In the beginning it felt like a game: click the squares with a stop sign, type the words you see, reassemble a puzzle — and tick “I am not a robot.” Those tiny tasks, repeated millions of times, quietly turned users into unpaid labor for Big Tech.
Luis von Ahn coined “games with a purpose” in 2004 to harness human intelligence for tasks that computers then struggled with: labeling images, transcribing text, classifying data. His ESP Game paired strangers to produce matching image labels. Google adapted the idea for the Google Image Labeler, and von Ahn later created reCAPTCHA — where solving CAPTCHAs helped digitize words from scanned books. He sold reCAPTCHA to Google in 2009. He then co-founded Duolingo in 2011, applying crowdsourcing to language learning: users translate and label content in exchange for free lessons, generating valuable language data that trains AI and supports commercial services.
What began as a contribution to a shared commons instead turned into privately captured data. As Ulises Mejias puts it, the original hope was that collective effort would benefit everyone, but instead that work was consolidated, sold, and monetized.
That outcome contrasts sharply with the internet’s countercultural roots. In the 1960s and 1970s, many Northern California thinkers imagined digital networks as communal and liberating. Stewart Brand’s early virtual community The WELL and the slogan “information wants to be free” embodied that optimism. Figures like Steve Jobs and John Perry Barlow drew from counterculture ideals when imagining cyberspace.
Yet taking politics out of technology was naive. Stanford historian Fred Turner argues that those who built early digital communities recreated familiar hierarchies rather than escaping politics. The utopian dream gave way to monetization: search engines, algorithms, and massive data collection turned the social web into a resource to be mined.
Early platforms explicitly gathered vast amounts of user data to monetize. What began as connection morphed into extraction — people’s attention and activity became raw material sold back as targeted advertising and products. As Turner puts it, digital media became mining industries; users became the resource.
Ulises Mejias and Nick Couldry call this dynamic “data grab” and liken it to a new form of colonialism: the systematic taking of a common resource for the benefit of a small elite. AI and machine learning are the latest technologies layered on top of that extraction, turning aggregated human contributions into proprietary models and services.
Three decades after bold declarations of a free, independent cyberspace, the internet’s infrastructure, platforms, and profit flows are concentrated in the hands of a few corporations. For many critics, this represents a deception: while users built shared knowledge and community, platforms privatized and monetized it.
There are signs of pushback. Communities resist new data centers, gig workers organize for better conditions, and younger generations express deep disillusionment with digital life. Surveys report many young people would prefer a world without the internet or see social media as harmful. That discontent fuels calls for change.
The remedy, Turner argues, is political more than technical. Rather than focusing solely on machine capabilities, society must decide what we want these technologies to do for the public good. The counterculture imagined technology could free people, but it failed to grapple with power and governance. If the internet is to recover its promise, attention must shift from innovation alone to politics, policy, and collective control over data and platforms.