SYNTHIFY
August Science Technology, and Society The Digital Decider College Admissions: Is AI used to read applications? Sonar -The Innovation from Nature Your Information, My Data Misinformation and Fake News The World of Genetic Engineering: Modifying Entities Artificial Intelligence: Mental Tracking Impact Who Owns Our DNA? Smart Cities, But Sicker People?
SYNTHIFY
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THE DIGITAL DECIDER :HOW ALGORITHMS DECIDE WHAT YOU SEE… AND WHAT YOU NEVER WILL -ANU O
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COLLEGE ADMISSIONS, IS AI USED TO READ APPLICATIONS? :ROLE OF AI IN ADMISSIONS -MARLEE MEI
SONAR -THE INNOVATION FROM NATURE -ASHLEY
YOUR INFORMATION, MY DATA -LUANA HUA
MISINFORMATION AND FAKE NEWS :HOW TECHNOLOGY HAS CHANGED THE SPREAD OF FALSE INFORMATION -MAGGIE ZHANG
THE WORLD OF GENETIC ENGINEERING: MODIFYING ENTITIES -TISTA BHATIA
ARTIFICIAL INTELLIGENCE: MENTAL TRACKING IMPACT IMPACT OF AI CODING ASSISTANTS ON NOVICE CODE OUTPUT:
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-DANE BAES
WHO OWNS OUR DNA? THE ETHICS OF CONSUMER GENETIC TESTING IN THE AGE OF GENOMICS:
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-ESTHER TYRNAUER
SMART CITIES, BUT SICKER PEOPLE? THE INSIDIOUS COST OF URBAN PROGRESS: -MEHREEN MUZAFAR
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THE DIGITAL DECIDER HOW ALGORITHMS DECIDE WHAT YOU SEE… AND WHAT YOU NEVER WILL
Anu O
I
t's Friday night, and you're just about to head to bed—when a notification pops up on your screen: A new TikTok video! For the first five minutes you feel like you're just scrolling through the same old For You Page… But little did you know that you're actually participating in a modern phenomenon called algorithmic curation, where your information isn't just filtered but deliberately engineered to control your very worldview. Welcome to the world of doomscrolling. Quite the fitting name, right?
The Architecture of Engagement Have you ever wondered how quickly checking a single video or Short can translate into endless hours of mindless scrolling? This cycle points less to an individual lack of control to get off the phone, but more towards intentional algorithmic curation. Platform recommendation engines have one simple goal: maximize user engagement. These engines are tailored to prioritize highly arousing content over civic value to keep users on their platforms. To keep your eyes on the screen for as long as possible, predictive engagement—views, clicks, shares—will naturally amplify certain emotions such as outrage, reshaping public interactions. Since the algorithm is driven by interaction, it will naturally favor outrage and controversy over nuanced discussion (Gillespie, 2014). Consequently, this digital design creates invisible boundaries in our experiences online. Users come into contact with “filter bubbles” that systemically exclude other worldviews from their feeds (Pariser, 2011). Things like opposing viewpoints and conflicting information are silently filtered from the feed, making it appear like most of the world agrees with highly curated pieces of reality. By doing so, daily media interaction becomes less like a digital meeting place to learn new perspectives and serves to increase social polarization.
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Capitalistic Surveillance In the digital world, user behavioral data is extracted, categorized, and predicted to manipulate human behavior. Each online interaction—search histories, location trackers, or online purchases— is categorized and converted into a digital profile. Way beyond social media algorithms, other algorithms determine employment opportunities, access to housing, and credit scoring, playing a significant role in reinforcing systemic social biases (O’Neil, 2016). Today's digital citizenship, such as applying for a job or even navigating banking services, requires people to give over their personal data, creating a society where privacy is not viewed as a basic right, but a luxury (Zuboff, 2019). Consequently, this leads to the normalization of the loss of autonomy, where your behavior is actively monitored and controlled for a corporation’s profit.
Invisible Censorship As moderation systems continue to govern online interactions, two problems need to be considered about such content moderation: what remains unchecked, spreading rapid viral information vs. what gets suppressed through “shadow banning.” When such platforms operate behind the scenes, users lose the ability to constitute the truth, transforming what was simply a scroll into government bodies that hold no democratic accountability (Noble, 2018).
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This reinforces a fundamental principle in Science, Technology, and Society (STS): Technology is not neutral, ever. Algorithms do not objectively or passively make decisions but actively reflect the economic and social values of the corporations allowing them (Winner, 1980). When these platforms are in control of what content can be accessed or hidden, corporate profit is quietly prioritized over public benefit, as views that challenge their financial interests are ultimately silenced.
Conclusion: Reclaiming Agency Online The algorithm’s puppet strings does far more than personalize your daily feed; it reshapes entire public discourse, decides who gets access to economic necessities, and allows certain voices while hiding others. We must acknowledge that algorithms are not neutral but are tailored models designed to monetize your behavioral data and attention. To protect the human agency of the right to access all media of truth, the future STS is relying on you—yes, you—and your active personal awareness. By reclaiming our worldviews, we must first design algorithms with stronger data privacy safeguards that prioritize digital conscious transparency over curated feeds.
August 29, 2026 / Anu O / mon.ch4rie@gmail.com 08
COLLEGE ADMISSIONS: IS AI USED TO READ APPLICATIONS? THE ROLE OF AI IN ADMISSIONS
Marlee Mei
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lass of 2027! With the Common App open, many students are already going back to school shopping or have already started the new school semester; it can be a very stressful time filled with a mix of anxiety and excitement. Between meeting your new teachers, making new friends, and class schedules, seniors also have the added pressure of continuing or finalizing college applications. For many seniors, this upcoming semester is one of the most demanding, as they need to stay on top of their academics while meeting deadlines.
There have been concerns that many colleges are using software to detect plagiarism and AI. How exactly is AI being used? First and foremost, AI can flag missing materials and and checking applications completeness. It can track common data sets, GPA trends, and course rigor to compare students within their own schools, across cities, and across different school systems. A major concern was algorithm bias, which compared past admitted students to prospective applications. Prospective students may be penalized for not having backgrounds similar to those of previously successful applicants, such as course rigor, extracurriculars, and prestigious awards.
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Schools like Virginia Tech are implementing AI tools; Juan Espinoza from enrollment management praises AI for being consistent. This fall, the school is debuting an AI-powered essay reader, which will help them get admission offers to students and make sorting through thousands of applications more efficient. Many colleges rely on these assistive technologies to review transcripts, and some selective schools have been using them to rule out applications that have been developed with expensive admission consultants.
So should we worry, and how should we combat this? But could there already be some bias, even on admissions teams? From the 2023 “ Harvard Admissions Officers Answer the Web’s Most Searched Questions” video published by Harvard College Admissions & Financial Aid, the panel was mostly made up of Harvard and other Ivy League alumni. Nonetheless, it is important to remember that the admissions teams consist of a diverse group of staff. However, it's the teams, not AI, that make the final admission decision. Moreover, applications are viewed holistically. The decision to submit a resume, SAT scores, and supplementals all depends on the individual colleges. It is important to check each school's requirements and pay attention to deadlines. You should connect courses and extracurriculars to a core theme that connects with you. It is crucial to begin requesting letters of recommendation, as strong letters can vouch for extracurriculars, curriculum, and extenuating circumstances while also highlighting leadership and personality beyond an essay. Being authentic in the essay, along with scores and awards, can help as well.
