Hey everyone! I’m loving all of your thoughtful responses to these sections. It’s great to see you take some time and sort of chew on these ideas about neutrality and objectivity. I’m sure plenty of professionals in your respective fields never do this deep dig, it’s provocative af! and forces us to really take into consideration how the work we do impacts the world around us (ick! feelings!)
I was planning on finishing up Science Under the Scope, but I think we can break it up between this week and next week just to really take our time. There’s no rush! we have nowhere to get to! Urgency is a trait of ableist white supremacy culture (bonus personal growth points if you have a moment to check out the link), it perpetuates the myth that we need to be productive to be valuable, that we need to be doing labor to have value. Fuck that noise.
We will take our time, let’s let this all marinate.
Segments eight, nine and ten of Science Under The Scope dive deeper into the real world impacts of uneven resource distribution and how that siphoning of resources by the overly resourced (usually white people) will intentionally minoritize other people and keep hold of power. Wang shows us this through breaking down “who benefits” from science industry funding. This is not the science we think about when we’re dissecting frogs (do the youth even still do that? I’m old and I still remember those little frog organs omg).
The example Wang gives is the difference between scientific research funding for cystic fibrosis (which predominantly affects white people) and sickle cell anemia (predominantly affects Black people).
How does this under representation happen? “The reason the answer to all of these questions is kind of the same – (middle class folks, white folks, folks with access to science ed, folks who see themselves represented in science, by science, as scientists) – is not by chance or some inherent factor of culture or biology. The reason is because our world’s histories of injustice, oppression, marginalization, and white supremacy have created this segmentation, this privilege.”
And so when we start to think about the intentional and systemic oppression of non-white people by white people and people who uphold white supremacist ideals, it becomes clearer how scientific research and data skews to favor a specific group.
For this week, please read eight, nine, and ten, and share two or three areas of research or technological development that might have bias towards people in power. Extra points if you can find something like this in your field (we’ll be doing writing project later this semester, you might want to use the content you find now).
Thanks everyone! Next module we’ll finish up Science Under the Scope. Have a great week!
The research or technological development that might have bias towards people in power are problem solving methos of AI & doctors. The reason is no one cares about their opinion where they could save life. The white people are trying let other races not to be powerful where they think other races will out done them.
Healthcare research studies may be bias towards people who have better access to healthcare.
Social media algorithms might also be bias towards people with power. People with less power are less likely to have their voices be heard of.
We live in a day and age where technology rules all, mainly referring to social media’s influence and effect on our everyday lives. There really is no such thing as freedom of speech when you hold an immense amount of power and influence over people’s lives. With the rapid growth of these social media platforms, cancel culture has become a huge part of society, and with this comes biased opinions. For me, after reading the question posed for this module, what immediately came to mind was the Kanye West and Donald Trump situation, where they were banned and bashed for great reasons. Don’t get me wrong; by no means do I support the unprecedented and heartless remarks of these two, but what happened was truly biased. I believe that these social media platforms and their respective owners, who had both Kanye West and Donald Trump banned and silenced, could hardly give a damn about the situation at hand. But because of society’s tendency to dictate how these platforms handle certain situations, this goes to show that these owners want to satisfy the needs of society, while in reality they really don’t care; they just don’t want to be part of the cancel culture. We see how social media works and tends to reshape and attack those with a voice. Unlike Kanye and Trump, one person who did not deserve the backlash and unfortunate consequences was Kyrie Irving. When you have power in this generation, what you say can be greatly used against you, and Kyrie had the worst of it. After posting about a book that referenced antisemitism, which Kyrie said he was not aware of, it greatly affected his endorsement, caused him to be suspended a couple of games, and caused him to be looked down upon for a genuine mistake. Which just shows you the biased narrative social media holds when dealing with people of influence. Another example of bias towards people in power was the establishment of Obamacare. Obamacare was aimed at providing affordable healthcare to those of lower income, and research shows that the rich were not happy with this. With money comes power, and Obamacare was aimed at one social group, so I would say this was biased toward the middle and lower classes, even though it was great for those who really needed it.
In the engineering field, famous engineers I’ll most likely get a job over upcoming engineers. Apart from this they will be able to charge a lot more than the new engineers because there will be biased towards them. Another example is in the news. If a news company is owned by for example republicans or democrats they will most likely support their respective parties even if it is not the right choice.
One area where technological development might be biased towards people in power is autonomous vehicles. Self-driving cars are engineered to make decisions that protect the people inside the car even if it means putting people outside the vehicle in danger. Most of the people outside of the car are most likely to be low-income people since they don’t have a vehicle. Another area would be social media algorithms. Social media algorithms are used to identify using user data to find the type of content the user would like. This might be biased towards people with power since they can promote certain viewpoints.
Facial recognition technology has been shown to have biases towards people of color and women. This is because the algorithms used to train these systems are often trained on datasets that primarily feature white men. This can lead to misidentification and false positives, which can have serious consequences, particularly in law enforcement.
Another area where technological development shows bias for people in power is climate change research. For example, research on the impacts of climate change on low-income communities and communities of color may receive less funding and attention than research on the impacts on wealthier, predominantly white communities. This can lead to unequal distribution of resources and unequal impacts of climate change.