What we experience as solar eclipses are largely a cosmic accident. An eclipse occurs when observers on Earth perceive the Moon’s angular size to be roughly the same as the Sun’s, allowing the Moon to fully obscure the Sun from view. A total eclipse extinguishes daylight and can drop the ambient temperature by as much as 10°C.

If the Moon’s path about the Earth were contained in the orbital plane of the Sun – known as the ecliptic – we would expect to see a solar eclipse once every 28 days. The Moon’s orbit, however, does not stay in the ecliptic: a 5° offset between the two orbital planes guarantees that, more often than not, prospective eclipses wind up becoming disappointing near-misses. Because of this, total solar eclipses are incredibly rare, passing over any spot on the Earth only once every few centuries.
Because of their rarity, people have been fascinated by solar eclipses since the faintest beginnings of civilization. The word “eclipse” comes from the Greek ékleipsis, meaning “to abandon,” but the first recorded eclipses may have occurred much earlier, possibly as early as 3340 B.C.E.

It is dangerous to look directly at the Sun before totality – the moment at which the Moon completely obscures the Sun. Modern eclipse observers use special protective lenses, or solar filters, to block out the Sun’s rays. The filters are coated with materials that decrease the intensity of incoming light or, in some cases, block out all but a certain wavelength of light. With this equipment, even casual observers can stare safely at the Sun for extended periods of time and discern a variety of interesting phenomena. Often, coronal mass ejections, streaks of plasma cast from the surface of the Sun, can be faintly seen behind the shadow of the Moon.

During eclipses, scientists are allowed glimpses of astronomical phenomena that the brightness of our star would normally keep hidden. The 1919 total solar eclipse, for example, was used by Arthur Eddington and other astronomers to verify Einstein’s theory of general relativity: light from distant stars was slightly bent by the Sun’s enormous gravity, in line with Einstein’s predictions. Nowadays, astronomical research tends to focus on transit events occurring at other, more distant stars, rather than local eclipses. Here at McGill, researchers use eclipses in distant star systems to analyze the atmospheric composition of exoplanets, in order to determine whether they may be candidates for life outside the Solar System.

“When a planet passes in front of a star,” says Dr. Nicolas Cowan, Professor of Astrobiology at McGill, “its atmosphere appears bigger when viewed at different wavelengths of light, which can tell you what molecules are present in that atmosphere. Through this technique, we’ve already discovered lots of greenhouse gases in different atmospheres. Once we detect an atmosphere with, say, water vapour in it, then we can start to try really hard to see if we can detect other gases, like ozone or methane.”

This method, known as transit spectroscopy, will be applied to much of the data collected by the James Webb Space Telescope, but eclipses remain a unique opportunity for the public to make interesting observations much closer to Earth using simple equipment. As of March 18, municipal libraries across Montreal have begun distributing eclipse glasses, and the English Montreal School Board and LBPSB have announced that April 8 will be a pedagogical day, which means amateur astronomers of all ages will have ample time to watch the rare transit as it occurs. As part of the Eclipse Fair, several telescopes outfitted with solar filters will be set up at the downtown campus. There will also be a handful of smaller solar scopes, which reflect the light of the sun into a small viewing box and allow the Moon’s shadow to be viewed without risk.

Much of the equipment will be managed by graduate and undergraduate volunteers from the Trottier Space Institute and the Anna McPherson Observatory. “Students are heavily involved in the eclipse fair,” says Carolina Cruz-Vinaccia, Program Administrator at the Trottier Space Institute (TSI). “We couldn’t do anywhere near the amount of outreach that we currently do without them. They’re really passionate about communicating their work, and they want to make sure people know what’s going on at the university.”

Cruz-Vinaccia heads the Eclipse Task Force organizing events for the upcoming eclipse. Activities at the Fair will include a make-your-own pinhole camera station, a photo booth, and a Solar System Walk, where the planets will be arranged to scale from Roddick Gates to the McCall-McBain Arts Building. The Redpath Society, in collaboration with TSI, will be organizing a program on the cultural significance of eclipses throughout history and their effect on wildlife, while the Rare Books and Special Collections section of the McLennan Library will be displaying records of eclipses from antiquity. In the wider Montreal community, Space Explorers, a McGill student-led physics outreach program, will be holding workshops to teach elementary school students about what eclipses are and how they work in preparation for April 8.

“The idea is to give not only the McGill community, but the surrounding community the opportunity to experience this once-in-a-lifetime event together,” Cruz-Vinaccia says. “Anecdotally, people who’ve seen total eclipses before say that it’s quite a moving experience, and we feel that it would be something that’s better viewed together.”

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Ke had filed an application to allow Chen to travel with his children to China. The application included two cases as precedent: one in which a mother took her 7-year-old child to India for six weeks, and another where a mother’s application to travel with her 9-year-old child to China was approved. However it was soon discovered that these cases did not actually exist, and instead they had been fabricated by ChatGPT.

Allegedly, Ke asked ChatGPT to find relevant cases that could apply to her client’s circumstances. OpenAI’s chatbot generated three results, two of which Ke then used in the application. When lawyers of Nina Zhang, Chen’s ex-wife, were unable to locate the referenced cases, Ke realized her mistake. She attempted to withdraw the two cases and quietly provide a new list of real cases without informing the opposition. Zhang’s lawyers then demanded copies of the two original cases, leaving Ke no choice but to inform them expressly of her mistake. She wrote a letter acknowledging her actions, calling the error “serious” and expressing her regret. In an affidavit, Ke later admitted her “lack of knowledge” on the risks associated with using AI, saying it greatly embarrassed her to “[discover] that the cases were fictions.”

Justice David Masuhara, who presided over the case of Ke’s client, wrote in his ruling that “citing fake cases in court filings…is an abuse of process and is tantamount to making a false statement to the court,” going on to say that the improper use of AI could ultimately beget the miscarriage of justice. Masuhara mandated Ke to review her files and disclose if AI had been involved in any other materials she had submitted to the court.

Fraser MacLean, the lead counsel of Ke’s opposition, also emphasized the serious dangers of using AI-generated content: “what’s scary about these AI hallucinations is they’re not creating citations and summaries that are ambiguous, they look 100 per cent real.” He adds that it is important to be “vigilant” in verifying the validity of a legal citation.

Despite Masuhara finding Ke’s apology to be sincere, she will be held liable for the costs incurred by Zhang’s lawyers in remedying the confusion. The judge also acknowledged that she was suffering the effects of “significant negative publicity” following her misconduct. The Law Society of BC has also issued a warning to Ke affirming the ethical obligation for lawyers to ensure accuracy with the growing use of AI tools. In addition to incurring the debt of her opposition, Ke will also be facing an investigation from the Law Society of BC.

While Ke’s AI-generated content was removed before it could have any significant impact on court proceedings, this case underscores the ethical risks surrounding the use of AI in the legal field. Discussions are already being held around the importance of lawyers’ diligence when it comes to navigating AI tools in their work and the need for clear guidelines to prevent potential abuses of the process. Thompson Rivers University law librarian Michelle Terriss commented that this ruling sets a new precedent, indicating that “[these] issues are front and centre in the minds of the judiciary and that lawyers really can’t be making these mistakes.”

Lawyers have an ethical duty to acknowledge the risks and benefits that arise from the use of AI tools. But as the use of AI grows, new questions around its implementation in the legal field are beginning to emerge, including whether or not a lawyer can ethically bill a client for work that an AI tool performed or if using AI to handle court materials is a breach of confidentiality. The latter is especially concerning as most AI tools, including ChatGPT, do not guarantee the confidentiality of user inputs – in fact, OpenAI’s terms of service state that a user’s exchange with the program “may be reviewed” by OpenAI employees in order to improve the system, and that the responsibility of maintaining confidentiality lies with the users themselves.

While AI can provide significant improvements to tasks including electronic discovery, litigation analysis, and legal research, concerns persist about biases and prejudices in the system in addition to the potential for legal fabrication. Bias in AI technology is common and results from the training process of AI tools. For instance, Microsoft’s AI tool for text-based conversations with individuals was found to mirror discriminatory viewpoints that had been inputted in training conversations. These biases have already made it into the legal field, with a prominent example being the Correctional Offender Management Profiling for Alternative Sanctions (COMPAS) system, an AI algorithm many US judges used in making decisions regarding bail and sentencing. Investigations revealed that the system, in assessing whether or not a past offender would re-offend, was found to generate “false positives” for people of colour and “false negatives” for white people. The issue lies in the training of AI, as many are programmed to “quantify the world as it is right now, or as it has been in the past, and [to] continue to repeat that, because it’s more efficient,” says AI and robotics expert Professor Kristen Thomasen of UBC.

