Racism in Science & Technology: Systemic Bias and Reform | Study Guides, Projects, Research Technical Writing

In unit 1: The culture of science, about ‘Racism and Overcoming Sciences Toxic Legacy’,

explores how historical racism has impacted the development of science and how the scientific

community has contributed to and perpetuated racial biases. The unit examines the legacy of

scientific theories used to justify racial discrimination, and how it highlights the harmful

consequences of this legacy, particularly for marginalized groups. So why do colored people get

treated differently in the scientific world? The annotation paragraphs are also organized by year,

it's this way to show how much “changes” through time.

Mallapatty, Smriti. "‘There’s No Space for Us’: An Indigenous-Health Researcher Battles

Racism in Australia." Nature, 3 Aug. 2020,

In this article, Smriti Mallapatty discusses the experiences of an Indigenous-health

researcher in Australia who faces systemic racism and exclusion within academic and health

research fields. The article highlights the researcher’s struggle to navigate an environment where

Indigenous perspectives and expertise are often marginalized, despite the importance of

Indigenous knowledge in addressing health disparities. Mallapatty’s work sheds light on broader

issues of institutional racism in science and health, emphasizing the need for inclusivity and

reform. This source provides valuable insights into the intersection of race, health, and academia,

making it useful for research on systemic racism in the scientific community and health care

systems. It is particularly relevant for understanding the challenges Indigenous researchers face

in predominantly Western research institutions. Some rhetorical features that were used in the

article were pathos, Mallapatty uses personal anecdotes and the lived experiences of an

Indigenous researcher to evoke empathy from the audience. By describing the researcher’s

struggles with exclusion and racism in the academic and health research fields, the article

appeals to readers' emotions. For example, The article details how the Indigenous researcher

feels marginalized and unsupported, highlighting feelings of isolation, frustration, and exclusion.

When comparing the article Mallapatty wrote with other sources on racism in academia or health

research, the analysis reveals broader insights into how arguments about systemic racism are

constructed and communicated across different contexts. By comparing the two approaches, we

learn that personal narratives, like those in Mallapatty’s article, can make abstract or distant

concepts like systemic racism feel more immediate and personal. When combined with more

data-driven approaches, such as studies that provide statistics on representation or health

disparities, we gain both an emotional understanding and a concrete grasp of the scope of the

issue. Together, these approaches offer a more holistic picture of systemic racism than either

source would alone (by Smriti Mallapaty). (Jeremiah)

Birhane, Abeba. "The Unseen Black Faces of AI Algorithms." Communications of the ACM,

vol. 65, no. 2, Feb. 2022, pp. 42-44.

In that article Abeba Birhane critically examines the inherent biases within artificial

intelligence (AI) systems, particularly focusing on how Black individuals and other marginalized

groups are disproportionately misrepresented or mistreated by these technologies. Birhane argues

that AI algorithms, often trained on biased datasets, perpetuate racial inequalities by failing to