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Checklist 1.Track Deadlines. You can maintain and keep up with deadlines on a spreadsheet or a running document. 2.Check test-optional policies; if your score is considered weak, let your GPA and course rigor shine. 3.Focus on a passion vs listing generic clubs. 4.List important awards and activities at the top with full names. It is better to have a few strong extracurriculars than random ones that dilute your application. 5.Use the Additional Information section to explain context.
While algorithms look for patterns, colleges seek people who can contribute to their communities and leave a long-lasting impact. Best of luck, Class of 2027!
August 29, 2026 / Marlee Mei / marleebmei123@gmail.com 12
SONAR THE INNOVATION FROM NATURE
Ashley
D
id you know that nature is the source of technological innovation? That is why humans are always familiar with nature in daily life. One of the technological innovation is linked to nature is sonar, used to explore the ocean and map vast reaches.
What is Sonar? Sonar (Sound Navigation and Ranging) is used to explore and map the ocean via sound waves to detect objects, because sound waves travel farther underwater than radar. Moreover, water can amplify and transmit sound hundreds of times more than open air at a considerable speed. It generates conditions for clear visibility and light in a supply.
Types of Sonar Sonar consists of 2 types: active and passive sonar. Active Sonar: Its transducer emits a pulse of sound or acoustic signal into the water by using sound waves to detect echoes: It propagates sound into the water. A receiver on the emitting transducer detects an echo of the sound wave after bouncing off objects. It determines the time between the initiation of the sound wave and its return. Passive Sonar: It is used to detect noise from marine organisms to identify conditions by introducing active sonar and is useful for military vessels, unlike using a transmitter-produced sound wave to generate data and emit signals. It focuses on listening to the ocean silently. That is why it enables users to remain silent and hidden. Passive sonar cannot measure an object’s range without being used in conjunction with passive sonar devices.
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Transmission and Reception The methodology of acquiring information from a sonar system depends on the type of sonar operated. Passive sonar relies on a reception system without active transmission components. Active sonar uses a transducer to measure the arrival time of the returning echo, which is subsequently used to determine its range and direction.
How Does Sonar Process The Data? By acquiring data, sonar converts sound propagation into a useful form. Sonar discerns useful information from ambient sounds that human ears cannot hear. However, the process is fraught with difficulties ranging from changing conditions to human error.
How Does It Impact the Environment? Sonar’s functions include output power, transmission frequency, and sound transmission characteristics in the marine environment, which impact marine species that rely on: Hearing response characteristics. Behavioural sensitivity. Distance from sound source.
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Environmental Challenges: 1.Modern power plants on ships and submarines generate a vast amount of power, which limits sonar ability to transmit and receive sounds. 2.The water temperature affects sound propagation; for instance, in freshwater, sonar capability degrades compared to saltwater. 3.Large amounts of algae or microscopic life, such as frogs, cause different levels of water density. Moreover, marine animals generate sound to avoid man-made emissions.
4.The biggest challenges to maximizing sonar effectiveness are geography and temperature. Sonar operates best in deep water where reflections off shore do not cause echoes. Geography: Sonar has trouble distinguishing between inputs to determine whether a sound is natural or artificial because of multiple reflective surfaces. Sonar-emitted sound tends to bounce off these layers and wrap or hide an object. Temperature: When the water level increases, sunlight reaches the floor, bringing about different strata and water temperatures (known as thermal layers). 5.The underwater environment is complex. Various sounds are intense and propagate along non-linear pathways, affected by temperature, salinity, other variables, and weather, over hundreds of miles. The sensor's detection is a combination of different sources, ranging from fishing vessels and earthquakes to organic life and other signals of interest.
Output Power The strength of active sonar plays an important role in potential impact considerations on marine species. The output power depends on the system’s designed purpose. When the system can detect objects at greater distances, power transmission can operate because the expected output power is reflected to the detector from a distant object and the source. High power sonar includes: Military antisubmarine sonars. Commercial sidescan sonars. Deep echo sounders. Fish finders.
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Output Frequency Active sonar uses a range of frequencies, depending on the equipment’s role: Lower frequencies (below 20 kHz) have greater ranges in seawater due to the low rates of attenuation with distance, relying on them for distant objects and not suitable for small objects. High to extremely high frequencies offer excellent object resolution (fish and small objects); however, they suffer from severe attenuation with distance from the source. These systems are only practical in shallow water and for objects near the source.
Output Power Levels Versus Received Levels The sound source will be brought up to the observer to reduce the increasing distance in source intensity as it returns due to the sound wave’s loss of energy and the propagation of the energy more thinly when the wave is released. Received level (called perceived output), unlike the source level, which is an abstract measure of the source characteristics. It should also be noted that sound levels quoted for various sources in air bear no direct relation to in-water sound sources. It is used for the determination of potential impact on marine species.
Receptor Species Auditory Characteristics Active sonar depends on the species’ hearing ability in different frequency ranges. The efficiency of sound identification with frequency, such as species-specific behavioral detected sound responses, may vary based on species’ sensitivity to disturbance and what activities they have engaged in.
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Knowledge Gap Sonar has undergone significant technological changes with the incorporation of AI and smart sensors. However, many scientific articles have not explored the functions of Sonar and the types of military sonar. 1.Is military sonar active or passive sonar? According to the Australian Government Department of Climate Change, Energy, Environment and Water, active sonar is categorized as a type of sonar used for military purposes. The scientific article’s introduction does not mention the different purposes of active and passive sonar, prone to misunderstanding by scientific readers. However, the National Sonar Service demonstrates that passive sonar operates for military vessels to detect objects and sounds in the ocean. -> Both active and passive sonar can be used for military purposes.
2.How do Passive Sonar work with data? The Source EBSCO illustrates that passive sonar cannot generate data; however, it is not mentioned that passive sonar can process data to convert received sound into electrical signals, which are sent via computer for a sonar operator to analyze according to the Science of the Sound. -> It may lead to misunderstandings about passive sonar’s data function.
August 29, 2026 / Ashley 18
YOUR INFORMATION, MY DATA LUANA HUA
INTRODUCTION
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oes “Big Data” own your information? Are large publicly accessible data sets a result of privacy breaches and uninformed consent? Am I violating privacy if I try to run Random Forest on your information for my science fair project? Modern science research is heavily driven by data and computation. Whether it’s in a literature review or original experiments done on pre-collected informatics, it is a common route taken for research that is not direct experiment or novel theory. For high schoolers and undergraduates especially, it seems like a good way to satisfy curiosity or complete a project for a CV. But has anyone stopped to think about what’s going on with this methodology, beneath the surface?
INFORMATICS IN RESEARCH Nowadays, when many people look to do research, it usually involves public data and analytics. Economic, epidemiologic, biomedical, there’s a data set for everything that involves real human information. Is the low barrier to access this data a downside for the quality of scientific content; is the information even accurate? And is this even ethical?