While the future of AI in the legal field and its ethical implications remain ambiguous, many legal and AI experts, including Professor Thomasen and Justice Masuhara, have weighed in, expressing their beliefs that an AI system could never “truly replace the work of a lawyer,” and that “generative AI is still no substitute for the professional expertise that the justice system requires of lawyers.”

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Soup and Science happens twice every academic year: once in the Fall term (usually late September), and once in the Winter term (usually January or February). Every day over the course of a week, five speakers — typically four professors and one undergraduate student from the Faculty of Science — give an overview of the aims and importance of their research work.

The talks, each lasting around five minutes, aim to provide brief but complete introductions of the speakers’ research to both current and prospective McGill students. They offer undergraduates an opportunity to interact directly with professors outside of class. Topics of the 37th Soup and Science talks ranged from evolutionary microbiology to bot detection, from drug synthesis and the development of quantum materials.

Following the lectures, audience members are challenged to a pop quiz on the topic of each presentation. Correct answers win the respondent a free “Faculty of Science” T-shirt. Afterward, soup is served for lunch — hence the “soup” in  Soup and Science — where students have the chance to mingle with the faculty, share their questions and discuss their interests. These discussions frequently end with offers for academic term or summer research projects.

Soup and Science was designed as a unique opportunity for students to meet their professors outside of the lecture hall. Science undergraduate programs often involve the successful completion of research projects, which take place either over the summer or during the academic term. For a first-time student researcher, searching for these positions can be daunting. This is where Soup and Science comes into play, with the aim to streamline this process by bringing professors and students together in a casual setting with more space for one-on-one conversations.

Rees Kassen, Professor of Evolutionary Biology and director of the Trottier Institute of Science and Public Policy, highlights the importance of promoting student-professor collaboration. He notes: “It’s hard for professors, in a lecture hall of 200 to 300 people, to interact with students. In my own research, I try to find ways to engage as many as possible. I hope to share my passion and get as many people as interested as possible.”

For newer students, Soup and Science also offers a window into the nature of research beyond the scope of their classes. Unlike cut-and-dry course content, real scientific investigations can be long and gritty, often requiring years of effort and a consistent process of trial and error to yield fruit.

“It’s really valuable for students to come and learn about science in a setting that is informal and welcoming,” says Grace Parish, an undergraduate researcher working at the Nguyen Lab in McGill’s Department of Microbiology and Immunology. She observes how “presentations are short, engaging, and accessible, helping students figure out what they might be interested in without getting them bogged down in the details.”

Contrary to departmental seminars which tend to involve faculty members and graduate students in specific fields of research, Soup and Science talks are geared toward introducing research to an audience with little to no expected background. The relatively relaxed tone of the event serves to spark the curiosity of students and faculty alike, engaging them in a way where they feel more free to learn.

“These presentations really show the different things people do across the Faculty of Science,” says John Stix, Professor in the Department of Earth and Planetary Sciences and Associate Dean of Research at McGill. He notes that while students are the main audience, the event is also of value to McGill professors as well. “[Researchers] tend to pigeonhole ourselves in our own fields, and we don’t know what people do across disciplines.”

Stix highlights the interdisciplinary benefits of Soup and Science in its ability to bring people from largely disparate fields, like geography and chemistry, together in the same room. For himself and many other professors, Soup and Science lectures also offer new perspectives on their own work in relation to other fields they are not necessarily familiar with. “Over time, people often find connections — an instrument, a computer program — between fields. The goal of Soup and Science is for both students and professors to get exposure to see the amazing work being done here at McGill.”

To learn more about Soup and Science, you can visit their website at www.mcgill.ca/science/research/undergraduate-research/soupscience, as well as view a selection of past talks on the McGill Science and McGill University YouTube channels.

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From January 19 to 21, the Canadian Conference for Undergraduate Women in Physics (CCUWiP) saw Canadian physics undergraduates grace the halls of McGill University and the Université de Montreal (UdeM). Over 100 delegates from underrepresented groups congregated to celebrate their accomplishments in physics and discuss an inclusive and fairer future for science.

Over three days, delegates partook in career panels, a grad school fair, and research project presentations – the usual fare at academic conferences. Student conferences have long served as meeting points for aspiring undergraduates to showcase their research and meet peers from other institutions. However, CCUWiP also served a third purpose: for delegates to share their experiences as coming from underrepresented groups in a traditionally white, Western, and male-dominated field. This shone through in the stories attendees brought to the table: tales from the many walks of life travelled by undergraduate participants.

CUWiP began in the US to “help undergraduate women continue in physics by providing them with an opportunity to experience a professional conference.” Organized by the American Physical Society and first hosted by the University of South California in 2008, they provided a unique venue for female undergraduate students in physics to meet other women in the field.

The first Canadian CUWiP was organized in 2014 by the Canadian Association of Physicists (CAP), which represents physicists across Canada. Coincidentally, this first conference was also held at McGill University by two of this year’s speakers: Dr. Brigitte Vachon, associate professor of physics at McGill; and Dr. Madison Rilling, executive director at Optonique and then-student in Joint Honours Mathematics and Physics.

This year, a decade later, physics undergraduates returned to Montreal to honour the gruelling work of undergraduate researchers and mark the progress made toward bridging the gender gap and other inequities in physics.

The Gender Divide in Physics

In physics, the gender gap is more of a gaping void. According to a 2021 analysis by Statistics Canada, women are 36.4 per cent less likely to enroll in a post-secondary STEM major than men. A 2023 report by the CAP found that women make up only 35.3 per cent of undergraduate physics majors across Canada: this figure sinks to an abysmal 22.9 per cent for doctoral students. This stands in stark contrast to other STEM fields. In chemistry, for instance, 40 per cent of students have historically been female-identifying. As a result of this gender stereotyping, many women are likely to leave or avoid entering physics careers entirely. 

“In my undergrad, there was a one-to-five girl-boy ratio in physics,” recounts McGill physics professor Bill Coish in an interview with the Daily. He notes that “the balance has improved quantifiably” though there is still progress to be made: “Conferences [like CCUWiP] are a good start. We need more outreach at an early stage […] for example, you can look at the work done by the Physics Outreach Committee at McGill.”

Early education, as Professor Coish points out, is one of the major hurdles to achieving gender parity in physics and other STEM fields. Gender discrimination in the education system represents a key factor in this imbalance. A 2020 study published in the Journal of Applied Developmental Psychology found that “Boys are more likely than girls to say that their own gender group ‘should’ be good at STEM.’’ Self-reinforcement of gender stereotypes throughout childhood, along with long-existing cultural and socioeconomic barriers against women, have long contributed to the gaping gender disparity in STEM fields.

This discrimination continues into the professional realm. Day two of CCUWiP saw astrophysicist Jocelyn Bell Burnell share her experiences as one of the first female graduate students in astronomy at the University of Cambridge. While working toward her PhD at Cambridge, Burnell discovered a series of periodic, localized blips from radio telescope data – signals she and her team would later identify as pulsars, a type of rapidly-spinning neutron stars. Despite her critical contributions, she was denied the 1974 Nobel Prize in Physics for the discovery of pulsars, which was instead awarded to her supervisor, Anthony Hewish, and his colleague Martin Ryle.

Gender-based discrimination is systemic in physics, and has persisted before and since Burnell’s time as a graduate student. A cross-cultural study, published in Nature in 2020, showed that women communicating in STEM were frequently characterized as “bitchy,” “bossy,” and “emotional” by correspondents. These biases, the researchers concluded, indicate that women in STEM find themselves “in a more vulnerable position when communicating publicly about their work, which could have implications for them participating fully in their careers.” This research suggests that a deep, cultural restructuring of gender attitudes in academia is necessary in order to eliminate the gender gap in STEM.

For Ivanna Boras, an engineering physics major at Queens University, such attitudes are the daily reality of women in her department. “Our voices tend to be ignored,” she says. “As a result, we try to band together. Luckily, it’s gotten better during upper years.”

Vanessa Smith, Vice President of the Dalhousie Undergraduate Physics Council, says that at Dalhousie, “the undergraduate physics body has a 50-50 split, but there’s only one [fully tenured] female professor in the Department of Physics.” For her, this highlights the need for continued and sustained progress toward gender equality in physics.

A Safe Space to Share

For delegates, CCUWiP represents an open, non-judgmental space for them to voice their experiences with discrimination in physics, gendered or otherwise. It also provides a perfect venue to exchange ideas and stories – not just academic ideas, but also personal anecdotes of their journeys through the realm of physics.

