While ideological slants exist, the fundamental driver of modern media is negativity. Catastrophic framing and outrage-inducing content are proven to boost virality and engagement, creating a 'stew of negativity' that is more about business models than political affiliation.

Nuanced health discussions are lost on social media algorithms that reward extreme takes. While more experts should engage, the long-term solution is to build new platforms, likely AI-driven, that prioritize substance over engagement and aren't designed to exploit our primitive impulses for profit.

A/B testing on platforms like YouTube reveals a clear trend: the more incendiary and negative the language in titles and headlines, the more clicks they generate. This profit incentive drives the proliferation of outrage-based content, with inflammatory headlines reportedly up 140%.

The addictiveness of social media stems from algorithms that strategically mix positive content, like cute animal videos, with enraging content. This emotional whiplash keeps users glued to their phones, as outrage is a powerful driver of engagement that platforms deliberately exploit to keep users scrolling.

Social media algorithms reward content that triggers high-arousal emotions like anger, fear, and awe, as these lead to engagement. Contentment, a low-arousal state, doesn't prompt users to click or share, so it is systematically de-prioritized, favoring rage bait.

Unlike social media's ad model, AI's revenue is driven by enterprise clients who demand accuracy for business use. This creates a powerful financial incentive for AI labs to prioritize truthfulness over virality, a complete reversal from the social media era that could benefit information quality.

Social media algorithms optimize for engagement, often amplifying divisive content. In contrast, LLMs must optimize for accuracy and truth to retain user trust. This fundamentally different business model positions LLMs as a potential societal antidote to algorithmic polarization.

Ben Smith argues that while distribution channels (like social video) pull content towards polarization for maximum engagement, a quality media brand must build the discipline to resist this pull. The focus should be on the target audience's needs, not the platform's algorithm.

The promise of new media was to foster deep, nuanced conversations that legacy outlets abandoned. However, it is increasingly falling into the same traps: becoming predictable, obsessed with personality feuds, and chasing clicks with inflammatory content instead of pursuing truth.