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In unit 1: The culture of science, about ‘Racism and Overcoming Sciences Toxic Legacy’, explores how historical racism has impacted the development of science and how the scientific community has contributed to and perpetuated racial biases. The unit examines the legacy of scientific theories used to justify racial discrimination, and how it highlights the harmful consequences of this legacy, particularly for marginalized groups. So why do colored people get treated differently in the scientific world? The annotation paragraphs are also organized by year, it's this way to show how much “changes” through time. Mallapatty, Smriti. "‘There’s No Space for Us’: An Indigenous-Health Researcher Battles Racism in Australia." Nature, 3 Aug. 2020, In this article, Smriti Mallapatty discusses the experiences of an Indigenous-health researcher in Australia who faces systemic racism and exclusion within academic and health research fields. The article highlights the researcher’s struggle to navigate an environment where Indigenous perspectives and expertise are often marginalized, despite the importance of Indigenous knowledge in addressing health disparities. Mallapatty’s work sheds light on broader issues of institutional racism in science and health, emphasizing the need for inclusivity and reform. This source provides valuable insights into the intersection of race, health, and academia, making it useful for research on systemic racism in the scientific community and health care systems. It is particularly relevant for understanding the challenges Indigenous researchers face in predominantly Western research institutions. Some rhetorical features that were used in the article were pathos, Mallapatty uses personal anecdotes and the lived experiences of an Indigenous researcher to evoke empathy from the audience. By describing the researcher’s struggles with exclusion and racism in the academic and health research fields, the article appeals to readers' emotions. For example, The article details how the Indigenous researcher feels marginalized and unsupported, highlighting feelings of isolation, frustration, and exclusion. When comparing the article Mallapatty wrote with other sources on racism in academia or health research, the analysis reveals broader insights into how arguments about systemic racism are constructed and communicated across different contexts. By comparing the two approaches, we learn that personal narratives, like those in Mallapatty’s article, can make abstract or distant concepts like systemic racism feel more immediate and personal. When combined with more data-driven approaches, such as studies that provide statistics on representation or health disparities, we gain both an emotional understanding and a concrete grasp of the scope of the issue. Together, these approaches offer a more holistic picture of systemic racism than either source would alone (by Smriti Mallapaty). (Jeremiah) Birhane, Abeba. "The Unseen Black Faces of AI Algorithms." Communications of the ACM, vol. 65, no. 2, Feb. 2022, pp. 42-44. In that article Abeba Birhane critically examines the inherent biases within artificial intelligence (AI) systems, particularly focusing on how Black individuals and other marginalized groups are disproportionately misrepresented or mistreated by these technologies. Birhane argues that AI algorithms, often trained on biased datasets, perpetuate racial inequalities by failing to

recognize or accurately process Black faces, leading to significant ethical and social issues. The article emphasizes the importance of diverse data and ethical AI development while calling for systemic change in the AI industry to prioritize inclusivity and justice. This source is essential for understanding the racial implications of AI systems and offers a well-reasoned critique of the current state of AI, making it highly relevant for research on bias in technology and the social consequences of AI. Some rhetorical features that were used in Birhane article was ethos, Birhane establishes credibility by drawing on her background in cognitive science and ethics, as well as referencing well-known studies and expert opinions in the field of AI. Her academic and professional authority helps build trust with the audience, making the arguments more persuasive. For example Birhane references prominent research on algorithmic bias and key incidents of AI failure, such as facial recognition technology misidentifying Black individuals. When comparing the rhetorical features in the article Birhane wrote with other sources that address racial bias in technology, AI ethics, or social justice, analyzing them together can offer deeper insights into how arguments about AI bias are framed and communicated. Examining multiple sources side by side reveals contrasting strategies, complementary arguments, and the broader landscape of the discourse around AI ethics and racial bias. So therefore analyzing these sources together allows us to see how credibility is built through different approaches. Like how they provide a fuller understanding of the issue. Birhane’s ethical lens challenges the assumptions made in more technical discussions, while empirical studies can validate her claims with data and quantifiable evidence (by Abeba Birhane). (Jeremiah) Prillaman, McKenzie. “The First Indigenous Female Surgeon in Canada Is Battling for Health Justice.” Nature News, Nature Publishing Group, 19 Oct. 2022. In this Nature article, author McKenzie Prillaman is addressing the issue that indigenous people are underrepresented and under supported in Canada. Nadine Caron, the first woman to become a general surgeon in Canada, has dedicated a large amount of her time and energy into fixing this problem. Prillaman’s main point is that Indigenous people have been getting professionally disrespected and stereotyped, which has led to them getting poor treatment. The main takeaway from this text is that Indigenous people deserve more equity in society, and Nadine Caron has done a great job making this a reality through her work, as she helped to found and now co-directs the Centre for Excellence in Indigenous Health at the University of British Columbia (UBC) in Vancouver. The text is meant to be inspiring because readers will feel a sense of hope listening to Caron’s story. The tone of the text is strictly informative and describes the work of Nadine Caron in an unbiased way. (Sawyer) Pierre-Louis, Kendra. “‘It’s a Constant Hum’: A Planetary Geologist Calls out Racism in Academia.” Nature News, Nature Publishing Group, 19 Oct. 2022. In this Nature article, author Kendra Pierre-Louis addresses the subtle racism that minority students deal with when pursuing a career in science. Pierre-Louis makes the claim that racism in America isn’t just violence and outright discrimination, but it also lurks in careers and stunts personal development. This problem is growing, and less and less minorities are choosing majors in geoscience and other scientific fields, so the author is aiming to spread awareness to the general public and put a stop to racism within the workplace. She does this by holding a serious tone throughout the article

MLA Citations:

Cam: Newsome, Melba. "Computer Science Has a Racism Problem: These Researchers Want to Fix It." 2022, https://doi.org/10.1038/d41586-022-03251-0. Accessed 15 Oct. 2024.