Between keynotes and workshops, days two and three of CCUWiP also saw the much-anticipated oral and poster presentations. The poster presentations were laid out in a science fair-esque manner, with delegates free to move between posters and discuss each other’s work in an informal setting. Student research took centre stage, with the projects exhibited ranging from topics like improving wildfire prediction and the acoustics of the human ear, to exploring the exoplanets orbiting distant stars. Alongside research work, initiatives in science outreach and education were also featured, as well as projects geared toward equity, diversity and inclusion.

During coffee breaks, delegates had the chance to share personal stories in physics. Michaela Hishon, from the University of Guelph, reminisces: “What sparked [my passion] was the mentors I had growing up. My high school teacher majored in geophysics: she encouraged and inspired me to pursue my current work in medical physics and outreach.”

For some, CCUWiP was a chance to speak out about issues they cared about. Raina Irons, from the University of Toronto, Mississauga, took time to highlight the importance of “creating opportunities and funding for Indigenous students interested in physics and astronomy.” She notes how socioeconomic hurdles are especially high for aspiring Indigenous students in STEM.

Undergraduates also had the chance to learn about lesser-known, yet equally crucial, careers in physics. One keynote saw Dr. Rilling speak about her work in science policy: a field which aims to bring the interests of scientists to political stakeholders and achieve support for science on a governmental level.

To many, CCUWiP stands out from other conferences in the way it promotes collaboration over competitiveness. “CCUWiP fosters a sense of community,” says Leslie Moranta, a PhD student at the Institut Trottier de recherche sur les exoplanètes at UdeM. “Being a woman in STEM can often feel isolating, and CCUWiP is a place for us to share our stories.”

For many underrepresented groups, conferences like CCUWiP are a unique chance to meet like-minded peers, share their experiences and accomplishments, and open the next page to a new, more inclusive chapter in physics.

CCUWiP 2024 was organized by Audréanne Matte-Landry, Joël de Leon Mayeu, and Pénélope Glasman from Université de Montreal; and Olivia Pereira, Simone Têtu, Sloane Sirota, and Ruby Wei from McGill University.

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Now, according to a new Nature article, it could even usurp silicon as the most important element in all modern electronics, from smartphones to the most powerful supercomputers.

Researchers from the Tianjin International Center for Nanoparticles and Nanosystems at Tianjin University in China (TICNN), and the Georgia Institute of Technology in the US were able to make graphene behave as a semiconductor, a material that can alternate between conducting and blocking electricity.

Professor Ma Lei, team co- head and director of the TICNN, says that this breakthrough “can truly make graphene electronics practical in the future.”

In the last century, silicon proved quintessential to the development of modern electronics because of its ability to regulate the flow of electrons: stopping them or allowing them to pass like a traffic light.

All electronic devices are based on the motion of electrons, tiny, negatively-charged particles that swarm around an atom. Conductors allow electrons to move freely inside the material, while insulators prevent the electrons from moving at all. Semiconductors are special in that they can be “switched” to behave as either an insulator or a conductor.

Think of an atom as a kitchen cabinet. In atoms, electrons must stay within their shelves and can only move back and forth between them. Above the valence shell — the highest “shelf ” within the atom exists the conduction band, which allows electrons to flow between atoms. Imagine two cabinets side by side, with their tops sitting flush: the two units are effectively connected, allowing you to slide an object — your electron — from one cabinet onto the other.

In conductors, the valence band and the conduction band are linked (electrons can move freely to and over the top of both cabinets). In insulators, electrons cannot easily move out of their valence bands and into the conduction band (electrons are stuck in the shelves underneath).

In semiconductors, the valence and conduction bands have a narrow band gap. At low energy, the semiconductor behaves like an insulator: valence electrons cannot escape to the conduction band. However, if you inject energy (i.e. photons) into the atom, its electrons can easily jump onto the conduction band and begin moving between atoms, as in a conductor.

Graphene and other carbon- based materials have long been pursued as an alternative to silicon. The problem with graphene is that it is a perfect conductor: zero band gap with electrons freely travelling around, making it unsuitable for the same applications.

Research has since worked on synthesizing a graphene-based material which does exhibit
this band gap. In 2001 Walter de Heer, Regent’s Professor of Physics at Georgia Tech and co-head of the research team, proposed the possibility that epitaxial graphene, a type of graphene formed by heating silicon carbide crystals, could be used to construct this band gap. The first layer formed by this process, which still remains attached to the crystal, behaves as an insulator. In theory, if this first layer was extracted and then overlaid onto a second sheet of regular, conducting epigraphene, the resulting material would behave as a semiconductor.

Picture leaping over a puddle of mud: with enough speed, you could avoid the slow trudge across the insulating layer and simply jump across.

Over the next two decades, de Heer’s team at Georgia Tech worked with nanoscience researchers at Tianjin University to refine this production technique. A major hurdle was low quality of epigraphene: the insulating layers produced were riddled with imperfections. To resolve this, the researchers employed “quasi- equilibrium annealing,” baking the silicon carbide crystals at a precise series of temperatures to produce a smooth insulating layer. Now, for the first time, scientists were able to implant the band gap in graphene, by welding the insulating and conducting layers together.

“The reason our research is valued is that it can truly make graphene electronics practical in the future and remove the biggest obstacle [to its commercialization],” explains Ma. However, he cautions that graphene still needs to undergo further testing and commercialization: it might take 10- 15 years for it to be able to compete with silicon in the industry.

In addition to replacing silicon, the advent of graphene-based chips would transform all of modern electronics. Graphene is able to conduct electrons along its edges, allowing future chips to no longer contain metal wires. Moreover, the average distance travelled by electrons through graphene is several times the distance in silicon. This allows the electrons to exhibit quantum properties like interference, which has crucial applications in quantum computing.

“To me, this is like a Wright brothers moment,” says de Heer. He notes that planes were “the beginning of a technology that can take people across oceans,” and that the same could happen with graphene-based electronics.

The post Silicon or Graphene? appeared first on The McGill Daily.

This interview has been edited for clarity and brevity.

Andrei Li for The McGill Daily (MD): Tell me a bit about yourselves. How did you become interested in neurophysiology and education?

Phoenix and Aidan (P&A): Our names are Phoenix and Aidan and we are the co-founders of the ThinkSci Outreach Program. We became interested in neurophysiology as I [Phoenix] study physiology and Aidan studies biochemistry. Aidan and I met when we took our first Intro to Physiology course together three years ago.

I’d say we both geeked out over neurophysiology together through that course and then both took courses throughout our degrees to learn more about it and the applications of neuroscience. We’ve both taught in different settings, I [Phoenix] personally have varied experiences from coaching to teaching. Pedagogy has just been something I’ve always loved, been interested in, and studied.

MD: How did you come up with the idea of the workshops?

P&A: In starting ThinkSci, our main mission was to empower youth from underrepresented groups to pursue undergraduate and graduate careers in physiology and STEM at large. When developing our workshops, we aimed to leverage our experiences on both sides of the coin, as both teachers and learners. We wanted them to be fun, engaging, and for students to leave the workshop feeling empowered, that they could see themselves doing that same work in the future! In our workshops, we use the SpikerBox: a bioamplifier and interactive learning tool to visualize neurological signals on your phone and laptop. This tool was developed with the goal of making learning about neuroscience more accessible to a younger demographic of students, since often, the cost of high-level neurological tools limits accessibility.

Aidan and I reflected on the lack of accessibility in our former high schools when it came to innovative tools used to engage students in science. This is when we decided to start ThinkSci: to introduce the Spikerbox in high schools to provide the opportunity to learn about neuroscience to a more diverse set of students.

MD: Could you give me a rundown of what the average workshop day looks like?

P&A: The workshop is designed for a group of roughly 40 students. The facilitators act as “ER doctors” presenting three patient cases and ask participants to study each patient’s condition. Students are expected to step into the shoes of neurophysiologists: to use the tools found at their stations to design experiments, make hypotheses, and draw conclusions. Students get to work in groups of six, with mentors available for guidance throughout the workshop.

In the workshop, the main tool we provide students is the SpikerBox. As an example, one of the patients has hypoxia – lack of oxygen – caused by a blood clot. Students then design an experiment to visualize how the brain sends signals to the rest of the body in hypoxic versus normal conditions.
The tissues used in the workshop are crickets and cockroaches. In the workshop, we walk students through all steps of preparation: cockroach anesthesia, leg preparation, along with a discussion on the ethics of using live tissue for science.

