Publishing Meta

The Playlistification of Publishing: A Dangerous Illusion or a Strategic Opportunity?

The idea of publishers adopting a Spotify-like model—curating content that evolves in real time based on user behaviour—is undeniably seductive. It suggests a future where readers are served a personalised stream of articles, essays, and interactive features tailored to their tastes, interests, and engagement patterns. But while this vision might seem like the logical next step for an industry grappling with declining ad revenues and shifting reader expectations, it also raises uncomfortable questions about data privacy, editorial integrity, and the fundamental purpose of publishing.

The Tech Mirage of Personalisation

At its core, the comparison to Spotify hinges on two technological pillars: artificial intelligence and metadata. AI promises the ability to analyse user engagement—time spent on articles, scroll depth, click-through rates—and translate this into actionable insights. Metadata provides the tags and classifications that make content modular, searchable, and ostensibly “smart.” Together, these tools create the illusion of a publishing ecosystem that can anticipate user needs and adapt like a living organism.

But this approach, for all its technological allure, glosses over a critical issue: the difference between music streaming and knowledge dissemination. Spotify’s playlists are transient; they serve a mood, a moment, or an activity. Publishing, particularly in educational contexts, isn’t just about delivering what readers want—it’s about delivering what they need. Curating content based on engagement metrics risks reducing knowledge to entertainment, privileging clickbait over substance and reinforcing existing biases.

Data Privacy: The Elephant in the Room

To build “content ecosystems that think like Spotify,” publishers would need to collect and process vast amounts of user data. This is where the parallels with edtech become particularly troubling. Education technology has long been criticised for its cavalier approach to privacy, with platforms hoarding student data under the guise of personalisation. If publishers adopt similar practices, they risk creating a surveillance economy where every scroll, click, and share is tracked, analysed, and monetised.

What safeguards will exist to prevent this data from being exploited? Will readers have meaningful control over how their information is used? And, more importantly, how will publishers reconcile the tension between editorial independence and algorithmic optimisation? These questions remain conspicuously absent from the conversation.

The Spotifyisation of Editorial Vision

The LinkedIn post frames this shift as a way to “deliver editorial vision more intelligently,” but that phrasing itself warrants scrutiny. Editorial vision is inherently human—it’s shaped by curiosity, judgement, and cultural context. Outsourcing it to algorithms risks flattening nuance and complexity, turning publishers into little more than content vending machines.

Spotify’s model works because music consumption is fundamentally passive; you don’t need to think deeply about the song playing while you work out or commute. Publishing, particularly when dealing with news, education, or thought leadership, is different. Readers engage with content not just to consume, but to learn, reflect, and challenge themselves. Reducing this experience to a feedback loop of clicks and skips risks undermining the very purpose of publishing.

Who’s Really in Control?

The drive toward personalised content ecosystems isn’t just a technological challenge—it’s a power shift. Platforms like Spotify have demonstrated that whoever controls the recommendation engine controls the market. As publishing moves toward playlistification, the risk is that editorial teams lose control of their audiences to data-driven intermediaries. Will publishers end up ceding power to tech platforms, much like the music industry did? Or will they find ways to adopt these technologies without sacrificing autonomy?

For educators and institutions, the implications are equally profound. If content becomes modular and algorithmically curated, who decides what students see? Will personalisation lead to more equitable access to knowledge, or will it reinforce existing inequalities by feeding students content that aligns with their socioeconomic status or prior performance?

A Future Built on Questions, Not Just Technology

The idea of publishers building playlists instead of products isn’t inherently bad—it’s just incomplete. The LinkedIn post focuses on what’s technologically possible without asking the harder questions about what’s ethically, culturally, or strategically desirable. Before rushing to implement AI-driven content ecosystems, publishers need to grapple with the consequences of their choices.

How will these systems shape public discourse? What happens to the serendipity of discovering something unexpected, something that doesn’t fit neatly into an algorithmic box? And what responsibility do publishers have to ensure their platforms serve the public good, not just corporate interests?

The playlistification of publishing may be inevitable, but it’s far from straightforward. If publishers want to build ecosystems that genuinely serve readers, they need to look beyond Spotify’s model and ask themselves what kind of world their technology is creating. Because once the algorithms take over, it may be too late to change course.