augmented interface for pulling data out of a spreadsheet

Data Dignity at RadicalxChange

Back in March this year we headed to Detroit for RadicalxChange, a conference with the stated goal of finding positive alternatives to “rising inequality, stagnating economies and increasing threats to liberal democracy from populists of the left and right.” Our contribution was a talk showing four concrete examples of ways people could buy and sell their data, rather than having it taken without their knowledge or permission, as part of a more humanizing future for AI and attention economies. The talk itself is a half hour, and there’s a lengthy question and answer session afterward.

We got a lot of questions after the talk and during the conference more generally. Here are a few of the themes that we noticed:

  • Digital identity. There were a lot of blockchain folks at this event interested in identity, and lots of recognition that digital identity is going to be an important part of things. This is an area that needs work, though everyone seems to agree it’s important.
  • Second-order effects and wealth inequality. Will wealthy people’s data be more valuable because wealthy people are willing to pay more to other wealthy people for their comparatively rare and exclusive data about wealthy people things? In practice, will this tend to widen existing class divides due to differing data labor skills? How do we keep the side-effects of problems in our current system from feeding back into destructive loops? What other second-order effects should we watch out for?
  • Data theft, bad actors, enforcement, and liability. How do you prevent people from stealing and reselling data? What is your liability if your data contributes to a harmful decision? What if your data is unintentionally bad? Or intentionally bad? How do we set good precedents and create good social norms?
  • Incriminating data. What happens when data includes evidence of small usually unenforced infractions such as jaywalking or speeding, and what is the responsibility of data unions, collectives, individual sellers, and buyers regarding this type of data? How do we avoid enabling biased enforcement? How might the law be changed?
  • Government Programs. There was an interesting discussion about the difference between data unions and the idea of a potential government social program version, and how that interacts with taxes, privacy rights, and other rights. For example, giving health data in exchange for socialized healthcare.
  • Implementation. How to get from here to there, who makes the rules and what kinds of rules are allowed, and how to trace individual contributions
  • Everyone loves Toast Space.

The biggest takeaway is that there is a growing community that is passionate and invested in the future of data dignity.

We’ve learned a lot in the months since giving this talk, as reflected in more recent work. We’ve also found ourselves talking to more folks involved with government and collecting more perspectives. Hopefully we’ll keep learning more as the community digs in to some of these questions!

Vi + M