We end with a final discussion where we share knowledge and experience on the lack of representation amongst certain communities in STEM. Students are encouraged to share their first-hand experiences with the facilitators and outreach mentors. Not only do we offer students the possibility to see themselves becoming neurophysiologists in the future, we also validate their current and past experiences in confronting inequality, lack of accessibility, and underrepresentation by providing a safe space for them to share. We hope their experience in our workshop provides them with the tools and resources necessary to advocate for themselves throughout their journey and build a community of support.

MD: What was the most challenging part of starting ThinkSci?

P: Managing the many hats we had on. From recruiting, to teaching, to funding, I would say all of our combined skills are being put to use. As two undergraduate students, it was definitely an endeavour to try to convince organizations and institutions to fund our initiative with little to no proof anything would come of it. But with just the right amount of will and some really awesome investors, anything is possible. We are so grateful to be funded by both the Canadian Association of Neuroscience and the Quebec Bio-Imaging Network.

MD: What has been the most rewarding part?

P: The most rewarding part has to be the workshops themselves. Seeing and interacting with young scientists, seeing the lightbulb go off when they learn something new and guiding them through problem-solving in the workshop.

Chloe (C): Getting to see the four or five students that stayed back after the presentation to ask questions and just talk to us about our own projects was extremely rewarding, since we could see that they really found an interest in neurophysiology.

MD: How do you hope to develop ThinkSci in the future?

P&A: In ThinkSci’s first year, we’re really focused on creating a knowledge-sharing hub of individuals from all walks of life, at all stages in their careers, passionate about neurophysiology, pedagogy and equitable access in STEM. Currently, we operate in Montreal and Ottawa. In the next few years, we hope to reach even more youth.

We hope to expand our reach to more schools and institutions in both cities, and to more locations across the country, including Indigenous and remote communities. I have faith in the awesome team we have this year: we’re constantly adapting our initiatives to the needs of the communities we work with.

MD: What advice would you give to youth who want to go into the health sciences and/or STEM?

P: Never forget why you’re pursuing your goals. Taking a pause to reflect on the “why” or “how” has always helped me refocus. It was important for me, as a first step to acknowledge the obstacles I faced through my journey. But it’s even more important to remind myself why I aspire to do what I aim to, as this gives me the strength to keep pushing.

Allow yourself to let these goals change and evolve over time. Don’t see this as “giving up,” but rather an opportunity for growth.

C: I’ve found a lot of more experienced students here to emulate as I go through university. Thinking about what they would do in certain situations or how they would approach certain opportunities has really helped me achieve my goals. I believe ThinkSci does this for a lot of students as well, since the organization really works to connect mentors and their students on a personal level. Students can really see themselves in their mentors.

To learn more about ThinkSci, and their programs you can follow their Instagram at @thinkscioutreach, and learn more about their work at can-acn.org/thinksci-outreach-program-wins-a-can-advocacy-award/.

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Suddenly your morning trip to Starbucks is a lot less ordinary. Everyone, from the cashier to the bus driver to the receptionist and your boss, are all talking about what they believe the aliens from planet Xorg look like. Finding life outside of Earth has always been one of the most captivating pursuits in science. As a space scientist myself, I can attest to the fact that the question of alien life will come up without fail in any given public talk related to astronomy.

Recently, it seemed as though internet publications had beaten scientists to the punch with announcements that evidence of life had been found in the Exoplanet K2-18 b. This came as quite a surprise to the scientists who had published their findings about this planet but had no recollection of telling the media that they had confirmed the existence of extra terrestrials.

What happened was that some of the conclusions of their published findings were spun into very misleading headlines. They did, however, prove to be quite effective in terms of how many people clicked on those articles online.

Such misrepresentations of science in the media, especially online media, have been happening more frequently in the last ten years. The business model of high engagement equals higher profits has created an online media ecosystem that thrives on sensationalizing scientific findings. By sensationalizing I mean that a lot of facts are distorted to attract more readers.

For context, what exactly is this planet K2-18 b? It is a planet that is two and a half times as wide and eight times as massive as Earth. It orbits a small red dwarf star at a distance of 124 light years from our solar system. K2-18 b has half the Earth’s density, suggesting the existence of light material such as water and ice on the planet. Furthermore, the planet was found to orbit near the habitable zone of the system, which fuelled speculation on whether K2-18 b could harbour life. Discoveries such as the evidence of water vapour and hydrogen gas in its atmosphere by the Hubble Space Telescope presented this world as a Hycean world candidate (a planet with a hydrogen atmosphere and a global ocean).

This wasn’t the first time that planet K2-18 b made an appearance in the media as a flag bearer for fake alien life. The same happened when this planet was discovered in 2015 and several online publications described it as a planet with a global ocean. While the idea that K2-18 b could potentially have water was proposed based on the density of the planet, the astronomers who studied this world simply mentioned it as one of many possible conclusions to their observations.

Similarly, in September of this year, spectral data from the NIRISS instrument of the James Webb Space Telescope showed evidence of methane, carbon dioxide, and hints of dimethyl sulfide (DMS) on K2-18 b. Among these, DMS was predicted to be a potential biomarker, but the data was not strong enough to say that the DMS came from life. The conclusions of the paper on these findings, which appeared as a letter in the Astrophysical Journal, were that DMS might be present in the atmosphere of K2-18 b but that it would require much more data to confirm. While the possibility of the origin of DMS being biological was brought up, considering it a certainty would have been scientific malpractice.

Several news outlets, however, spun these findings in a different light. USA Today led with the headline “NASA says Exoplanet named K2-18 b could harbor life.” CNET had the headline “Webb finds potentially habitable planet might be an ocean world,” while The Guardian sounded off the headline “NASA says distant Exoplanet could have rare water ocean and possible hints of life.” Many of these articles cherry-picked findings from these studies while omitting the researchers’ words of caution. One might argue that sensationalizing science will get more engagement from the public. But researchers would say that they still observe strong public engagement without having to exaggerate scientific results. When it comes to news, simply announcing findings as they are is the best course of action.

Over time, media exaggeration of science erodes the public trust in science and scientific institutions. It is the collective responsibility of researchers and the media to ensure clear communication between science and the public.

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This interview has been edited for clarity and brevity.

Andrei Li for The McGill Daily (MD): Could you tell me more about the Space Generation Advisory Council?

Sobia Nadeem (SN): SGAC is an international organization made up of young space technology professionals. It’s free to become a member, and you can get more involved by applying to project groups: sustainable policy, aerospace research, etc. Several of our working groups have the opportunity to present at the UN Committee on the Peaceful Uses of Outer Space [COPUOS]. People involved in SGAC also regularly publish their work at conferences, such as the International Astronautical Congress. The SGAC gives you the insight and ability to contribute to space technology at an earlier stage of your career.

MD: Could you tell me more about the history of how this hackathon came about?

SN: The hackathon falls under the umbrella of our Giant Leap Initiative for gender equality in STEM. Our event is just before the UN Office for Outer Space Affairs [UNOOSA] Space4Women conference happening this week in Montreal. The hackathon is not directly affiliated with the conference, but it does give a taste of what it’ll talk about. In our hackathon, students get exposure to outer space and space exploration under the hackathon theme: this year, supporting women and gender minorities in remote communities.

Yulia Akisheva (YA): The idea started with a conference in Toulouse, France, with a local event focused on women in space. We built on that event — published articles, did outreach, kept in touch with the space community — and we ended up going to South Korea in 2022. Our mission was inspired by The Moment of Lift by Melinda Gates: empowering women to shape their own futures. The hackathon is only one of our many projects that focus on this topic.

Nathan Schilling (NS): The hackathon grew out of the UN Sustainable Development Goals, particularly in eliminating the gender gap in science. We’re focused on getting more women into space, into STEM, and using space tech to support women worldwide. Our first hackathon, in Daejeon, South Korea, ended with the winning team being able to propose an idea and actually begin to commercialize it. Our overall goal is to get more women, minorities, and youth into STEM.

MD: Broadly, what are the objectives of the Our Giant Leap Hackathon?

NS: Our objectives are twofold. First, to get teams to find solutions to the gender gap through space technologies. This year, we’re looking at leveraging space technologies to support remote communities worldwide. Second, to get career developments for hackers — networking with mentors, industry specialists, and fellow hackers. We’re really invested in the international dimension — getting hackers connected and fostering opportunities for global collaboration.

MD: How did you, personally, get involved with the SGAC?

SN: I was previously a director for SEDS [Students for the Exploration and Development of Space]. I loved the work I was doing, but I wanted to have a greater impact on the international scale, and SGAC gave me that opportunity.

NS: My ex-girlfriend faced a lot of sexism in the space industry, and I really felt a need to address this issue. When I learned of the SGAC and the hackathon, I thought: here’s an opportunity to work on an issue I care about.

