolen, A. (n.d.). Artificial intelligence, machine learning, deep learning and more. Retrieved from https://www.sas.com/en_us/insights/articles/big-data/artificial-intelligencemachine-learning-deep-learning-and-beyond.html#/.
G S N I M H Y T L I R R E O G D N AL RAMOS | PAGE 6
S R E ED K A ER M - SID N O ON I S I C C E ER D E EV H T UN YO
EDITOR IN CHIEF ASHIMA MUGIBUR RAGHMAN
HEAD OF DESIGN A.F
HEAD OF MARKETING ISABELLE ZHU
WRITERS SOPHIA HOLMES, ALEXANDRA DALMU, CELINE VAZQUEZ, HOLLY VAUX, JOANNA PEGG, AMELIA KIRK, MADISON RAMOS
DESIGNERS ISABELLE ZHU, KATIE LAU, EMILY YU, JULIA FENG, JOANNA PEGG
EDITORS ANDREA GONZALEZ, IMAAN HUSSAIN, YAFIA ALI, HOLLY VAUX
MARKETING DEPARTMENT ASHIMA M.R., ANDREA GONZALEZ, EMILY YU, JULIA FENG, SABAH IMRAN
CREDITS ASHIMA M.R., ANDREA GONZALEZ, EMILY YU, JULIA FENG, SABAH IMRAN
MARKETING DEPARTMENT ANDREA GONZALEZ, IMAAN HUSSAIN, YAFIA ALI, HOLLY VAUX
EDITORS ISABELLE ZHU, KATIE LAU, EMILY YU, JULIA FENG, JOANNA PEGG
DESIGNERS SOPHIA HOLMES, ALEXANDRA DALMU, CELINE VAZQUEZ, HOLLY VAUX, JOANNA PEGG, AMELIA KIRK, MADISON RAMOS
WRITERS ISABELLE ZHU
HEAD OF MARKETING A.F
HEAD OF DESIGN ASHIMA MUGIBUR RAGHMAN
EDITOR IN CHIEF
See you in the next issue.
cover design by A.F.