The Attention Engine
カートのアイテムが多すぎます
カートに追加できませんでした。
ウィッシュリストに追加できませんでした。
ほしい物リストの削除に失敗しました。
ポッドキャストのフォローに失敗しました
ポッドキャストのフォロー解除に失敗しました
-
ナレーター:
-
著者:
概要
Episode Overview
Most of us assume that what we see online is largely the result of our own choices. In reality, much of the modern internet is shaped by recommendation systems designed to keep our attention for as long as possible.
These systems learn continuously from our behaviour - what we click, how long we pause on a post, what we watch to the end - and use those signals to decide what appears next in our feeds.
In this episode of Fact & Friction, we explore the 'attention engine' behind modern digital platforms. Harry and Sean unpack how engagement‑driven algorithms work, why emotionally charged content tends to travel further, and how repeated exposure subtly shapes what feels important, urgent, or interesting. The goal is not to criticise technology but to understand the incentives behind it, and to give listeners practical ways to regain control over where their attention goes.
In This Episode
- How recommendation algorithms learn from clicks, pauses, and watch time
- Why engagement - not accuracy - is often the core metric shaping online feeds
- How emotional and novelty‑driven content spreads faster than neutral information
- The subtle signals that indicate your attention is being steered
- Simple habits that introduce friction and help you regain control of your digital focus
The Point of Friction
- Common narrative: Social media simply shows you the content you choose to engage with.
- Underlying reality: Engagement algorithms actively shape those choices by amplifying the content most likely to keep you watching, scrolling, and reacting.
Why It Matters
Attention sits upstream of many decisions we make each day. What we see repeatedly influences what we think about, what we feel is important, and how we interpret events. When digital systems are designed primarily to maximise engagement, they naturally prioritise content that captures emotion and curiosity. Understanding how these systems operate helps listeners recognise when their attention is being nudged, and restores the ability to choose where their focus truly belongs.
Listener Reflection
What captured your attention online today, and did you deliberately choose it, or did it appear repeatedly until it felt important, and you’d spent a lot more time engaged with it than you intended?
Next Episode
In Episode 2 we explore 'rabbit holing' - how recommendation systems can quietly steer curiosity toward increasingly dramatic or extreme content, often without the user realising the journey is being guided.