MD: What were the most challenging aspects of organizing this hackathon? The most rewarding?

NS: The most challenging part of this was adjusting to Montreal. I work in logistics, and there was a disparity between previous, structured events where you knew where everyone would go to lunch, for instance, and this new event of the hackathon, which is less structured and has more uncertainty, in a new city for me. The most rewarding part was serving breakfast, serving lunch, getting to meet all these talented hackers: helping people with small actions.

SN: I previously organized events for the Canadian space sector — it was really familiar and I knew the lay of the land when it came to reaching out to Canadian professionals. In SGAC, I had a very different experience on the international team, so it’s been a challenge and a learning experience. This hackathon has been very rewarding, especially with attracting an international audience, we even have a team participating from the European Space Agency. It was very fruitful to showcase the Canadian space sector to international teams.

People don’t think too much about Canada when it comes to space. It’s unfortunate, because at conferences we stick together and are really tight-knit. It’s great having people come to our turf. Everyone is very supportive, and it’s really easy to build new bonds.

MD: What advice would you have for youth who want to get into STEM, but aren’t sure how they would want to?

YA: Join a network, go to events, and talk to people. Don’t hesitate to reach out in a meaningful way to people you are inspired by. The SGAC is a good resource: we’re the largest group of young space professionals globally, affiliated with the UN, with 160 countries represented through 25,000 members. You will be able to find someone, whether it be a sponsor or a mentor: it’s much easier than it seems. Do a project — hackathon, design competition, building a model rocket, anything.

SN: One thing that’s really daunting is that in STEM, there might not seem to be many role models you relate to. Echoing what Yulia said, it’s very important to reach out, find people who have walked your paths in life and share your perspectives. I got into space through mentorship; I failed two of my courses in my first year and put a lot of unnecessary pressure on myself. Through support, I discovered that school is just a tool to get you where you want to be. Failure is another part of life: use it to get you where you want to be. You don’t have to be at the top of your class to succeed.

NS: First, find people who you can connect with in terms of interests and identity. Reach out! Don’t be afraid to cold call, cold email, cold connect through Linkedin and so on. It’s really easy nowadays with technology. Be genuine with your passion, show that you care, and ask for advice. Often, you’ll have a long-term partnership develop. Courses aren’t everything — getting straight As isn’t enough. You’ll get more mileage by joining projects, doing research, and getting hands-on experience in the fields you want to work in. Get exposure and experience, because in the end, that’s the most important part.

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Such everyday euphemisms come from a tech sector dominated by a handful of powerful companies collectively known as “Big Tech.” However, their dominance might be at risk. Last month, the United States saw the beginning of two legal battles that could permanently reshape the tech landscape into one without Big Tech monopolies.

On September 12, a long-awaited trial began against Google in Washington District Court. Filed by the US Department of Justice (DOJ), it purported that Google had deliberately blocked smaller companies from competing in the search engine industry.

Two weeks later, on September 26, a joint suit was filed against Amazon by the Federal Trade Commission (FTC) – the US agency responsible for market fairness – and several state attorneys.

Both legal cases claim that the two key Silicon Valley companies – pillars of the US tech landscape – abused their power to maintain near-total control over the online shopping and search engine industries.

These two legal challenges are the largest against the American tech sector in the last 20 years, comparable only to the landmark case against Microsoft two decades ago. In 2001, Microsoft agreed with US regulators to allow users to download and operate non-Microsoft programs, like Java, on Windows PCs.

If either case is settled favourably for prosecutors, the victory could signal a weakening of Big Tech’s long growing power over the tech industry. Ultimately, they might herald the dismantlement of Silicon Valley’s griphold on the tech industry. Elettra Bietti, an associate professor at the Northeastern University School of Law, sees this as greater public inclination for “more proactive enforcement against Big Tech.”

The US government’s actions come at a time of unprecedented Big Tech influence over not only the tech sector, but the world economy as a whole. According to Investopedia, seven out of the ten largest companies in the world (by market cap) are American tech companies.

In turn, Big Tech companies have near-complete control of their respective industries. Amazon dominates American online retail with 37.8 per cent of total sales, while Google accounts for 83.5 per cent of the global search engine market.

Silicon Valley companies’ supremacy has created a perfect breeding ground for monopolistic practices. The DOJ alleges that Alphabet, which owns Google, spends billions every year on ensuring Google is the default search engine used by its business partners, such as in Apple devices. Such practices are exclusionary, and are aimed at preventing smaller search engines from gaining users, argues the DOJ.

Similarly, the FTC claimed that Amazon has used its “monopoly power to inflate prices, degrade quality, and stifle innovation for consumers and businesses.” In 2021, the Biden administration appointed Lina Khan, a prominent critic of Big Tech and particularly of Amazon, as the new chair of the FTC. While still a law student, Khan was notable for publishing an influential paper arguing Amazon’s pricing practices were anticompetitive, squeezing small businesses out of the online market by limiting their profitability.

The US government’s moves come late into a tech economy dominated by large corporations. Since the Microsoft case, little action has been taken against the takeover of fledgling tech sectors by established companies. Some have attributed this to the US government’s inability to adapt to the rapidly-evolving tech industry. Others have argued that the federal government’s policy of corporate deregulation, a philosophy passed down from the Reagan era, is the primary reason for the slew of big corporation takeovers, both in Silicon Valley and in other industries.

Globally, the US still remains behind many other countries in holding tech companies in check. Just this summer, the EU won $1.3 billion USD in compensation from Meta for transferring European user data to the US, in breach of EU data privacy laws. And in 2021, online retail giant Alibaba was fined a record $2.8 billion USD by Chinese regulators for abusing merchants with its monopoly powers.

Nonetheless, the current actions of the US government  are likely to come as a relief to smaller companies and consumers alike. In the past, antitrust lawsuits put forward by private plaintiffs have often been rejected by federal judges. A notable example is Epic Games’ 2020 lawsuit against Apple’s 30 per cent commission on web store products, which was thrown out on the grounds of insufficient wrongdoing by Apple. For Eleanor Fox, a law professor at New York University, private suits are often viewed as petty by judges, and are not taken seriously.

Now that the US government is stepping up to confront the monopolised tech sector, it remains to be seen whether the hold tech monopolies have over our lives will be weakened or not. Only time will tell if the US will rein back the juggernaut of Big Tech.

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Current superconductors need to be cooled to close to absolute zero (-273°C). This requires bulky and highly expensive equipment. Niobium-titanium alloy, the superconductor used in high-speed maglev trains, requires temperatures of just 11°C.

The existence of any room-temperature superconductor would revolutionize nearly all modern technology. In power grids, room-temperature superconductors would save up to seven per cent more power while taking up less space than traditional metal wires, both considerable gains on a global scale. They would allow for electric motors with near-perfect efficiency. They would make quantum computers not just scientists’ toys but products accessible to all.

So when, in July, a team of South Korean scientists claimed the creation of a room-temperature superconductor using everyday materials, the viral frenzy was all too predictable.

In its name, “LK-99” signifies a promise. Short for “Lee Kim 1999” — named after lead researchers Lee Sukbae and Kim Ji-Hoon and the year they started this project — LK-99 is a testament to the time and work poured into making a dream come true. 

Alex Kaplan, a Princeton graduate, was one of the first to break the news. His tweet amassed millions of views in the following days, accelerating the growing online hype. Seasoned researchers and amateurs alike raced to replicate LK-99’s incredible properties. Videos of floating rocks quickly flooded the Internet, purporting successes at demonstrating LK-99’s esoteric properties. Tech entrepreneurs rallied their followers toward investing in this “new big thing.” Tech stocks soared while memes and Reddit discussions spread as freely as electrons in a superconductor. 

LK-99 became the equivalent of the sci-tech community’s new Taylor Swift album. It became the trend that everyone — from the average Joe to the Silicon Valley mogul — was buzzing about. 

“On the other hand, reactions from the scientific community were more subdued. Researchers in the field treated the results with natural skepticism. Historically, many supposed “room-temperature superconductors” had already been synthesized through the years, only for their findings to be questioned after careful review. Issues with data accuracy disqualified most such findings. Academic misconduct also tainted the playing field far before LK-99 came along. 

Crucially, LK-99 also failed to exhibit the  Meissner effect, a critical test for true superconductivity. When a substance begins superconducting, any magnetic field will be expelled: this causes, for instance, the characteristic floating above a regular magnet seen in popular science displays. LK-99 was found, by researchers from Nanjing University, to not display the Meissner effect.

