The Present Bias Machine

How Algorithmic Media Warps Our Memory and Our Minds

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A plane crash, a mass shooting, a stock market plunge, a celebrity scandal—each of these events feels like the only thing that has ever happened. They dominate our feeds, spark endless discourse, and disappear almost as suddenly as they arrive, replaced by the next urgent headline. But something lingers: the subtle shift in our perception of reality.

Is the world more dangerous than before? Are disasters more frequent? Have things reached some unprecedented state of decline? Or is something else at play?

The Algorithmic Engine of Recency Bias

Psychologists Daniel Kahneman and Amos Tversky identified what’s known as recency bias—our tendency to give disproportionate weight to recent events when forming judgments. If something just happened, we assume it’s more common than it is. If it’s fresh in our minds, we overestimate its probability of happening again.

This is a well-documented cognitive shortcut, but what happens when it’s coupled with an information environment designed—at an architectural level—to maximize the prominence of the recent?

Algorithmic media, from social feeds to recommendation engines, prioritizes engagement. And nothing engages like what’s happening right now. Older information fades from visibility, often not because it’s irrelevant but because the machine values newness over depth. A breaking event isn’t just news—it’s fuel for the attention economy.

The result? Our brains, already wired for recency bias, are given an IV drip of confirmation. The event we just saw feels like it must be happening all the time because it’s all we see. Our priors—the mental models we use to predict the world—get rewritten, not based on statistical reality, but on what the algorithm chooses to show us.

There’s another effect at play: the shortening of cultural memory. The past has always been a contested space, but in an era where the pace of digital information erases context faster than ever, it barely stands a chance. What happened a week ago feels like ancient history. News cycles move at warp speed, and events that would have once shaped discourse for months are now buried under a deluge of new content.

The implications are profound. When each crisis feels without precedent, we lose the ability to learn from history. Patterns become invisible. We react like every new event is a one-off rather than part of a recurring cycle. This is particularly dangerous in public policy, financial markets, and social movements, where long-term memory is crucial for making informed decisions.

Fighting the Recency Machine

So, how do we push back against a system that feeds our worst cognitive instincts?

1. Seek context over immediacy. When a significant event occurs, look for historical parallels. Read long-form analysis, not just the breaking updates.

2. Resist the algorithm’s pull – Diversify your information sources. Be intentional about following thinkers who emphasize historical patterns and big-picture analysis.

3. Reclaim personal memory – If something feels unprecedented, ask: Is it? Find out when something similar happened before and compare.

4. Slow down – Our brains aren’t meant to absorb information at the pace of an algorithm. Taking breaks from the feed isn’t just healthy—it’s a form of cognitive resistance.

We can’t undo recency bias entirely—it’s built into how we process information. However, we can recognize how algorithmic media amplifies it and actively work to correct it. The past still matters, but only if we fight to remember it.

That’s it for now, thanks for reading, and see you again soon.