Large-scale data collection has become increasingly important across many areas of research, including economics, public policy, education, public health, sociology, and environmental science. Access to large datasets allows researchers to identify broad patterns, compare different populations and study trends over long periods of time.
In economics, for example, large datasets can help researchers analyze employment, inflation, consumer behavior, and inequality. In public policy, data collected from government programs, surveys, and administrative records can be used to evaluate whether policies are effective and which groups benefit most from them. Clearly informatics and data collection, as well as accessibility of this, are extremely useful. However, there are some quite rigorous standards that must be enforced around this for it to be beneficial to society, for a variety of reasons. Big data creates major research opportunities, but scale does not eliminate problems involving bias, consent, privacy, ownership, inequality, or research quality.
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BIG DATA OWNS YOU NOW Mittelstadt and Floridi in “The Ethics of Big Data: Current and Foreseeable Issues in Biomedical Contexts” identify five major issues already receiving attention: informed consent, privacy and anonymization, ownership of data, the reliability and objectivity of knowledge produced from big data, and the “Big Data Divide.” The Big Data Divide refers to inequality between organizations that possess the data, computing resources, and expertise necessary to conduct sophisticated analyses and those that do not. Therefore, making large quantities of information available does not automatically make research equally accessible to everyone. Additional emerging concerns are also highlighted: harms to entire groups rather than only individuals, changes in relationships of trust when institutions possess extensive personal information, differences between academic and commercial uses of data, intellectual-property disputes over discoveries created from aggregated datasets, and whether individuals can realistically exercise rights over their information. Together, these issues lead the authors to argue that governance of big data must develop alongside the technology rather than assuming existing ethical rules will always be sufficient. Zook et al in “Ten Simple Rules for Responsible Big Data Research” approach big-data ethics from a practical perspective. Their central argument is that researchers should not treat datasets as abstract collections of numbers simply because the people represented in them are not physically present in the research process. Much large-scale data ultimately describes individuals or communities. They argue that researchers should begin with the assumption that data involving human behavior may have consequences for people, even when the information appears harmless or is already publicly accessible.
A CRITICAL AND PHILOSOPHICAL PERSPECTIVE When approaching large scale data collection, the belief that its enormous scale automatically makes research more accurate, objective, or scientifically valuable should be challenged. There are also broader ethical and philosophical implications on data and personal autonomy. For example, it can be argued that big data gives organizations an unprecedented ability to observe individuals, make predictions about them, and use those predictions to influence decisions. One can distinguish confidentiality from secrecy. For example, information can be shared with a doctor, school, company, researcher, or government agency while still being confidential. The fact that another organization possesses information does not mean that all restrictions on its use disappear. 21
There is also the issue of transparency. When large datasets are used to make predictions or decisions about people, individuals and society need some ability to understand how those systems operate. This becomes particularly relevant in public policy, education, credit, employment, health care, and other settings where data driven classifications can significantly affect opportunities. Big-data systems increasingly classify people according to predictions made from past behavior or correlations with similar groups. The risk is that people increasingly become defined by what an algorithm predicts about them rather than by choices they make themselves. Many are critical of the assumption that publicly available data presents little ethical risk. Data that appears harmless by itself can reveal extremely sensitive information when combined with other sources, and open access should not be treated as equivalent to unlimited permission to aggregate, analyze, or republish information.
THE FUTURE OF INFORMATION SCIENCE IN SOCIETY Large-scale data collection has transformed research across fields such as biology, economics, public policy, public health, and the social sciences. Open access can further improve transparency and collaboration by allowing researchers to verify results and build on previous work. Researchers must also consider informed consent, re-identification, unequal access to data and computing resources, institutional power, harm to individuals and communities, and the possibility that poor-quality analysis can influence real-world decisions.
September 16, 2026 / Luana Hua / luanahua821@gmail.com
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MISINFORMATION AND FAKE NEWS HOW TECHNOLOGY HAS CHANGED THE SPREAD OF FALSE INFORMATION
Maggie Zhang
INTRODUCTION
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ow do we know if what we see online is actually true? Today, social media allows information to spread to millions of people in just a few seconds. Because of this, misinformation and fake news have become major problems in modern society. A fake post, edited picture, or misleading headline can be shared thousands of times before anyone checks if it is true. Misinformation is false or inaccurate information that is shared without meaning to deceive people. Disinformation is false information that is purposely created or shared to trick people. Even though false information has existed for a long time, technology has made it much easier to spread. Understanding how technology spreads misinformation, how it affects society, and how people can fight against it is important because so many people now get their news and information online.
HOW TECHNOLOGY SPREADS MISINFORMATION Misinformation and disinformation are similar, but the main difference is the person's intention. Misinformation is false information that someone shares because they believe it is true or do not know that it is false. Disinformation is created or shared on purpose to deceive people. Even if someone does not mean to spread something false, misinformation can still cause problems when other people believe it and continue sharing it. Social media has completely changed how people receive information. Before social media, newspapers, television stations, and professional journalists were some of the main ways people got their news. Today, almost anyone can make a post and share information with a large audience. A person does not have to be a professional journalist or go through a fact-checking process before posting something online. This means false information can spread much faster than it could in the past. Social media algorithms can make this problem even worse. These algorithms decide what content appears on a person's feed based on things like their interests and what they interact with. Posts that get a lot of likes, comments, or shares may be shown to even more people. Emotional, shocking, or controversial posts often get a lot of attention, which can cause misleading information to spread quickly. Another problem is that fake information can look real. A fake news story might use a professional-looking website or a convincing headline. Real pictures and videos can also be edited or taken out of context to make people believe something that is not true. Because people often share posts quickly without checking them, misinformation can reach people all around the world almost instantly.
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THE EFFECTS OF MISINFORMATION ON SOCIETY Misinformation can make it difficult for people to know which sources they can trust. If someone constantly sees different versions of a story online, they may not know which one is true. Over time, this can cause people to lose trust in journalists, scientists, governments, and other organizations. When people do not trust reliable sources, it can become harder for society to deal with important problems. Misinformation can also affect politics. False information can change how people think about political candidates, elections, and important issues. Social media makes it easy for political misinformation to reach a large number of people. Sometimes, people are more likely to believe information that agrees with what they already think. This can cause arguments, division, and stronger disagreements between groups of people. Health misinformation can be especially dangerous. During the COVID-19 pandemic, the World Health Organization described the huge amount of information, including false and misleading information, as an “infodemic.” People were exposed to many different claims about the virus, treatments, and vaccines. Some of this information was incorrect, which could cause confusion and lead people to make unsafe choices. False health information can also make people less likely to trust doctors and health organizations.
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Misinformation can even affect everyday decisions. People might buy a product because of a false review, believe a fake story about a current event, or make a health decision based on something they saw online. False information can spread through friends, family, influencers, and online communities. Since people often trust information shared by people they know, correcting misinformation can be difficult. This shows that something posted online can have real effects in the world.