Still, the hype continued. A disconnect widened between rigorous science and the general public. On one side stood the more likely reality: that LK-99 was yet another dead end, and the search for a room-temperature superconductor was far from over. On the other loomed the well-intentioned but misguided notion that somehow LK-99 would be the “eureka” moment of our time.

Fuelling these misconceptions, more than for previous room-temperature superconductors, were those Silicon Valley entrepreneurs, afraid of stagnation and all too happy to jump on the bandwagon if it might stave off the current boom-and-bust cycle.

Gradually, as researchers failed over and over again to reproduce the South Korean group’s results, the body of evidence grew against LK-99’s status as the first-ever room-temperature superconductor. Researchers realized that many of LK-99’s properties, including the floating rock videos, were the result of normal ferromagnetism.

Other issues began appearing. Complaints were put forward by the work’s co-authors, purporting that the paper had been put forward for publication without their consent. At the time of writing, these allegations are still under investigation. 

In the end, LK-99 didn’t become the shining arrow pointing to a new era of technology. It failed on the promise in its name, was hijacked by sharp-smelled tech execs, and exposed a lack of scientific understanding in the general public . Its saga shines light on the growing divide between the unforgiving truths of scientific progress, and its oversimplified interpretation in pop culture. 

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I was first initiated into the world of personality tests as a teenager. Around the same time I was exploring my sexuality, other identifying markers became available to me – namely, the microlabels assigned to me by quizzes on the internet. First, lauded by zealous middle school teachers, there was a quiz to discover our learning types, which was a product of the paid platform Career Cruising. The assessment was called Learning Styles Inventory, and it consisted of a mere 20 questions to determine whether we were visual, auditory, or tactile learners. A few months later, our class did a Myers-Briggs test. As a lover of systems, the acronyms and neat classifications were a welcome mindframe to me. 

The draw toward self-exploration was a healthy impulse. Especially as young adults, there are a lot of unkowns one has to grapple with: Who are you? Who do you identify with? Who is your community? 

The potentially destructive facet is the advice that is given as a consequence. The learning type quiz dictates which educational environment you will thrive in. The Myers-Briggs test identifies supposed flaws in your personality. There is also the Big Five Personality Test, which claims to identify your openness, conscientiousness, agreeableness, extraversion, and neuroticism. Another popular personality test, Enneagram, has a focus on self-improvement, meaning you are expected to rehabilitate your personality based on your results. 

Advice that is anything other than individual is doomed to ignore traits – or combinations of traits – that are unique to a person. These tests also work on an assumption that we can accurately interpret possibly unclear questions and that we are able to accurately identify some pretty sweeping personality traits in ourselves. 

Take a look at the Learning Styles Inventory, for example. The question, “If learning to cook, I would rather: a) follow written recipes; b) create my own recipes, tasting as I cook; or c) be told how to cook” simplifies an activity with dozens of factors. For instance, the answer will change based on experience with cooking, and it is hard to answer if someone has no cooking experience at all. The question, “I find it easiest to remember: a) names; b) things I have done; or c) faces” is simply baffling, especially given that option b) can encompass all of human memory. Even ignoring the possible confusions in these questions, they point to superficial qualities in a person and assign them undue importance. At best, the Learning Styles Inventory is a frivolous introduction to learning styles, but the corresponding study tips imply that the Inventory tries to take itself seriously. There is no information on the Career Cruising website concerning the reasoning behind the questions. 

The Big Five test is a more comprehensive questionnaire, allowing you to do a 300-question personality test. Although I imagine these results could be quite specific to the person, spending so much time self-analyzing can become unhealthy. It is a way of thinking about identity that is divorced from the community around you. With 300 questions, trivial subjects surface. The effect of “I love action” or “I go straight for the goal” on any of the Big Five traits is never explained. The calculations behind the results are a black box, and there is no way to discern how the test uses the data it collects to form its conclusions. While the Big Five test was created by psychologists with the backing of evidence, some online assessments have been revealed to produce sexist results – ranking women as more disagreeable than men for the same traits depending on what gender one self-identifies as. This is because results are shown in comparing other test-takers with the same gender.

The Enneagram test attempts the most ambitious stab at your personhood. According to the website Truity, the Enneagram identifies a core belief that “drives your deepest motivations and fears — and fundamentally shapes a person’s worldview and the perspective through which they see the world and the people around them.” The framework is self-confident, but Professor Sanjay Srivastava of the Department of Psychology at the University of Oregon points out the lack of evidence and scientific theory behind the test. The fact that Enneagram does not acknowledge the lack of scientific background suggests that it is a commercial rather than evidence-based model.

Myers-Briggs has accrued credibility by basing the test off of psychologist Carl Jung, and approximately 3.5 million tests are administered each year. Despite the confidence in Myers-Briggs, it lacks empirical evidence to support the veracity of claims to capture someone’s personality. In an interview between a University of Wharton journal and Merve Emre, an associate professor of English at Oxford University, Emre claims 50 per cent of people who take the test receive different results a second time. Emre also points out that when participants disagree with their results in workplace evaluations, they are often told by MBTI test administrators that they’re not interpreting the results correctly. 

If anything, these tests are able to  monitor our perception of ourselves – a very subjective experience that concrete questions can never fully account for. 

Yet another flaw is that these tests are static. They record a moment in time, while our experiences in life are constantly shaping how we interact in the world. Another pitfall is confirmation bias, a phenomenon where we are more likely to believe evidence that supports our existing beliefs. Thus, when we receive results that validate our opinions of ourselves, we may accept them without enough critical consideration. 

Finally, many of these personality tests cater to a specific audience – they are not universal. This was recently found in a study on the Big Five Test: a translated version of the test was given to a small South American tribe, and the results did not cluster into the expected five types. Not only do the tests lose accuracy when applied across various demographics, but they also reflect a rigid interpretation of personality. To put stock into such models limits our perceptions of people through a Western gaze.  

Although I can understand the temptation to neatly classify a chaotic assortment of values and quirks, I am learning to embrace the ways humans are unable to be described in a paragraph. I am also learning to describe myself based on the actions I do for others and the way I react to real-life experiences, rather than trying to extrapolate meaning from vague statements such as “I am always prepared” (the Big Five). Although I will keep doing personality tests for fun, I will no longer be putting stock in them. 

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It is tempting to jump to a first conclusion that cheating has run rampant during the ChatGPT era, and to a second conclusion that with plagiarism detection tools, we should now return to a pre-ChatGPT world. Both assumptions would misunderstand the unique capabilities – and limitations – of ChatGPT. 

First consider that ChatGPT was never an excellent essay writer. It functions by predicting the next most likely words in a passage, meaning it cannot truly comprehend concepts. When prompted to craft original work, ChatGPT echoes broad sentiments from its training data without being able to provide a source. ChatGPT is also notorious for fabricating false citations. Although ChatGPT is capable of regurgitating common ideas in a repetitive style, it lacks the gravity or insights that distinguish great pieces of writing. 

DetectGPT is another algorithm recently developed to aid in machine generated text detection for large language models (LLMS), including ChatGPT. LLMS are trained on huge data sets, and then generate sentences by predicting future words. Arxiv, a paper written by the creators,  identifies an application of LLMS as “replacing human labor.” The phrasing implies that replacing human labor in an academic or journalistic setting must be exposed and presumably prevented, yet the question of which human labor is and is not appropriate to replace with machines is ongoing. However, there are clearly some domains where fragments of information are cushioned by linguistic formalities, such as a cover letter or emails which follows a rigid form. Here, because of the massive training datasets that follow similar linguistic patterns, ChatGPT  elegantly succeeds in predicting common forms. 

The idea of relegating emails, CVs, or Slack messages to a computer has less repercussions than to pass off an entire essay. The former depends heavily on forms that require no creativity, and often need to be packaged in purposefully verbose platitudes. These shorter messages, however, would also be more difficult for a detection software to spot. 

The idea of AI writing our emails conjures a droll image of the future, of an individual sending a machine generated email to the receiver, who in turn uses AI to summarize the contents. A possible conclusion from this is that we need to let go of email formalities altogether. Perhaps a future workforce will discontinue the necessary “Good day! Hope this finds you well. Shall we double back on this issue next meeting?” corporate vernacular. 

To those that struggle with English, ChatGPT is also a resource, constructing grammatically correct and mostly socially concordant phrases from an idea. In this way, AI levels the playing field. The ability to regurgitate the formats and traditions of emails, cover letters, reports, is of less importance when that task can be entrusted to artificial intelligence. 

The uses of ChatGPT are widespread. A recent post in r/consulting asks redditors how they utilize ChatGPT for consulting work. Responses include summarizing ideas for presentations, crafting a maternity leave message, and technical coding questions. 

