THE ALGORITHM VS. THE HUMAN MIND: A LOSING BATTLE
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NO RECOGNITION FOR THE AUTHOR
YouTube does not reward consistency, insight, or author reputation. A comment may become a “top comment” for a day, only to vanish the next. There’s no memory, no history of editorial value. The platform doesn’t surface authors who contribute regularly with structured, relevant input. There's no path for authorship to emerge or be noticed. The “like” system favors early commenters — the infamous firsts — who write “first,” “early,” or “30 seconds in” just after a video drops. These are the comments that rise to the top. Readers interact with the text, not the person behind it. This is by design. YouTube wants engagement to stay contained within the content creator’s channel, not spread toward the audience. A well-written comment should not amplify a small creator’s reach — that would disrupt the platform’s control over audience flow.
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USERS WHO’VE STOPPED THINKING
The algorithm trains people to wait for suggestions. Most users no longer take the initiative to explore or support anyone unless pushed by the system. Even when someone says something exceptional, the response remains cold. The author is just a font — not a presence. A familiar avatar doesn’t trigger curiosity. On these platforms, people follow only the already-famous. Anonymity is devalued by default. Most users would rather post their own comment (that no one will ever read) than reply to others. Interaction is solitary. YouTube, by design, encourages people to think only about themselves.
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ZERO MODERATION FOR SMALL CREATORS
Small creators have no support when it comes to moderation. In low-traffic streams, there's no way to filter harassment or mockery. Trolls can show up just to enjoy someone else's failure — and nothing stops them. Unlike big streamers who can appoint moderators, smaller channels lack both the tools and the visibility to protect themselves. YouTube provides no built-in safety net, even though these creators are often the most exposed.
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EXTERNAL LINKS ARE SABOTAGED
Trying to drive traffic to your own website? In the “About” section, YouTube adds a warning label to every external link: “You’re about to leave YouTube. This site may be unsafe.” It looks like an antivirus alert — not a routine redirect. It scares away casual users. And even if someone knows better, they still have to click again to confirm. That’s not protection — it’s manufactured discouragement. This cheap shot, disguised as safety, serves a single purpose: preventing viewers from leaving the ecosystem. YouTube has no authority to determine what is or isn’t a “safe” site beyond its own platform.
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HUMANS CAN’T OUTPERFORM THE MACHINE
At every level, the human loses. You can’t outsmart an algorithm that filters, sorts, buries. You can’t even decide who you want to support: the system always intervenes. Talent alone isn’t enough. Courage isn’t enough. You need to break through a machine built to elevate the dominant and bury the rest. YouTube claims to be a platform for expression. But what it really offers is a simulated discovery engine — locked down and heavily policed.
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||#HSLdiary #HSLmichael
Europe’s new Platform Work Directive gives gig workers new rights to challenge surveillance, wage theft & algorithmic control 
https://www.eff.org/deeplinks/2025/10/what-europes-new-gig-work-law-means-unions-and-technology
to 
Dr. Thilo Hagendorff, our research group leader at IRIS3D, has taken this question seriously and systematically. With his interactive Ethics Tree, he has created one of the most comprehensive overviews of ethical problem areas in generative AI: 
Myth-busting: AI isn’t always intelligent—it reflects the data it’s fed. Biased training data can lead to discriminatory outcomes in hiring, policing, even credit scores.
Always ask: Who trained the AI? On what data?
Since 
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