As hardware continues to advance with more powerful GPUs and specialized ASICs, does the work factor the cost parameter in bcrypt provide enough of a future-proof shield, or will we eventually reach a point where even the maximum slowness we can tolerate for a legitimate user login is no longer enough to deter a massive parallel attack?

What do you think? is there a limit to how much we can keep slowing things down before it breaks the user experience

I think that this the be common practice is really outlandish. To have non-encrypted passwords for anyone with database access to have is crazy to me. There has to be a better way for personal information to be stored, correct?

This source refers to the Wikipedia page for the film Everything Everywhere All at Once as it appeared on December 5, 2023. Given its place in a bibliography about data mining, the movie likely serves as a metaphor for the overwhelming and fragmented nature of modern digital surveillance. It highlights how our personal lives exist across a sprawling multiverse of datasets that companies constantly try to map and unify.

This is another reason why this whole surge of lookism is so destructive for society and young people's mental health. Now it is "looksmaxing." The fringe gets pushed to the top of the algorithm and slowly moves the overtin window. This means that it becomes more and more ok to say and do outlandish things that people deem to be right or ok.

I believe that this is why we can't have nice things, mapping the relationship between online trolling and mainstream culture by MIT Press, in 2015. The book explores the blurred lines between trolling for the lulz and the ethical implications of how mainstream media amplifies that behavior, fitting perfectly with the book's focus on the intersection of automation and ethics. https://mitpress.mit.edu/9780262529877/this-is-why-we-cant-have-nice-things/

I believe that it mostly has to do with isolation. If a clip of a troller goes viral because it is disruptive by its nature. This means that the person who probably spends a lot of time in isolation gets to be seen, heard, and recognized by others in the community, thus refeeding into the cycle of troll.

This analysis highlights how metadata can serve as an empirical measure of authenticity, effectively unmasking the dual-persona strategy used by public figures. By identifying the stark contrast between the polished, staff-driven iPhone posts and the more aggressive, personal Android updates, the study reveals how accounts often act as sockpuppets for multiple voices. This discrepancy can lead to a significant loss of trust, as it exposes the curation behind a supposedly authentic brand and shows how tone can be weaponized to manipulate public sentiment.

This case illustrates the profound ethical dangers of inauthentic behavior on social media, specifically through the creation of a sockpuppet account by Dr. BethAnn McLaughlin. By fabricating Sciencing_Bi, McLaughlin engaged in a form of "digital blackface" that exploited marginalized identities to gain clout and shield herself from accountability. The ultimate deception, faking the character’s death during the COVID-19 pandemic, demonstrates how easily emotional trust can be weaponized, leaving a lasting impact on the very communities the MeTooSTEM movement sought to protect.

This source provides a foundational summary of HyperText Markup Language (HTML), explaining that it is the standard markup language for creating web pages by describing the structure of a webpage through a series of elements. A key detail from the source is that HTML elements tell the browser how to display content, using tags like

for headings and

for paragraphs to label pieces of content.

On Instagram, a single post distills complex human experiences into a structured collection of Strings (usernames and captions), Integers (like counts), DateTimes (relative post age), and Binary/Blob data (the image or video itself). These digital artifacts act as a significant simplification of reality by flattening three-dimensional, multi-sensory moments into a 2D frame that lacks the physical context, emotional depth, or the "unfiltered" events occurring just outside the camera's view. This system works exceptionally well for "influencers" and brands who benefit from highly curated, aesthetic-first storytelling that drives rapid engagement.

Several surprising bots focus on transparency, such as NYPDedits, which monitors Wikipedia for anonymous edits coming from police department IP addresses to ensure institutional accountability. Among the bots users often like are helpful utility tools, such as Musico Bot on Discord for shared listening experiences, or customer service bots that provide 24-hour support. Conversely, many dislike antagonistic bots that are designed for deception, such as those used for spamming or artificially manipulating public opinion. Ultimately, because these bots lack human intent, their actions are viewed as technical functions of their programming rather than personal choices, which shifts the moral weight of their behavior onto the developers who run them.

Expectations for bots focus on efficiency, speed, and rigid adherence to code, whereas normal users are expected to possess empathy, social nuance, and accountability for their "intent." For example, a unit conversion bot can scan thousands of posts to provide instant metric offsets that a task a human could not perform at that scale without extreme fatigue. These bots are typically managed by independent developers who use APIs to automate actions. Because a bot lacks personal will, we often view its errors as technical bugs rather than moral failings, shifting the ethical responsibility back to the person who created or ran the program.

How often do I hear someonthing along the lines of "social media isn't real life." Actually very often. It was a running joke in my friend group so much so that one of my friends made his bio "Instagram isn't real life." On some levels, I agree to this statement, and on others, I totally disagree. The things that people do and say on social media have adverse effects on their real-life circumstances. For example, the lady who lost her job because of a racist tweet. That had a real-world effect. On another level, the things people post sometimes just aren't reality. The unrealistic beauty standards for teens and young people are so far beyond what reality is that it tarnishes people's self-image and can lead to depression and alienation.

I believe that the reason so many people saw the tweet was that it was fringe in nature. Social media doesn't push out the most sensible takes. It shows the ones that get a reaction out of people. Then there was a snowball effect on the tweet, as it got more traction, it reached a wider and wider audience. I bet most people didn't even see the original tweet first. They saw someone who tweeted about the tweet. That's how the virality of social media works.