In contrast to current concerns, I posit that academics and journalists are safer from replacement. These industries are built off of rigorous research and artful writing, two tenets which ChatGPT, as a language model, cannot embody. However, some careers may dwindle with much of its appeal now supplanted by artificial intelligence. For instance, ChatGPT can create balanced and personalized diet plans, and answer basic customer support. That being said, its disposition for hidden errors makes it unlikely to be more reputable than a professional. ChatGPT, for now, is best served as a tool for generating text which can then be approved by humans. 

In essence, AI detection software will hopefully quell the panic of academic plagiarism, and attention can then be paid to alternative uses. Meanwhile, AI detection software does not prevent the use of ChatGPT to automate some everyday formulaic tasks. In the future, perhaps the workforce will acknowledge the needlessness of overly procedural pieces of writing, and we can assign ChatGPT to more creative uses. 

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Algorithmic, or big data policing refers to “a range of technological practices used by law enforcement to gather and process surveillance data on people, places, and populations and to forecast where and when crime is likely to occur.” A 2020 report from the University of Toronto’s Citizen Lab stated that “multiple law enforcement agencies across Canada have started to use, procure, develop, or test a variety of algorithmic policing methods.” For example, the RCMP has long used facial recognition in human trafficking cases. The Edmonton Police Service uses a software called NeoFace Reveal to compare faces to their mugshot database. The Toronto Police, among many other Canadian police departments, came under fire in 2020 for using facial recognition software without public knowledge. According to the Canadian Centre for Civil Liberties, “facial recognition technology has been deployed by police forces without notice, meaningful consultation, or public oversight and accountability.”

The report defined four types of algorithmic technology used by police forces: automated license plate readers (ALPRs) that can detect license plates and use them to find information about the vehicle in question; social media surveillance software that analyzes data from social media platforms; facial recognition technology to detect faces and compare them with a database to retrieve information about people; and social network analyses that use data to analyze relationships in a particular social organization. As people’s lives are increasingly online, this provides significant data about their lives that private companies or law enforcement can collect and use for surveillance.

Data-driven policing strategies have many advantages for law enforcement. They promise increased efficiency by using algorithmic analysis to predict where crime will occur and decide which areas law enforcement should focus on. They allow law enforcement to easily find information about a person and use that data to predict whether that person is dangerous. Additionally, they’re able to collect data on general mobility patterns and social activities at a much larger scale than older strategies. 

However, algorithmic policing strategies, especially facial recognition, are embedded with bias and can be very fallible. This produces concrete harm for marginalized people, something many critical AI experts have drawn attention to. The Montreal Society and Artificial Intelligence Collective (MoSAIC) argues that data-driven policing technologies present an “extreme risk,” as they “can be used for intrusive mass surveillance, particularly when used in live settings.” Dr. Joy Buolamwini, founder of the Algorithmic Justice League and a researcher at MIT, has found that AI services have significant difficulty identifying darker-skinned and female faces. Data scientist Kelsey Campbell from Gayta Science has similarly flagged the ways in which AI presents a danger to trans and non-binary people. According to Campbell, AI is usually programmed based on binary conceptions of gender, ignoring the reality of transgender and non-binary people. It automatically classifies people as either male or female based on arbitrary categories, namely body parts. If transgender or non-binary people are using AI technologies, they may have to identify themselves as male or female, even when this choice doesn’t reflect their gender identity. Facial recognition also doesn’t account for a changing appearance, such as a transition, putting transgender people at an increased risk of being flagged as dangerous – or possibly outed.

Even if the technology itself was not biased, it can enable or exacerbate existing biases within police forces by enhancing their capabilities of surveillance and profiling. A 2021 report by the Standing Committee on Public Safety and National Security determined that systemic racism in policing “is a real and pressing problem to be urgently addressed.” If police officers already hold deep-seated racial bias, they’re unlikely to question it in the technology they’re using. In the United States, where facial recognition is even more widespread, Black people such as Nijeer Parks, Robert Williams, and Michael Oliver have been falsely arrested for crimes they didn’t commit because they were misidentified by facial recognition software. Although all three of these men were eventually cleared, the trauma from these false arrests had serious repercussions for their families and communities. Although police have targeted marginalized communities since long before AI was created, this technology allows them to conduct their operations more efficiently, leading to increased surveillance of marginalized groups. If certain people’s faces are less “legible” to AI, then there’s an increased risk that they will be flagged as dangerous or mistaken for someone else. If AI considers someone to be dangerous, it gives the police more justification to stop them on the street or arrest them, even if they have no other reason to suspect them of a crime. 

Another concern is the lack of transparency regarding how police departments use this technology and where they acquire it. In January 2020, it was revealed that many Canadian police departments used facial recognition technology provided by Clearview AI without public knowledge. Clearview AI offers a large database of faces mostly scraped from the internet without consent from the websites or from those whose data was taken. By the time the collaboration came to light, Canadian police had already run 3,400 searches using 150 free trial accounts. In February 2021, Canadian authorities declared Clearview AI’s activities illegal as they were ‘mass surveillance.’ Another company, Palantir, which provides technology to the Calgary Police, was also used by ICE in the United States to plan raids and detain undocumented immigrants, receiving condemnation from Amnesty International. 

A further issue with transparency is the lack of consultation with the communities in which these technologies are deployed. For example, in 2021, the SPVM announced that they were installing nine new cameras in public spaces to tackle gun violence. They were subsequently criticized for not adequately consulting the communities affected. Surveilling people without consultation or informed consent takes away their agency in tackling issues within their own communities. Meaningful community consultations must be as accessible as possible, which means providing information in languages spoken by community members, advertising the consultation sessions through different mediums, and using accessible language to describe the technology and its impacts. MoSAIC argues that if a technology cannot be easily explained or interpreted to the communities affected, it is inherently high-risk.

Because the Canadian government currently lacks policies that effectively constrain the use of algorithmic policing technologies, there is also little accountability. At present, there is no AI-specific legislation in Canada to regulate the use of algorithmic policing technologies other than existing privacy and human rights legislation and the Directive on Automated Decision-Making. The Directive states that automated decision-making technologies have to pass a risk-assessment, and there should be opportunities for affected individuals to provide feedback and seek recourse. However, the Directive currently has no power over technologies developed at the provincial level or by private companies. Without a proper governance framework, it’s nearly impossible for the federal government to regulate the use of these technologies for either public institutions or private companies. And given the speed at which AI is developing, it will only become more difficult for policymakers to keep up. 

In order to mitigate the harms of AI in policing, many civil society groups are calling for a moratorium on the use of AI technology by law enforcement until proper regulation can be put in place. When Vermont became the first state to ban facial recognition in 2020, the American Civil Liberties Union of Vermont stated that this ban “sends a clear message that instead of a discriminatory police state, Vermonters want to create communities where everyone can feel safe, regardless of what they look like, where they are from, or where they live.” Across the United States, states and cities have already banned the use of algorithmic and predictive policing technologies, especially facial recognition, by law enforcement. Many of these bans came into effect after the murder of George Floyd in 2020, when there emerged an increased national consciousness about systemic racism and bias in policing. In October 2022, in Canada, the House of Commons Standing Committee on Access to Information, Privacy and Ethics recommended a “national pause” on facial recognition technology until a substantive legal framework could be put in place. 

The Citizen Lab report provides additional recommendations for the government to mitigate the harms of AI. They ask for a judicial inquiry into the use of police datasets in algorithmic policing technologies. They call for complete transparency surrounding which technologies are being developed, used, or procured by police departments, and for the government to establish requirements concerning reliability, necessity, and proportionality before a technology can be used. Provincial governments should also implement regulations for algorithmic policing technologies within their own provinces. Police departments should also obtain judicial authorization before deploying any of these technologies. Finally, governments and law enforcement should bring in external experts, including those from communities targeted by police violence, to design policies for implementing technologies, developing regulation, and monitoring the effects of algorithmic policing technologies.

While AI as a technology is still developing, there is concrete evidence that it can cause harm, especially in the hands of law enforcement. It’s concerning that institutions with documented problems of systemic racism are allowed to use these powerful technologies with little public oversight. Many studies have proven that these technologies are extremely fallible, especially when dealing with women, transgender people, and people of colour. The past few years have brought increased attention to police violence towards marginalized communities, and giving police departments more sophisticated tools to conduct their operations will only exacerbate this violence and discrimination.

