Keith Porcaro

5/x In finance, trust structures help people take advantage of expertise and diversification that may be unachievable on their own. #datatrusts

6/x For data, the analog isn't personal data (I argue), but organizations who hold data that may be collected for one purpose, but useful for others. Consider, say, hospital records that may have secondary uses for research. #datatrusts

7/x An organization, especially one that is data immature, may not be well-equipped to manage third-party data relationships. This goes beyond "having a standard contract"—it's about ensuring the relationship plays out as expected. #datatrusts

8/x This can be a good fit for a trust. A data trustee acts on behalf of an organization to manage third-party relationships around data. #datatrusts

9/x In my paper, I discuss variants on this basic model: a "blind trust" where a data analysis company is held in trust and the shareholders are beneficiaries (like @Truata1 ); managing a multi-party collaboration; and isolating data from bankruptcy risks. #datatrusts

10/x Of course, data is different from other assets. It’s not as obviously ascertainable; its value comes from inferences and discoveries derived from the data; duties of care around data management are underdefined. #datatrusts

11/x I argue that #datatrusts trusts may not be a good fit for regulating users' relationships with a platform. Data can be freely replicated, and a "user trust" may not be able to prevent users from cutting side deals, undermining the negotiating leverage of the trust.

12/x In modern trusts, (especially in NA), the trust document plays a dominant role in setting the terms of the trust. It can override defaults in trust law. This means that a commercial trust arguably prioritizes a settlor's intent over beneficiary interests. #datatrusts