FIGHTING MISINFORMATION AND THE FUTURE OF INFORMATION One of the best ways to fight misinformation is to become better at checking information. People should look at who created a post and where the information originally came from. It is also helpful to compare information with other reliable sources before believing or sharing it. Fact-checking websites can help determine whether claims, pictures, and videos are accurate. People should also slow down before sharing something, especially if it makes them extremely angry, scared, or excited. Social media companies also have a responsibility to help reduce misinformation. Platforms can create systems that identify false or harmful information and give users more context about questionable posts. They can also explain more about how their algorithms decide which posts people see. However, companies have to be careful because stopping misinformation should not mean removing people's ability to express their opinions. Journalists also have an important role in fighting misinformation. Professional journalists can check facts before publishing stories and provide reliable information during emergencies. Factcheckers can investigate false claims and show evidence that explains what is actually true. Reliable journalism gives people a better way to separate real information from fake or misleading content.
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Artificial intelligence could make misinformation an even bigger problem in the future. AI can create realistic pictures, videos, voices, and articles that may be difficult to tell apart from real ones. Deepfakes, for example, can make it look like someone said or did something that never actually happened. However, AI could also be used to help detect fake information and assist fact-checkers. This means AI could become both part of the problem and part of the solution.
CONCLUSION Technology and social media have changed the way misinformation is created, shared, and consumed. False information can now spread extremely quickly and affect people's trust, political opinions, health choices, and everyday decisions. People can help reduce the problem by checking sources, comparing information, using fact-checking tools, and thinking carefully before sharing posts. Journalists and social media companies also have important responsibilities when it comes to providing accurate information and limiting harmful false claims. As artificial intelligence becomes more advanced, deepfakes and other forms of fake content may make misinformation even harder to recognize. In the future, knowing how to tell the difference between reliable and false information will be an important skill for everyone.
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September 12, 2026 / Maggie Zhang / magmaggiezhang@gmail.com
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or millions of years we thought our genetic code was a simple nuanced structure that showed no modifications or changes to certain conditions.Today, CRISPR and gene-editing technologies have given us the pen to modify our own DNA for future breakthroughs. Before we get into the complexity of various nuances in this whole branch of genetics, we need to underline some key terms . Genetic engineering - The direct manipulation of a subject’s genome to add , remove or fix traits .It builds modified human living things called GMO’s or creates medicines like human insulin. Customized Specimen - I know the word sounds weird but from recent studies the science has baffled us from time to time to show how genetic engineering can be used in animals all the way to humans to customize specific traits as we did so as kids with our play dolls .But what exactly makes a person or a subject customized; Tailoring biological traits for specific functions, environments, or research purposes slightly or completely altering its DNA. Examples across domains: disease-resistant crops (Bt cotton, Golden Rice), model organisms in medical research (knockout mice), and engineered cellular therapies (CAR-T cell therapy).
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From the Lab to the World Gene modification as a process is used in various caricatures of occupations such as Agriculture, Animal testing,pharmacy , and overall research of autonomical diseases in our body .Let us see how the customized Specimen is finally deployed in the real world . CRISPR-Cas9 : A fast, flexible tool that edits genes by cutting DNA at a specific target location. Guide RNA : A small piece of RNA that meets or matches the target DNA sequence .It finds the exact spot on the genome .It acts as the GPS taking the molecular enzyme to the correct spot . Cas9 Protein: An enzyme that acts like molecular scissors to cut the target DNA strand. Targeting: The guide RNA finds the correct spot on the DNA. The Cas9 protein attaches to it and makes a cut. Repair: The cell tries to fix the cut. Scientists can use this moment to turn a gene off, or insert a new piece of corrected DNA. TALENs (Transcription Activator-Like Effector Nucleases: Often preferred for its high versatility and highly specific nature .These are again custom-built restriction enzymes used to cut specific DNA sequences and edit genes. They are larger and more complex than the newer systems. DNA-Binding Domain: Made from proteins originally found in Xanthomonas bacteria. They use repeating amino acid chains called RVDs (repeat variable diresidues) to recognize and bind to a single, specific DNA letter (nucleotide) at a time.Nucleotides are nothing but the functional building blocks of RNA and DNA. Cleavage Domain: Fused to a cutting enzyme called Fokl. Dimerization: Two TALEN proteins must lock onto opposite sides of the target DNA strand and join together to activate the Fok/ cutter. Double-Strand Break: Once joined, the enzyme cuts both strands of the DNA, creating a break that the cell tries to repair, allowing researchers to delete, fix, or alter genes.
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Mechanisms Where They Are Used Medicine : Targeted gene therapies, synthetic insulin production and genetically modified pigs and humans China has been a great pioneer in this domain Agriculture: Genetically modified crops to resist vector bone diseases improve nutrition and fight against pesticides. Gene drives use tools like CRISPR-Cas9 to bypass normal rules of heredity, forcing a specific genetic trait to not just half of the offspring but to 90% . Industrial Biotechnology: Bioengineered microorganisms producing sustainable biofuels and biodegradable materials.
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Dark side of Genetic Manipulation Every common entity or a breakthrough in biotechnology comes with its own advances and disadvantages. Biological and Technical complication Off target mutations - Unintended DNA cuts causing phenotypic mutations which are observable cell or tissue traits or oncogenic risks such as cancer development. Ecological and environmental risks : Genetically modified organisms in the wild disrupts the natural order of the universe by disrupting natural ecosystems or reducing genetic variation mostly seen in interbreeding . Access Disparities: The risk of "genetic inequality" where high-cost treatments are restricted to wealthy demographic.Mordern gene therapies cost thousands or even millions of dollars which do not cater to all the beings out there .Also health insurance usually never covers gene modification strategies or therapies in its cost often posing a burden on the underprivileged.
Conclusion In conclusion, genetics in the whole world has come a long way, something that was almost impossible more than 10 decades ago has been subsequently changed with new systems that genetic engineering has brought to us .It is now deeply integrated in our economical ventures of society such as medicine , Pharma, surgery , agriculture and industries .Technology isn't inherently good or bad-our stewardship, policy, and precision will decide whether "customized specimens" heal the world or disrupt it.
August 24,2026 / Tista Bhatia/ tistabhatia@gmail.com 32
ARTIFICIAL INTELLIGENCE: MENTAL TRACKING IMPACT IMPACT OF AI CODING ASSISTANTS ON NOVICE CODE OUTPUT
Dane Baes
Introduction Through the past few years, Artificial Intelligence (AI) has made many adjustments and has been tailored to meet its requirements. As it learns more information by the day thanks to digital networks, it helps learn trends to help improve and appeal to the individual that is using it, as AI is evolving to become more human-like and realistic from their responses to their video production as well. Thanks to this creation, AI assistants can be seen in almost every website nowadays, especially used to navigate through obstacles. AI’s impact on coding –a large aspect of the modern world– is an example of how things could be made easier through this epic of modern technology, as it helps break down and solve code in seconds.
