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Cache. Cookies. Deepfake. Cloning. Spoofing. Algorithms.

Familiar words? But really—are they? Most of the netizens scroll past them, oblivious to how deep they go. Still, we scroll.

Scroll. React. Repeat.

Terminologies often appear in tech articles, app settings, or warnings that users click past without reading. They may seem abstract, just digital jargon in the background noise of daily scrolling. But each term holds real, tangible weight. Each one affects how people live and interact online. And they form a complex ecosystem, shaping the information users consume and the risks they face.

Cache stores fragments of data from websites and apps, speeding up experiences, but also keeping a quiet memory of a user’s behavior. Cookies, on the other hand, track user preferences and movement across the web. They tell websites what people like, what they've bought, and what they're likely to click next. Serves not just as passive tools, but as the frontlines of data mining.

Now, enter algorithms—designed to learn behavior: What does a user stop to watch? What do they skip? Who do they follow, mute, or block? Algorithms take this input and generate an output: a feed designed specifically for each user, tailored to their attention span, political views, sense of humor, or even insecurities.

Think about it: the first video you see on your “For You” page—was it really for you? Or did the algorithm push it because it knows you better than you know yourself?

It’s not magic; it’s not neutral. It’s machine learning. It’s engineered. Optimized not for your well-being or education, but for engagement—your attention, your emotion, your reaction.

Generally speaking, algorithms aren’t totally bad. In fact, they help make our digital experiences smoother, faster, and more personalized. Think of your favorite social media platforms or streaming services; they all use algorithms to recommend content based on your previous interactions, making it easier to discover new music, videos, and friends. Algorithms can sift through mountains of data in seconds, bringing us relevant results and helping businesses reach their audience more efficiently.

However, the very same algorithms that make our online lives easier can also shape our behavior, beliefs, and interactions in ways we don't even realize.

And here lies the danger: What’s personalized isn't always responsible. What keeps people engaged isn't always what keeps them safe. Engagement is the currency, and outrage, fear, and sensationalism often outperform nuance and truth.

In the average Filipino’s feed, one might find the now-ubiquitous pink-haired tarot reader flipping cards. Underneath that? A trending skit of a couple-turned-ex reenactment. A few scrolls later, a video of a girl dancing in a school uniform with text bubbles about grades, teachers, or love life.

It’s light, fun, and very Filipino. The content that breaks through isn’t always the most thoughtful or true; it’s what sparks dopamine. Humorous skits. Parody teachers. Trends that flatten reality for a laugh, a like, or a share.

And with every view, the system learns. What people react to, they receive more of. What they ignore fades; that’s not a coincidence. That’s curation, by code.

Behind the catchy trends lie the patterns of data breaches, identity theft, fake job offers, cloned accounts, and phishing links disguised as delivery updates or bank alerts.

The Philippines, according to the Kaspersky Security Network report, showed that the Philippines ranked 4th among the countries vulnerable to cyberattacks in 2023. One wrong click, and suddenly, it’s your information, identity, and savings that are compromised.

Yet, the basic digital safety practices remain uncommon. Many users don’t activate two-factor authentication. Many are unaware that their digital footprints—comments, photos, even deleted posts—can be used against them.

The irony? We’re exposed not just by hackers, but by ourselves. Every form autofills. Every password reuse. Every “Allow cookies” you don’t read. You’re leaving breadcrumbs—data trails—on platforms you don’t fully understand, managed by laws that barely exist.

What’s worse, awareness doesn’t always grow alongside internet use. In the excitement of going viral or trending, the basics of safety get ignored.

Deepfakes are no longer distant threats. From face-swap apps to fully AI-generated videos of public figures saying things they never said, deception is getting easier to create and harder to detect. Cloning—of accounts, of voices, of online identities—is becoming commonplace. People get scammed by “friends” who are not friends, and by relatives who are not relatives.

Spoofing lets scammers mimic email addresses or websites, tricking even the digitally literate. A fake university page offering scholarships. A spoofed job post promising part-time work for students. In a developing economy where many are just looking for opportunities, these tactics find easy victims.

Unfortunately, Philippine law has yet to catch up to these fast-evolving threats. The gaps are real. The Cybercrime Prevention Act of 2012, while a start, was created in an era before TikTok trends and AI-generated scams. There are no strong safeguards ensuring how algorithms operate, no transparency requirements for content recommendation systems, and very limited institutional support for cybersecurity education.

And this isn’t just an IT issue. This is a you issue.

In an era where digital life is real life—where Facebook often functions as both ID and resume, where TikTok is both entertainment and news source—the lack of safety and literacy is not a luxury problem. It's a foundational one.

Without stronger systems, the internet can quickly shift from a tool of empowerment to one of exploitation. It matters because young people should not have to navigate a minefield every time they open their phones. It matters because false information can spread faster than any correction. It matters because in a hyperconnected world, the weakest link can affect us all.

Being online shouldn’t mean being vulnerable.

The problem may feel too big, but the response doesn’t have to be.

It starts with education. Digital literacy must be included in school curricula, not just how to use tools, but how to understand them: how algorithms work, what phishing looks like, what data privacy means.

Then comes regulation. Tech companies must be pushed to reveal how content is promoted or demoted. Transparency in algorithmic design doesn’t kill innovation, it builds trust.

Next is empowerment. Users need to demand better security features and share knowledge when scams surface. Civil society must lead.

Notably, there must be a cultural shift. Not everything that’s popular is worth reposting. Not every comment needs a reaction. Not every feed deserves our attention.

The digital world is not neutral. It is designed. Built. Curated. And it is evolving faster than most users can understand.

But awareness is a kind of resistance. And resistance doesn’t require a protest—it can begin with a pause, a question, a second thought before clicking.

Click differently. Click your feed—but this time, don’t just scroll. Click with caution. Click with care. The real power belongs not just to the algorithm, but to the one who knows how it works.