🧠 How AI Hijacks the Moments That Make Us Human

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Welcome back AI prodigies!

In today’s Sunday Special:

• 📜The Prelude

• 🔮How Predictive AI Maximizes Attention

• 🧭What It Means for Us

• 🤖How We Stop Being Human

• 🔑Key Takeaway

Read Time: 7 minutes

🎓Key Terms

• Predictive AI: The ability to identify patterns, anticipate behaviors, and forecast future preferences.

• Deep Learning (DL): Mimics the human brain by creating multiple layers of artificial neurons to solve complex problems without needing explicit programming.

🩺 PULSE CHECK

📜THE PRELUDE

You just spent hours scrolling through YouTube Shorts and listening to Spotify’s AI DJ, where every swipe, scroll, and sound was meticulously designed to capture your attention and learn your preferences. And yet, a quiet emptiness lingers.

We live in the most connected era in human history, with an infinite amount of access to content filled with constant interaction. Even so, we still feel increasingly disconnected from ourselves.

Why do we feel so disconnected, even as digital engagement continues to soar? How does Predictive AI eliminate the quiet moments where self-awareness is developed?

🔮HOW PREDICTIVE AI MAXIMIZES ATTENTION

⦿ 1️⃣ What It Maximizes.

It’s no secret that the most popular social media platforms, including TikTok, YouTube, and Instagram, are engineered to farm our engagement. So, how do they achieve this?

They rely on DL, which emulates how our brain processes information. DL is deployed to detect, understand, and predict what we want to see. More specifically, these social media platforms utilize Artificial Neural Networks (ANNs), which establish relationships between Inputs and Outputs.

⦿ 2️⃣ What It Observes.

Inputs are measurable characteristics about:

1. User Behavior: What you watch, click, save, share, or skip.

2. Content Metadata: Content details like video length, audio used, and upload date.

3. Contextual Signals: Situational conditions like location, time of day, and device used.

All these Inputs are funneled into the ANNs, which process them through multiple specialized layers, each designed to identify specific patterns. These specific patterns are used to develop Outputs that predict how a certain user will respond to specific content.

⦿ 3️⃣ What It Predicts.

Outputs represent predicted user engagement patterns, including:

1. Emotional Classification: Assessing whether a user’s reaction will be positive, neutral, or negative.

2. Binary Classification: Categorizing user behavior into one of two classes: “Will Click” or “Won’t Click.”

3. Engagement Forecasting: Predicting a user’s total watch time, average number of shares, or frequency of comments.

The ANNs generate a probability, such as: P(Watch ≥ 30s | Inputs) = 0.87. This means: given the Inputs, there’s an 87% chance that you might watch at least 30 seconds of this 37-second video.

⦿ 4️⃣ What It Causes.

When the predictions are accurate, our brief moments to disconnect disappear. You don’t stop to think; you just scroll to the next TikTok, YouTube Short, or Instagram Reel. This endless scrolling erodes the quiet moments that allow you to develop self-awareness. So, what exactly does that mean?

🧭WHAT IT MEANS FOR US

⦿ 5️⃣ For Our Behavior.

By eliminating natural pauses between videos, Predictive AI replaces micro-moments of mental silence with continuous, optimized stimulation. On YouTube Shorts, 70% of the time spent viewing videos is driven by algorithmic recommendations, leaving only 30% for active content discovery. As a result, viewers have fewer moments to process what they’ve just watched.

When’s the last time you drove to a destination or ate a meal without the impulse to listen to music or watch a video? The Pew Research Center found that 67% of 18- to 29-year-olds “often” or “almost constantly” feel the need to check their smartphone. Moments that used to serve as natural breaks are now filled with content engineered to hold our attention.

⦿ 6️⃣ For Our Sense of Self.

Without reflection, we can’t metabolize experience into identity. This cognitive function is what American educational psychologist Richard E. Mayer refers to as Elaborative Processing: the active mental work of connecting new information to existing memories, values, and beliefs. This isn’t a passive function; it demands attention, time, and most critically, solitude.

Elaborative Processing is how we update our internal models of the world. For example, after a difficult conversation, we might later think, “Why did that bother me so much?” or “What does that say about what I value?” Intentional reflection helps weave our lived experiences into a broader narrative of self. Without it, experiences pile up without structure. We may remember events, but we don’t fully understand how they’ve changed us.

As Predictive AI becomes better at preempting boredom, we lose the empty spaces that once served as the stage for self-reflection. Over time, the risks compound. Without mental stillness, identity becomes fragmented and reactive.

🤖HOW WE STOP BEING HUMAN

⦿ 7️⃣ The Death of Uncertainty.

The erosion of solitude is rewiring what makes us distinctly human. As Predictive AI becomes better at anticipating our needs, we’re losing capacities that’ve defined our species for millennia.

We evolved to navigate uncertainty. For thousands of years, we didn’t know what lay beyond the next hill, whether the harvest would succeed, or how a conversation might unfold. This uncertainty compelled us to develop remarkable cognitive abilities, including imagination, planning, emotional resilience, and the capacity to tolerate ambiguity.

When TikTok serves content that feels telepathically tailored, when YouTube Shorts knows your viewing preferences better than you do, and when Spotify creates playlists that capture your exact mood, you stop asking yourself: “What do I actually want?”

Predictive AI eliminates these micro-level uncertainties. While this may seem convenient, it weakens the mental muscles we use to anticipate, choose, and cope with the unknown.

⦿ 8️⃣ The Outsourcing of Desire.

Perhaps most troubling is how Predictive AI shapes our preferences. For instance, content feeds on social media platforms teach us what to like by repeatedly exposing us to variations of content that previously held our attention. This creates a feedback loop where our desires become increasingly narrow and predictable. Over time, we forget whether we genuinely care about a certain topic or if we’ve simply been trained to engage with it.

We’re witnessing the gradual outsourcing of human curiosity to AI-powered systems and machine-optimized frameworks. Instead of developing our own sense of what we find beautiful, interesting, or meaningful, we defer to AI-enabled algorithms optimized for engagement metrics that resemble little relationship to human flourishing.

🔑KEY TAKEAWAY

Predictive AI eliminates moments of mental stillness by constantly filling attention gaps with optimized content, eroding our capacity for reflection. Without these quiet moments, we lose the ability to process our experiences into a meaningful identity.

Over time, this leads to an increasing dependence on AI to guide our moods, choices, and desires. The more machines predict what we want, the less we remember how to want for ourselves.

📒FINAL NOTE

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