Before a programmer presses “run”, they should be able to look at a short piece of code and make a reasonable prediction about what it will do. Though for a beginner, this is not always easy: one changed variable, loop, or condition can completely change the output. Nowadays, AI coding assistants can write and explain code in merely seconds. That creates an important question: if a novice programmer has already relied on AI to help write code, does that experience change how accurately they can mentally track code on their own? Advancements in AI coding assistants have made it easier for novice programmers to understand and work with code, but AI does not directly measure or calculate their mental tracking ability. Instead, mental tracking can be measured by testing how accurately programmers can predict code output on their own, which allows researchers to examine whether prior reliance on AI affects their ability to understand and mentally trace code independently.
Why Mental Tracking Matters Mental tracking helps programmers understand what their code is doing without having to run it. In general, it is the cognitive ability to hold and update information in your brain’s working memory. This requires the programmer to build a mental model of how the code executes and trace the outputs back to the code step by step. Mental tracking can reveal whether a student actually understands the code rather than simply knowing its syntax.
Being able to mentally track code also helps novices become more independent programmers because predicting an output requires students to reason through the code instead of relying on trial and error. It can also help them identify mistakes before running the program. Research has found that tracing can help novices understand and explain code, although students may struggle when they have incorrect ideas about how programming concepts work
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What AI Coding Assistants Change AI coding assistants can generate, explain, and modify code, which can help beginners complete programming tasks more quickly. This connects to mental tracking because beginners still need to understand and trace AI-generated code rather than simply accepting the output. If students rely only on AI to provide the answer, they may complete the task without fully understanding how the code works. Research by Kazemitabaar et al. (2023) found that AI assistance can improve coding performance among novice learners. In their study of 69 novice learners ages 10–17, students who had access to an AI code generator had a 1.15× higher completion rate and 1.8× higher scores on codeauthoring tasks. The researchers found that AI assistance increased students’ coding performance without decreasing their performance on manual code-modification tasks. This suggests that AI can help beginners complete programming tasks more efficiently while still allowing them to work with code themselves. However, despite these benefits, using AI coding assistants can also lead to over-reliance. Kazemitabaar et al. (2023) specifically noted that over-reliance on AI could negatively affect learning and retention. Similarly, Rojas-Galeano (2025) found that students viewed AI coding assistants as helpful for understanding code and increasing confidence, but some students had difficulty transferring what they learned to programming tasks without AI assistance. This is important because it suggests that while AI can improve performance when students have access to it, frequent reliance on AI may make it harder for some beginners to apply programming concepts independently to new problems.
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The Possible Trade-off Furthermore, previous AI use may affect how much beginners practice solving problems independently; some students may use AI to understand and explain code, while others may rely on AI to generate complete solutions. Although both uses can help students complete programming tasks, relying on AI to create most of the code may reduce the amount of independent problem-solving practice a beginner gets. One possible explanation is that heavy reliance on AI systems may reduce the amount of practice beginners get with mentally tracing code, although this relationship would need to be tested through research. Since AI can provide a solution with only a few clicks, students may skip the process of working through each function and procedure step by step. This can make programming feel easier and more straightforward, but it may also limit how much students practice reasoning through code on their own. Research on code tracing has shown that tracing can help students understand and explain how code works, making this independent practice important for developing code comprehension (Hassan & Zilles, 2023). Learning primarily through AI assistance may also create difficulties with transferring knowledge to new problems. If novice programmers begin with AI generating solutions for them, they may have fewer opportunities to learn each programming concept and practice applying it independently. This connects to Rojas-Galeano (2025), who found that students recognized benefits from AI coding assistants but also experienced difficulties transferring what they learned to tasks without AI assistance. This creates a possible trade-off between AI assistance and independent reasoning, where AI can help students perform better in the moment but may not always lead to the same level of independent problem-solving ability.
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How This Can Be Tested This idea of measuring the impact of prior AI use on novice programmers can be tested through a simple online exercise. Participants would first be shown several short pieces of code and asked to predict the output before running the program. After recording their predictions, they would execute the code and compare the actual output with what they expected. Each participant would then receive an accuracy score based on how many predictions were correct, providing a measure of their mental tracking and code comprehension skills. This idea of measuring the impact of prior AI use on novice programmers can be tested through a simple online exercise. Participants would first be shown several short pieces of code and asked to predict the output before running the program. After recording their predictions, they would execute the code and compare the actual output with what they expected. Each participant would then receive an accuracy score based on how many predictions were correct, providing a measure of their mental tracking and code comprehension skills. The study should also consider participants’ prior programming experience and baseline programming skill. Before the main exercise, participants could complete a short baseline assessment that measures their understanding of basic programming concepts without using AI. Participants could also report how long they have been programming and what programming languages they have previously used. This information would help determine whether differences in code-tracing accuracy are related to prior programming ability rather than only differences in AI usage. The study should also consider how participants used AI coding assistants before completing the exercise. For example, participants could indicate whether they typically use AI to generate complete solutions, modify existing code, or mainly ask for explanations. During the assessment, participants’ screens could be monitored to ensure they complete the code-tracing exercise independently and do not use AI while making their predictions. Finally, the results could be compared across participants with different levels of prior AI use while accounting for their programming experience and baseline skill. This would help determine whether AI use is associated with differences in mental tracking accuracy rather than differences in existing programming ability. Overall, the study could provide insight into how AI coding assistants may support or affect independent programming skills and what role they should have in programming education.
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September 12, 2026 / Dane Baes / danebaes08@gmail.com
Who Owns Our DNA? The Ethics of Consumer Genetic Testing in the Age of Genomics
Esther Tyrnauer
Introduction
O
ver the past decade, consumer genetic testing has moved from a niche curiosity to a mainstream phenomenon. Companies like 23andMe and AncestryDNA have sold tens of millions of testing kits worldwide, allowing ordinary people to spit into a tube and receive a detailed report on their ancestry, health risks, and even distant relatives they never knew existed. The appeal is obvious: for a modest fee, anyone can uncover hidden pieces of their family history or gain insight into their genetic predispositions to certain diseases. But beneath the fun of piechart ancestry breakdowns lies a much darker reality that the industry has been reluctant to advertise: once your DNA leaves your body and enters a corporate database, you largely lose control over it. The 2023 breach of 23andMe, which exposed the genetic and family data of nearly 7 million people, and the company's subsequent bankruptcy, which turned millions of genetic profiles into an auctionable business asset, prove that this is not a hypothetical concern. The real question is not whether people should be allowed to explore their genetic ancestry, but whether the current system, in which a handful of private companies hold immense, largely unregulated power over humanity's most personal information, is one society should accept. It should not, at least not without far stronger protections than currently exist.
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How Consumer Genetic Testing Works Consumer genetic testing kits are designed to be simple enough for anyone to use at home. A customer orders a kit online, provides a saliva or cheek-swab sample, and mails it to the company's lab. There, technicians extract DNA from the sample and analyze specific locations in the genome using a technique called genotyping, which scans for particular genetic markers rather than sequencing the entire genome. These markers can reveal information about ancestry composition, connections to relatives who have also tested with the same company, and, in some cases, predispositions to certain health conditions or carrier status for inherited diseases. Results are typically delivered through an online portal within a few weeks. While this process feels straightforward from the consumer's perspective, it generates an enormous, permanent digital record of some of the most personal information a person can possess: their biological blueprint.