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For those who have used ChatGPT before, the platform’s widespread adoption can’t have been much of a surprise. One quick glance at the platform often leaves new users marvelling at its capabilities. From being able to tell jokes, to being able to pen full-page articles all at the push of a button, ChatGPT is able to replicate tasks which, for decades, have seemed only achievable by humans. More impressive still, further in-depth testing of the platform’s capabilities have led to some truly remarkable results. On December 31, a paper published by Michael Bommarito and Daniel Katz, professors at the Chicago-Kent College of Law and Michigan State University of Law respectively, revealed that ChatGPT was even able to pass the bar exam, reporting that the chatbot’s top two and top three choices were “correct 71% and 88% of the time.” 

At McGill, ChatGPT’s rapid rise to stardom is unsurprisingly becoming an increasingly prevalent topic of conversation in the classroom. In my experience as a student at the Desautels Faculty of Management, several of my professors have polled students about their knowledge of the platform. Some have gone even further, verbally committing to redesigning future assignments with the knowledge that students can use ChatGPT to help them answer questions. While such commitments mostly led to reactions of amusement by students in the classroom, there’s no doubt that ChatGPT’s capabilities have left many professors seriously worried about its broader academic implications. And for good reason; a mere two weeks after the platform made headlines about passing the bar exam, it once again made the news when professors at the Wharton School of Business, University of Pennsylvania, announced that the chatbot was able to pass exams given to their MBA students. Here at Desautels, my Operations Management professor revealed to students that ChatGPT was able score 80 per cent (an A-) on the 2021 edition of his final exam. 

Concerns about the rapid advancement of technology is nothing new – in 1942, Isaac Asimov famously published his three laws of robotics as a result of a fear that robots would eventually completely replace humans – but never before have machines been this close to actually fully replicating “human” thought. And while Asimov’s fears have yet to materialize, ChatGPT’s capabilities definitely do raise fears about humans being replaced by robots, at least in the sphere of academia. 

AI looks to be improving at an increasingly fast rate. On January 23, Microsoft officially announced a new multi-billion-dollar investment into ChatGPT, with a commitment to improving its capabilities beyond its current limits. These commitments, while undoubtedly exciting, also run contrary to the spirit of learning within the academic setting, raising broader questions about the role of AI in academia as a whole. 

McGill has frequently taken measures to prevent widespread cheating and preserve academic integrity. Back in 2003, for example, the university responded to the rise of the internet by passing a Senate resolution designed to underscore that “all students must understand the meaning and consequences of cheating, plagiarism and other academic offences under the Code of Student Conduct and Disciplinary Procedures.” But while responses to “old” tech were more straightforward, responses to the rise of “new” adaptive tech like AI likely won’t be. Unlike websites such as Google, which actively seek and return existing web pages, AI creates them. This means that while Google can only simply return previously written papers, AI like ChatGPT can go one step further: creating new, never-before-seen papers for its users. 

With AI blurring the line between human and machine, blurred too becomes the line between what is and what is not academic integrity. For example, plagiarism is currently widely defined as presenting another person’s work as your own. But how does this definition extend to the use of AI, where a student doesn’t present “another person’s,” but rather a machine’s, work as their own? Questions also arise about how the principles of academic integrity apply to those who use AI simply to aid their work, rather than to replace it. For example, if a student uses AI to help teach them how to resolve a similarly – but not identically – worded question, or if a student requested AI feedback on an essay they wrote, are these instances of academic malpractice?   

These concerns are relatively widespread. Just two months after ChatGPT’s release, students took the first steps to combating the rise of AI in academia by releasing GPTZero – an AI software designed to red-flag AI-generated writing. While GPTZero is definitely a step in the right direction in the long road to preserving academic integrity, it is exactly that: just a step. 

Ultimately, there’s no denying that platforms like ChatGPT, powered by fresh investments from many of the world’s tech giants, aren’t going anywhere. Nor can one deny that as AI continues to blur the line between human and machine, blurred too becomes the line between what is and what is not academic integrity. While we should definitely welcome the benefits that AI provides, we should equally look to resolve the very real threats that it poses. Only then will we actually be able to truly preserve the academic integrity we so clearly value. 

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Diabetes is a disease that develops due to a lack of insulin production or inefficient insulin utilization. Insulin is a hormone produced by the pancreas in response to food ingestion. Once ingested foods are broken down into blood sugars, insulin helps these sugars enter the body’s cells so that they can be used for energy. Diabetes causes insulin deficiency or insulin resistance, which can in turn lead to persistently high blood sugar levels as the sugar in the bloodstream cannot enter cells. Over time, high blood sugar can result in health problems, including heart disease, vision loss, and kidney conditions. 

Genetically, evidence has shown that East Asian people are more likely to develop diabetes than their Caucasian counterparts. A 2020 study published in Nature investigated genetic information from 433,540 East Asian individuals. While type 2 diabetes is generally believed to develop due to obesity, the study’s results showed that East Asians developed the condition despite not being obese. Researchers identified numerous new genetic variants associated with type 2 diabetes that were unique to people of East Asian descent, which could explain their higher likelihood of developing diabetes.

Additionally, a well-established physiological characteristic of East Asian women contributing to their increased risk of developing type 2 diabetes is their tendency to store fat viscerally instead of subcutaneously. Visceral fat is belly fat that surrounds internal organs, including the stomach, liver, and intestines. It is more dangerous to health than subcutaneous fat, which is fat stored just below the skin. When in excess, visceral fat can lead to type 2 diabetes. Therefore, the tendency to gain visceral fat puts individuals of East Asian descent at a higher risk of developing type 2 diabetes.

Another physiological feature among East Asian individuals pertains to their increased likelihood of having impaired insulin function. Insulin is a hormone that plays a crucial role in developing type 2 diabetes. It lowers blood sugar levels after food consumption by allowing blood sugars to be absorbed by cells. When insulin functions poorly, blood sugar levels stay high after food consumption, increasing the risk of type 2 diabetes. 

Considering that people of East Asian descent account for a significant proportion of total cases of diabetes worldwide, it is essential to prioritize interventions that target East Asian populations to combat the diabetes epidemic. Primary prevention of diabetes could be achieved by modifying risk factors, including a diet high in sugar and refined grains, lack of physical activity, and impaired insulin function. Public health policies promoting a healthy diet among the population, such as the consumption of whole grains and plant-based proteins, should be reinforced. Public health agencies should also allocate funds to improve treatment modalities that preserve or boost pancreatic islet functioning, as such modalities could help prevent diabetes in East Asian individuals. 

Early-life influences also play an essential part in diabetes prevention because maternal lifestyle and health conditions such as gestational diabetes and obesity affect the risk of diabetes in newborns. Interventions that promote a healthy body composition, diet, and lifestyle need to be implemented before and during pregnancy to significantly reduce the incidence of diabetes in the future child. Multisectoral agencies should collaborate to promote health literacy in parents-to-be.

Further research is required to more comprehensively understand the drivers of the diabetes epidemic before evidence-based prevention strategies can be proposed to address the rising global public health “tsunami.” Policies for diabetes management and prevention targeting the access and affordability of health services, diabetes medications, and appropriate glucose monitoring systems may be necessary. For example, prediabetes screening could be made more affordable to encourage regular screenings. Prediabetes is when blood sugar levels are higher than the normal range but not high enough for the person to be diagnosed with type 2 diabetes. It does, of course, indicate an increased risk of developing type 2 diabetes. Prediabetes screening is important in diabetes prevention as prediabetes is reversible, meaning that healthy dietary and lifestyle habits can prevent or delay it from turning into type 2 diabetes.

Lastly, it is notable that the prevention of diabetes is hindered by a lack of reliable epidemiological data in numerous East Asian countries. For instance, the prevalence of diabetes in countries without available local data is estimated based on modelling using pooled estimates from countries that share similar geographic, ethnic, and economic features; this results in less accurate interpretations of data. Another flaw in data collection pertains to the parameters being used. Many East Asian countries lack epidemiological data on impaired glucose tolerance (IGT) despite having a high IGT prevalence. IGT is a high-risk condition for diabetes and is diagnosed by the oral glucose tolerance test (OGTT). Instead, these countries use only fasting plasma glucose (FPG) tests, which mainly screen for diabetes by measuring blood sugar levels after fasting for eight to ten hours. The use of FPG alone in epidemiological studies is concerning because it is less sensitive in detecting diabetes and prediabetes than the oral glucose tolerance test (OGTT). According to a study conducted in 2015, using FPG only may significantly underestimate prediabetes and diabetes cases compared to using OGTT and FPG together. Therefore, there is a need to improve the collection and interpretation of epidemiological data regarding diabetes for use in future public health prevention activities, particularly in lower- and middle-income East Asian countries. 

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