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It wasn’t long ago that the worry was that rich students would have access to the internet earlier, gaining tech skills and creating a digital divide. Schools ask students to do homework online, while only about two-thirds of people in the U.S. have broadband internet service. But now, as Silicon Valley’s parents increasingly panic over the impact screens have on their children and move toward screen-free lifestyles, worries over a new digital divide are rising. It could happen that the children of poorer and middle-class parents will be raised by screens, while the children of Silicon Valley’s elite will be going back to wooden toys and the luxury of human interaction.

With such ubiquity comes power and influence. And along with the technology’s benefits come worries over privacy and personal freedom. Yes, AI can take some of the time and effort out of decision-making. But if you are a woman, a person of color, or a member of some other unlucky marginalized group, it has the ability to codify and worsen the inequalities you already face. This darker side of AI has led policymakers such as U.S. Senator Kamala Harris to advocate for more careful consideration of the technology’s risks.

Today, we can see a similar pattern emerging with the deployment of AI. Good intentions are nice, but they must account for and accommodate a true diversity of perspectives. How can we trust the ethics panels of AI companies to take adequate care of the needs of people of color, queer people, and other marginalized communities if we don’t even know who is making the decisions? It’s simple: we can’t and we shouldn’t.

Data is no less a form of common property than oil or soil or copper. We make data together, and we make it meaningful together, but its value is currently captured by the companies that own it. We find ourselves in the position of a colonized country, our resources extracted to fill faraway pockets. Wealth that belongs to the many — wealth that could help feed, educate, house and heal people — is used to enrich the few. The solution is to take up the template of resource nationalism, and nationalize our data reserves.

Emphasising time well spent means creating a Facebook that prioritises data-rich personal interactions that Facebook can use to make a more engaging platform. Rather than spending a lot of time doing things that Facebook doesn’t find valuable – such as watching viral videos – you can spend a bit less time, but spend it doing things that Facebook does find valuable. In other words, “time well spent” means Facebook can monetise more efficiently. It can prioritise the intensity of data extraction over its extensiveness. This is a wise business move, disguised as a concession to critics. Shifting to this model not only sidesteps concerns about tech addiction – it also acknowledges certain basic limits to Facebook’s current growth model. There are only so many hours in the day. Facebook can’t keep prioritising total time spent – it has to extract more value from less time.

But let’s assume that our vast data collective is secure, well managed, and put to purely democratic ends. The shift of data ownership from the private to the public sector may well succeed in reducing the economic power of Silicon Valley, but what it would also do is reinforce and indeed institutionalize Silicon Valley’s computationalist ideology, with its foundational, Taylorist belief that, at a personal and collective level, humanity can and should be optimized through better programming. The ethos and incentives of constant surveillance would become even more deeply embedded in our lives, as we take on the roles of both the watched and the watcher. Consumer, track thyself! And, even with such a shift in ownership, we’d still confront the fraught issues of design, manipulation, and agency.