I was reading the Julia Evans article, and what stuck out to me was specifically the odometer example. This was supposed to be a program that tracked 10,000 km, but it only actually tracked 262 km because floating-point errors kept accumulating over time. I originally thought of floating point as a super technical concept, but this example makes it seem much clearer and less technical to me, and makes me think twice about how much we should trust computers when it comes to accuracy.

Learning about metadata made me realize how much information I have that is going out to the public that I do not even know about. Every photo I take shares a location and a timestamp, and most apps track when and how the app is being used, so it sort of bothers me how so much of my information and schedule is going out to these companies, which can potentially sell it to other groups or organizations.

The Huck Magazine provides an article that goes over click farms and added an observation that I did not expect earlier. It isn't just bots on automated scripts running servers, rather it is actual humans manually liking and following posts at a large scale. This blurs the distinction between "bot" and "human" which I believe this chapter doesn't fully address since it is the artificial manipulation of metrics, regardless of who does it.

This stat that states how over half of the negative tweets about The Last Jedi were from bots or accounts that were politically motivated make me rethink how I interpret online backlash. Whenever I see this online, I assume it is a group psychology, but this statistic has showcased to me that a lot of this really just comes down to bots. This makes me wonder how often public opinion is shaped without anyone noticing.

The idea of deontology seems difficult to apply in real life because situations vary, and you aren't always able to apply a strict set of rules. For example, in social media, people may feel obligated always to tell the truth. In doing so, this could spread negativity and be seen as harmful, suggesting that consequences may need to be seen alongside different moral rules.

This section of consequentialism is interesting to me since it talks about how actions are judged based on the total of their consequences, sort of acting as a cumulative judgment. Personally, I do not agree with the idea; however, consequentialism can be seen as problematic since it can justify harming a small group of people as a justification for supporting a larger group. For example, using social media to maximize engagement could lead to promoting harmful content for maximum exposure.