The Benefits of Consumer Genetic Testing The popularity of these services is not accidental; they offer genuine and often meaningful benefits. For many people, ancestry testing provides an emotional connection to family history, cultural heritage, and even long-lost relatives, sometimes reuniting adoptees with biological parents or siblings. On the health side, some tests offer insight into carrier status for conditions like cystic fibrosis or Tay-Sachs disease, which can be valuable information for family planning. Certain platforms also screen for a limited set of genetic variants associated with elevated risk for conditions such as certain hereditary cancers, informing conversations with healthcare providers about further screening. Beyond individual users, the aggregated genetic data collected by these companies has become a valuable resource for scientific research, contributing to studies on disease mechanisms, drug development, and population genetics. In many ways, consumer genetic testing has democratized access to information that was once available only through expensive clinical channels, empowering individuals to take a more active role in understanding their own biology.
Ethical and Privacy Concerns This is where the industry's rosy marketing collides with an uncomfortable reality, and where the ethical case against the status quo is strongest. The first problem is ownership: when a person submits their DNA, they typically click through lengthy terms of service that grant the company broad rights to store, analyze, and in some cases share that genetic information with pharmaceutical or research partners. Almost no one reads these agreements in full, which means "informed consent" in the genetic testing industry is often a legal fiction rather than a genuine safeguard. The 2023 23andMe breach turned this abstract risk into a concrete harm: attackers used stolen passwords to break into roughly 14,000 accounts, but because of the platform's "DNA Relatives" family-matching feature, that initial foothold cascaded into the exposure of data belonging to 6.9 million people, the majority of whom never had their own password stolen at all. Genetic information, unlike a credit card number, cannot be reissued once it is exposed, a point UK regulators emphasized when they fined 23andMe £2.3 million for its inadequate security practices. 40
The company's 2025 bankruptcy made the ownership question even starker, transforming millions of genetic profiles into a sellable corporate asset and prompting nearly thirty state attorneys general to sue, arguing that DNA is not the kind of property that should change hands in a bankruptcy auction without each person's explicit consent. Beyond corporate mishandling, there is the problem of discrimination. Genetic testing can reveal predispositions to conditions like Alzheimer's or hereditary cancers, and while the U.S. Genetic Information Nondiscrimination Act (GINA) bars health insurers and most employers from using this information against people, the law has glaring gaps: it does not apply to life insurance, disability insurance, or long-term care insurance, and it exempts employers with fewer than fifteen employees. In other words, the very insurance products people most need when a genetic risk becomes real are the ones GINA does not touch. Finally, consumer genetic databases have become an investigative tool for law enforcement. The 2018 arrest of the Golden State Killer, made possible when investigators uploaded crime-scene DNA to the genealogy site GEDmatch and traced third-cousin matches back to a suspect, was celebrated as a triumph of forensic science. But it also revealed something unsettling: you do not have to take a DNA test yourself to be searchable. A distant cousin's decision to spit into a tube can make your family genetically traceable by police, without your knowledge or consent, illustrating that genetic privacy is not really an individual choice at all, since one person's decision to test can expose an entire extended family.
Finding the Right Balance The current regulatory patchwork is simply not built for the stakes involved, and closing that gap should be a policy priority rather than an afterthought. Oversight of direct-to-consumer genetic testing companies varies significantly by country and is generally far less rigorous than the rules governing clinical genetic testing ordered by a doctor. Some companies have taken modest steps toward transparency, publishing clearer privacy policies and allowing users to opt out of research participation or law enforcement searches, but these protections are voluntary, inconsistent across the industry, and, as the 23andMe bankruptcy showed, can potentially be renegotiated the moment a company changes hands. Lawmakers should not wait for the next scandal to act. At minimum, genetic data should be treated as a distinct, specially protected category, not an ordinary business asset that transfers automatically in a merger or bankruptcy sale, and companies should be required to obtain fresh, explicit consent before genetic data changes ownership. Congress should also close GINA's insurance loopholes, extending protection to life, disability, and long-term care insurance, so that the health insights genetic testing promises do not come at the cost of future insurability. None of this means research should grind to a halt; genomic research has produced real medical breakthroughs, and blanket restrictions would throw out enormous public benefit along with the risk. But there is a meaningful difference between researchers accessing de-identified, consent-based datasets for legitimate studies and a bankruptcy court auctioning off 15 million people's DNA to the highest bidder. Policy should be built to distinguish between the two.
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Conclusion Consumer genetic testing sits at a genuinely exciting intersection of technology, science, and personal identity, and it would be a mistake to dismiss the real benefits it has delivered in ancestry discovery, health insight, and scientific research. But the industry's short history has already shown what happens when innovation outruns regulation: a company can lose the genetic data of millions to hackers, get fined a few million pounds, and then sell that same data as a corporate asset a few years later when the business fails. That is not a hypothetical slippery slope; it is what actually happened to 23andMe. The uncomfortable truth is that genetic information is unlike any other kind of personal data. It cannot be changed after a breach, it implicates relatives who never consented, and it will likely still describe you and your descendants decades from now. Treating it with the same casual terms-of-service framework used for a shopping app or social media account is not a neutral choice; it is a decision to prioritize corporate convenience over the kind of protection this uniquely permanent information deserves. As more of the human genome ends up in commercial databases, society cannot keep treating this as a niche privacy issue. It is a foundational question about who gets to control the biological information that defines us, and the answer, increasingly, should be the individuals it belongs to, not the companies that happen to be holding it when the terms of service are signed.
August 28, 2026 / Esther Tyrnauer / estherbtyrnauer@gmail.com 42
Smart Cities, But Sicker People? The Insidious Cost of Urban Progress Mehreen Muzafar
L
ast summer, a 34-year-old schoolteacher from Srinagar was admitted to the hospital with a fever. She lived in one of the city's newly developed smart neighborhoods and had shown no signs of any serious sickness prior to this. Yet something was wrong with her immune system, and the doctors couldn't pinpoint why her inflammatory markers were so high. Srinagar is being rebuilt as a smart city. New roads, digital infrastructure, and modern buildings are replacing old neighborhoods. But underneath the progress, a biological experiment is happening.
The Old Way Of Life Research shows that people raised in rural environments with regular contact with farm animals have lower inflammatory responses to stress, higher levels of anti-inflammatory IL-10, and more regulated immune function overall. A study led by researchers from the University of Ulm and the University of Colorado Boulder found that rural-raised individuals had significantly lower levels of inflammatory immune cells after a stressful experience compared to their urbanraised counterparts. The urban group also showed prolonged elevation of the inflammatory compound interleukin-6 and muted activation of the anti-inflammatory compound interleukin10. This is what scientists call the biodiversity hypothesis. The microbes typically found in rural environments are more diverse than those in urban environments, and our immune systems need to be challenged by these natural environment microbes to develop properly. Without that kind of exposure, our systems are less likely to rein in inflammation. Srinagar's traditional lifestyle with its gardens, wetlands, and close connection to nature offered this protection. People lived with animals, walked outdoors, and had diverse microbial exposures. But as the city modernizes, those protective factors are disappearing
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The Smart City?
Srinagar's Smart City Mission includes new concrete structures and roads, digital surveillance systems, and modern buildings with sealed windows. The project, approved at an estimated cost of Rs 3,634 crore, has delivered visible upgrades including the redevelopment of Lal Chowk, pedestrian-friendly streets, electric buses, cycle tracks, and riverfront promenades along the Jhelum. Official data shows 185 projects worth Rs 4,154.96 crore have been sanctioned, with 103 projects valued at Rs 2,575.95 crore already completed. But despite this supposed success, residents report an acute public health crisis that smart infrastructure has yet to address. The stray dog crisis is a major concern. According to official statistics, Srinagar has one stray dog for every 13 humans, with the Union Territory reporting over 2.13 lakh dog bite cases between 2022 and 2025. Srinagar alone accounts for 36,406 of these cases, making it the worst-affected area. Every day, approximately 150 people are bitten by stray dogs across Jammu and Kashmir. The new smart infrastructure shows no signs of addressing this public health emergency. The waterlogging problem is perhaps even more glaring. Despite smart planning and over ₹792 crore already spent under the Srinagar Smart City Project, a single hour of rain still floods the city. Recent images of Srinagar's flooded Lal Chowk and iconic clock tower circulated widely after rainfall choked the city's drainage system. Chief Minister Omar Abdullah himself acknowledged shortcomings, calling it a matter of shame that the ground floor of the Secretariat was under water and questioning where the Smart City money went. The government has since ordered a thirdparty audit to investigate alleged shortcomings in the project's implementation.
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And then there are the reduced green spaces. Concretization leads to less natural immune support from the environment. As the city covers its soil with concrete, it loses the microbial diversity that once helped residents' immune systems develop properly.
The Need For Balance Srinagar's Smart City Mission has achieved some actual successes—132 projects completed, green building initiatives that reduce asthma and allergy risk, and improved walkability and public spaces. The city has also established an Integrated Command and Control Centre to monitor civic operations. But the city is ignoring deeper health questions. The urban environment is changing the workings of people's immune systems. Research suggests that spending as much time as possible in environments offering a wide range of microbial exposures has many beneficial effects, yet Srinagar's development is moving in the opposite direction and is sealing people off from nature while failing to address basic public health crises. The biggest irony lies in the fact that the Smart City Mission has actually made things worse in some ways. The government has acknowledged that no comprehensive drainage scheme was ever executed under the Smart City project, and stormwater pipelines were laid only along select corridors rather than replacing the older, inadequate sewerage system. This approach leaves large stretches of the historic downtown dependent on drains built generations ago for a much smaller city. A little sprinkle of rain is enough for those drains to fail.
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Conclusion Srinagar is caught between two struggles. The city wants to be modern and smart. But the traditional way of life- close contact with animals, open spaces, and natural environments protected people's immune systems. The contradiction is that this supposed progress might be making people sicker Srinagar doesn't need to go back to being a “rural village”. But it definitely needs to change its definition of a smart city. Instead of just installing sensors and building roads, the city could integrate nature into the urban framework, address the stray dog crisis as a public health issue, protect wetlands and green spaces, and recognize that human health is a part of smart urban planning. This entire case has made us question whether being smart is only about technology or if it has anything to do with people's biology too.
August 29, 2026 / Mehreen Muzafar /muzafarmehreen8@gmail.com 47
WORKS CITED THE DIGITAL DECIDER - ANU O Gillespie, T. (2014). The relevance of algorithms. MIT Press. https://mitpress.mit.edu/9780262525374/therelevance-of-algorithms/ Pariser, E. (2011). The filter bubble: What the Internet is hiding from you. Penguin Random House. https://www.penguinrandomhouse.com/books/305009/the-filter-bubble-by-eli-pariser/ O'Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown Publishing Group. https://www.penguinrandomhouse.com/books/241363/weapons-of-mathdestruction-by-cathy-oneil/ Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs. https://www.hachettebookgroup.com/titles/shoshana-zuboff/the-age-of-surveillancecapitalism/9781610395694/ Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. NYU Press. https://nyupress.org/9781479837243/algorithms-of-oppression/ Winner, L. (1980). Do artifacts have politics? Daedalus, 109(1), 121–136. https://www.jstor.org/stable/20024652 iStock. (n.d.). Smart phone controlling man [Vector illustration]. https://www.istockphoto.com/vector/smartphone-controlling-man-gm1291542410-386627154 MDPI. (2023). Social sciences article (Vol. 12, Issue 12, Article 679). https://www.mdpi.com/20760760/12/12/679 Getty Images. (n.d.). Social media bubble speech concept vector [Illustration]. https://www.gettyimages.com/detail/illustration/social-media-bubble-speech-concept-vector-royalty-freeillustration/526466381 COLLEGE ADMISSIONS: IS AI USED TO READ APPLICATIONS? - MARLEE MEI Gecker, Jocelyn. “Colleges Are Using AI Tools to Analyze Admissions Essays, Applications.” AP News, 2 Dec. 2025, https://apnews.com/article/ai-chatgpt-college-admissions-essays-87802788683ca4831bf1390078147a6f. Accessed 25 Aug. 2026. Rim, Christopher. “How AI Is Reshaping The Elite College Admissions Landscape.” Forbes, 13 May 2025, https://www.forbes.com/sites/christopherrim/2025/05/13/how-ai-is-reshaping-the-elite-college-admissionslandscape/. Accessed 19 Aug. 2026. SONAR -THE INNOVATION FROM NATURE-ASHLEY EBSCO: https://www.ebsco.com/research-starters/science/sonar-technologies The Science of the Sound: https://www.usff.navy.mil/community-outreach/us-navy-stewards-of-thesea/science-of-sound/ National Sonar Service: https://oceanservice.noaa.gov/facts/sonar.html Australian Government: https://www.dcceew.gov.au/environment/marine/marine-species/cetaceans/sonarseismic-impacts
YOUR INFORMATION, MY DATA - LUANA HUA Boyd, Danah, and Kate Crawford. “Critical Questions for Big Data: Provocations for a Cultural, Technological, and Scholarly Phenomenon.” Information, Communication & Society, vol. 15, no. 5, 2012, pp. 662–679. doi:10.1080/1369118X.2012.678878. Chambers, Tod. “Taking Bioethics Personally.” Narrative Inquiry in Bioethics, vol. 3, no. 1, 2013, pp. 1–3. doi:10.1353/nib.2013.0001. Kitchin, Rob. “Big Data, New Epistemologies and Paradigm Shifts.” Big Data & Society, vol. 1, no. 1, 2014, pp. 1–12. doi:10.1177/2053951714528481. Metcalf, Jacob, and Kate Crawford. “Where Are Human Subjects in Big Data Research? The Emerging Ethics Divide.” Big Data & Society, vol. 3, no. 1, 2016. doi:10.1177/2053951716650211. Mittelstadt, Brent Daniel, and Luciano Floridi. “The Ethics of Big Data: Current and Foreseeable Issues in Biomedical Contexts.” Science and Engineering Ethics, vol. 22, no. 2, 2016, pp. 303–341. doi:10.1007/s11948015-9652-2. Richards, Neil M., and Jonathan H. King. “Big Data Ethics.” Wake Forest Law Review, vol. 49, no. 2, 2014, pp. 393–432. Rothstein, Mark A. “Translational Bioethics and Health Privacy.” Ethics & Human Research, vol. 45, no. 3, 2023, pp. 40–44. doi:10.1002/eahr.500167. Vayena, Effy, et al. “Ethical Challenges of Big Data in Public Health.” PLOS Computational Biology, vol. 11, no. 2, 2015, article e1003904. doi:10.1371/journal.pcbi.1003904. Zook, Matthew, et al. “Ten Simple Rules for Responsible Big Data Research.” PLOS Computational Biology, vol. 13, no. 3, 2017, article e1005399. doi:10.1371/journal.pcbi.1005399. MISINFORMATION AND FAKE NEWS - MAGGIE ZHANG “Journalism, Fake News & Disinformation.” Unesco.Org, 30 Apr. 2020, https://www.unesco.org/en/articles/journalism-fake-news-disinformation. Accessed 10 Aug. 2026. World Health Organization. “Disinformation and Public Health.” Www.Who.Int, 6 Feb. 2024, https://www.who.int/news-room/questions-and-answers/item/disinformation-and-public-health. Accessed 10 Aug. 2026. World Health Organization. “Infodemic.” Www.Who.Int, 2022, https://www.who.int/healthtopics/infodemic. Accessed 10 Aug. 2026. World Health Organization. “Managing the COVID-19 Infodemic: Promoting Healthy Behaviours and Mitigating the Harm from Misinformation and Disinformation.” World Health Organization, 23 Sept. 2020, https://www.who.int/news/item/23-09-2020-managing-the-covid-19-infodemic-promoting-healthybehaviours-and-mitigating-the-harm-from-misinformation-and-disinformation. Accessed 10 Aug. 2026. World Health Organization. “Immunizing the Public against Misinformation.” Www.Who.Int, 25 Aug. 2020, https://www.who.int/news-room/feature-stories/detail/immunizing-the-public-against-misinformation. Accessed 10 Aug. 2026.
ARTIFICIAL INTELLIGENCE: MENTAL TRACKING IMPACT - DANE BAES Hassan, Mohammed, and Craig Zilles. “On Students' Usage of Tracing for Understanding Code.” SIGCSE 2023: Proceedings of the 54th ACM Technical Symposium on Computer Science Education, Association for Computing Machinery, 2023, pp. 129–135. Kazemitabaar, Majeed, et al. “Studying the Effect of AI Code Generators on Supporting Novice Learners in Introductory Programming.” 2023. Qiao, Yunhan, Md Istiak Hossain Shihab, and Christopher Hundhausen. “A Systematic Literature Review of the Use of GenAI Assistants for Code Comprehension.” 2025. Rojas-Galeano, Sergio. “Tool or Trouble? Exploring Student Attitudes Toward AI Coding Assistants.” 2025. WHO OWNS OUR DNA? - ESTHER TYRNAUER American Society of Human Genetics. "The Genetic Information Nondiscrimination Act (GINA)." ASHG, 7 Apr. 2025, www.ashg.org/advocacy/gina/. Chamary, J.V. "How Genetic Genealogy Helped Catch the Golden State Killer." Forbes, 30 June 2020, www.forbes.com/sites/jvchamary/2020/06/30/genetic-genealogy-golden-state-killer/. "23andMe Data Breach: What Was Exposed, Who Was Affected, and What Happens to Your DNA Now." Security.org, www.security.org/identity-theft/breach/23andme/. "23andMe Hit with £2.3M Fine After Exposing Genetic Data of Millions." The Register, 17 June 2025, www.theregister.com/2025/06/17/23andme_ico_fine/. "6.9 Million 23andMe Users Affected by Data Breach." HIPAA Journal, 24 Apr. 2025, www.hipaajournal.com/6-9-million-23andme-users-affected-by-data-breach/. "Attorneys General File Lawsuit Opposing 23andMe's Sale of Personal Genetic Data." Legal Reader, 11 June 2025, www.legalreader.com/attorneys-general-23andme-bankruptcy-genetic-data-lawsuit/. "Genetic Discrimination." National Human Genome Research Institute, 6 Jan. 2022, www.genome.gov/aboutgenomics/policy-issues/Genetic-Discrimination. "In Hunt for Golden State Killer, Investigators Uploaded His DNA to Genealogy Site." NPR, 27 Apr. 2018, www.npr.org/sections/thetwo-way/2018/04/27/606624218/in-hunt-for-golden-state-killer-investigatorsuploaded-his-dna-to-genealogy-site. "Judge OKs Sale of 23andMe — and Its Trove of DNA Data — to a Nonprofit Led by Its Founder." NPR, 30 June 2025, www.npr.org/2025/06/30/nx-s1-5451398/23andme-sale-approved-dna-data. SMART CITIES, BUT SICKER PEOPLE? - MEHREEN MUZAFAR
Bashir. "Operationalizing Resilience for Srinagar Smart City." PM Symposium, University of Maryland, 2020. Bilal, S. "Stray Dog Dilemma: A Smart City That Forgot Public Safety." Kashmir Reader, 11 May 2026, https://kashmirreader.com/2026/05/11/stray-dog-dilemma-a-smart-city-that-forgot-public-safety/. Böbel, T.S., et al. "Less Immune Activation Following Social Stress in Rural vs. Urban Participants Raised with Regular or No Animal Contact, Respectively." Proceedings of the National Academy of Sciences, vol. 115, no. 20, 2018, pp. 5259-5264, https://www.pnas.org/doi/full/10.1073/pnas.1719866115. Bakshi, M. "Rethink Srinagar: Building a City That Absorbs Rain Instead of Drowning in It." Ziraat Times, 2026. Preferred Background Image: "A View of Srinagar, 1872." By Bishan Singh, Christie's Images/Bridgeman Images. "The Green Concrete Hardstanding." Geograph Britain and Ireland, 2016, https://commons.wikimedia.org/wiki/File:The_Green_%5E_Concrete_Hardstanding_-_geograph.org.uk__4915610.jpg. "Components of Smart City." By JudyMiao, Wikimedia Commons, https://commons.wikimedia.org/wiki/File:Components_of_Smart_City.png
SYNTHIFY
Publication: SYNTHIFY (instagram: @synthifyofficial_) Editor: Minsung Choi, Ryan Ahn, Soobin Leem, Paramith Bhandari, Irene Seohyun Lee, Jaehwan Kim Writer: Anu O, Marlee Mei, Ashley, Luana hua, Maggie Zhang, Tista Bhatia,Dane Baes, Esther Tyrnauer, Mehreen Muzafar Layout: Ayeon Cho, Teresa Nam, Minsol Kim, Jeongyeon Han, Alan Yurikh
“We live in a society exquisitely dependent on science and technology, in which hardly anyone knows anything about science and technology” -Carl Sagan