I see the discussion of assumptions falling along the same lines of stereotypes, I’m guessing that’s why they were assigned back to back. A Venn diagram showcasing stereotypes and assumptions would have a very large overlapping area.  From the two assigned readings, I think it’s fair to say that both topics, health and immigration, are often shrouded with assumptions any time that they are brought up. I was guilty of creating immediate assumptions about the Flanigan article after only reading the title. Why and when would prescription requirements be bad? That’s not something that I ever think about, so I immediately assumed that prescriptions are inherently good, after all, they are made to give medicine to help people. It turns out I only needed to read half of the first page before the example scenarios overrode my previous assumptions.

I generally agree with the argument made by Flanigan that prescription drug laws violate patients’ rights to self-medication. That was the explicit argument, but I almost felt as if it turned into saying that all drugs should have open access to all in any amount. That’s basically what would happen if the prescription part of prescription drugs was eliminated. This is of course, an assumption made by me. I think the elimination of prescription drugs and respecting of self-medication is a very idealist stance and will be nearly impossible to achieve given how manufactured our society is. We can get make progess by decriminalizing drugs like Oregon has done, which I think is great. However, without the proper allocation of subsidies, funds, and infrastructure in place to provide things like free drug rehabilitation services, I fear that more issues will come. Luckily Oregon is accounting for these things, offering those with addictions and criminal charges the opportunity to go to rehab instead of jail. On a seperate note, I find it ridiculous and abhorrent that there are so many people that are unable to get the prescription drugs they need, whether it be because of cost of supply, but usually because of cost. The cost barrier of those individual medical needs must be broken down, otherwise removing the prescription part would only make a small dent.

While listening to the podcast I began thinking about just how much of what I view online is a result of algorithms and machine learning. I don’t think, though, that algorithms are always bad. For example, I’ve been on Tiktok, Twitter, and Instagram long enough to where I’ve interacted with enough of the rights posts so that my feeds generally only include things that I’m genuinely interested in, with the exception of some ads and whatever branches of new content get snuck in. I do a lot of hiking, so I like when I see hikes and hike-related content pop up in my feed. I selectively choose to interact with those things that I like in hopes that the algorithms will provide me with similar content. I do think that algorithms can, however, be very dangerous or harmful when scrolling with the wrong mindset or lack of education on a subject. This is why I think that social media is very problematic for children and young people. Without prior knowledge of a subject, it can be very easy to believe something that you haven’t heard of before. If those initial experiences can spiral out of control and be difficult to change a mindset if a foundation has been built upon it. There isn’t a doubt that there is harmful content on every social platform, but I think we also have to be careful with censoring. I’m under the belief that censoring is fine in the case of children, as they have less critical thinking skills and experiences to relate things to, but I think harmful/negative content can also provide insight into how biases are created and why people think the things that they do and that censorship should generally be avoided for those that are not children.

One of the bigger problems with social media is that you’re almost always in an echo chamber, being fed content that you are likely to agree with, making it all the more difficult to change opinions in the future. This is why I see travel as being so important. The best way to learn about a culture or topic is to be immersed in it, ideally as much as possible and from a wide range. By no means, however, is travel a perfect solution to eliminate bias. If you’re going somewhere as a tourist, then you will only be gaining the perspective of a tourist. Oftentimes tourism involves exaggerated aspects of a culture, and limited interactions with locals can lead to further biases if you try to apply them to everyone from that culture. Travel is also inaccessible for many, as it is very expensive and takes up a lot of time. Books and education are other potential solutions, but even then bias is still present.

At the end of the day, there isn’t really anywhere you can go to truly escape bias. I think the best counter-measure to having biases is to listen to as many different opinions as possible before making a decision. Although this is technically an original blog post that I have personally written, I even question myself as to where these thoughts originated from. Sure I may be expressing myself in an original way, but I would wager that 99% of all my thoughts are based on the thoughts, concepts, and ideas of others.

For the Implicit Association Test, I did the Race IAT. My results were what I expected, in the middle with little-no automatic preference, but what surprised (disappointed) me was in the data summary at the end. 24% of participants had a strong automatic preference for European Americans compared to African Americans, with 24% of participants having a moderate preference for European Americans compared to African Americans. This is obviously problematic for many reasons, but what I think about most is how much that must impact the unconscious decisions of people across America. This could be the difference between getting a job or promotion for someone, or even something as mundane as saying hello to someone on the street. I would be curious to see the age demographics, which unfortunately are not provided. I think that they would provide some insight into how biases are across generations, and if they are slowly fading away or still evenly distributed across age. There is also a disclaimer on the site about how this data fluctuates and shouldn’t be used for serious decisions, but I think that the data is relatively accurate based on my experiences and things I’ve learned.

From an overall perspective, moral arguments seem to overlap around 90% with the previous arguments that we have been studying. One of the biggest things that stuck out to me is the concept of Noncognivtists. Refusing to be objective and pick a stance of right or wrong, it seems like a very cop-out choice to fully follow be a Noncognivist. I have a hard time understanding the train of thought behind this concept, however, the Noncognivist comparison that moral disagreement is similar to expressing emotions does make a lot of sense to me. Nearly all moral arguments that I can think of invoke some sort of emotion, and emotion seems to be the guiding reasoning for many moral arguments, which may not necessarily be the right thing to do. While Noncognivists do seem a bit extreme, I suspect that most people have a bit of Noncognivism in them. It can be difficult to pick a right or wrong stance every time, as there are some morally grey areas in life, so while Cognivists may initially seem much more reasonable, it isn’t always as practical.

Another concept that I found interesting (and familiar) is Universalism and the Universalistic Maximizing Consequentialist (USM). Immediately this sounds nearly identical to that of a Utilitarian, especially given the sample argument of maximizing happiness.  It would seem to me that all Utilitarians use the USM principle to guide their arguments, and I was surprised that Utilitarianism was not mentioned at all in this section.