Yu Xiong is Chair Professor of Business Analytics at Surrey Business School.
We are all familiar with the small group of social media giants that have mastered the art of monetizing attention. Platforms like TikTok, Instagram, Facebook and X are engineered to keep us engaged, serving up content designed to trigger dopamine responses and sustain endless scrolling. Research shows that features such as algorithmic recommendations and frictionless feeds can disrupt self-awareness, creating a “compulsion loop” that keeps users coming back for more.
Many remember a more carefree era of the internet: a time when sharing photos or personal updates felt spontaneous rather than strategic. Back then, few people gave much thought to the fact that their data could be captured, analyzed and commercialized behind the scenes.
That changed when human behavior itself became the most valuable product online. Every click, pause and swipe began feeding business models built on behavioral prediction. The vast data trails we leave now power what Shoshana Zuboff famously called “surveillance capitalism,” a system in which user experience is continuously extracted, analyzed and monetized.
You might also hear this described as “platform capitalism”—a model where value is extracted rather than shared, and where users’ contributions enrich platform owners far more than the communities themselves. From the social-media boom of the late 2000s to the rise of mobile apps in the 2010s and AI-driven content in the 2020s, this imbalance has only deepened. Today, a small group of technology firms mediate much of our cultural and economic life online, shaping how we interact, consume and even perceive information.
Yet there are emerging pockets of resistance, united by a single question: What would the internet look like if it served people again? Too often, these ideas are dismissed as unrealistic, especially when they invoke blockchain or decentralized technologies.
But a return to some of the early web’s values may be more achievable than many think. We are edging toward a digital landscape where individuals can retain ownership of their data, creativity and attention, rather than surrendering it entirely to centralized platforms.
This shift can already be seen in open-source collaborations and decentralized networks such as Mastodon, where communities run their own servers and set their own rules. The technology exists, and it can scale, but adoption remains the main challenge. For these ideas to gain traction, they need more than technical proof. They require economic incentives and governance systems that make participation genuinely worthwhile.
Still, many believe that the current system may need to falter before genuine change occurs. The issue of digital identity offers a glimpse of this tension. For years, our online selves have been fragmented across countless logins and profiles, each reducing individuality to a dataset.
New models—from decentralized IDs to verifiable credentials—promise users greater ownership and portability of identity. But they also raise difficult questions: Who oversees verification, how do we prevent exclusion and what happens when systems designed for trust fail? Even traditional “know your customer” schemes have resulted in significant data breaches, exposing the fragility of centralized models.
Beneath these technological experiments lies a broader cultural challenge: rebuilding trust. Consent, once a meaningful principle of autonomy, has been reduced to a series of perfunctory clicks on “I accept” boxes, often with little understanding of what is being agreed to.
Restoring it will require infrastructure that genuinely empowers users to see, manage and control how their information is used. Technologies such as blockchain can make transparent consent management technically possible, but without careful governance, they risk recreating the same hierarchies we are trying to escape.
Alongside these debates about infrastructure sits a new creative one. AI is transforming how culture is produced and shared, raising urgent questions about ownership, authenticity and originality.
Research suggests that as AI-generated content multiplies online, it increasingly trains on itself, producing a feedback loop that erodes distinctiveness and trust. A recent report from Axios found that although AI-written web pages briefly outnumbered those written by humans, the two are now roughly equal, highlighting concern that AI is heading toward self-referential collapse. The challenge ahead is to use AI as a collaborator—an amplifier of human imagination—rather than a substitute for it.
Taken together, these developments signal an internet in transition: one moving, slowly but perceptibly, from extraction toward participation. Yet that shift will not happen by accident. It will require new institutions, fairer economic models and a collective willingness to question whether convenience should remain the internet’s ultimate design goal. If we can learn to value agency and authenticity as much as efficiency, then the web’s next chapter may yet belong to its users once again.
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