Version from Cam’s Doc:

Keller, Matthew D., et al. “Skin Colour AƯects the Accuracy of Medical Oxygen Sensors.” Nature News, 19 Oct. 2022. This article by Keller, Harrison-Smith, Patil, and Arefin focuses on the racial bias present in pulse oximeters, which measure blood oxygen levels. During the COVID- pandemic, it became clear that these devices provide less accurate readings for people with darker skin tones due to the way melanin scatters light. This inaccuracy can lead to dangerous consequences, such as missed diagnoses of hypoxemia. The authors highlight several retrospective studies confirming that Black, Hispanic, and Asian patients are disproportionately aƯected by this bias, resulting in delayed or inadequate treatment. They emphasize that this issue is part of a broader trend of racial bias in medical devices, with flawed calibration processes and oversampling of light-skinned individuals exacerbating the problem. The authors call for regulatory reform and updated device design to ensure pulse oximeters work equitably for all skin tones. This article contributes a significant perspective on how racial bias in medical technology aƯects healthcare outcomes and provides a clear path for systemic change in device calibration and clinical trials. Newsome, Melba. "Computer Science Has a Racism Problem: These Researchers Want to Fix It." Nature, 19 Oct. 2022. Melba Newsome discusses the ongoing racial disparities in computer science, highlighting the underrepresentation of Black, Hispanic, and Indigenous individuals in the tech field. The article points out that, despite comprising a significant portion of the workforce, these groups hold a much smaller percentage of computing jobs and degrees. This lack of diversity has far-reaching consequences, including the development of biased technologies that disproportionately harm marginalized communities. Newsome highlights eƯorts by computer scientists like Juan Gilbert to create more inclusive environments through mentorship and support networks. The article underscores that while some diversity initiatives exist, progress remains slow, and systemic change is needed to address both educational and professional disparities. Newsome’s article is a valuable contribution to discussions about equity in STEM, illustrating the need for comprehensive solutions that go beyond surface-level diversity eƯorts.

Indigenous communities have long been marginalized. The article is both informative and inspiring, demonstrating how Caron’s activism and leadership have paved the way for more equitable healthcare systems in Canada. Prillaman presents Caron’s journey as an example of the larger movement for Indigenous representation and justice in medical fields. This piece is crucial for understanding the unique challenges Indigenous healthcare professionals face and the impact of their work on health outcomes for marginalized communities. Pierre-Louis, Kendra. “‘It’s a Constant Hum’: A Planetary Geologist Calls out Racism in Academia.” Nature News, 19 Oct. 2022. Kendra Pierre-Louis discusses the subtler forms of racism that minority students and professionals encounter in academia, particularly in the geosciences. The article sheds light on how systemic racism stunts the careers of minority students and discourages them from pursuing degrees in scientific fields. Pierre-Louis’s piece uses a serious tone and empathetic storytelling to raise awareness about the isolation and professional obstacles minority scientists face, making a compelling case for institutional reform. By emphasizing the structural nature of racism in academic careers, the article contributes to the larger conversation about racial equity in STEM and the need for long- term changes to foster a more inclusive environment. Together, these sources illustrate the pervasive nature of systemic racism across diƯerent scientific and technological fields, from medical devices to AI algorithms to academia. Whether through technology, healthcare, or education, each article demonstrates how racial bias creates barriers for marginalized communities and underscores the urgent need for comprehensive reform. These works highlight both the personal struggles of individuals in these fields and the broader institutional challenges that perpetuate inequality, providing a holistic view of racism’s impact on science and society.

Racism in Science & Technology: Systemic Bias and Reform, Study Guides, Projects, Research of Technical Writing

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MLA Citations:

Version from Cam’s Doc: