It's beer o'clock: regularly scheduled programming edition

Data sovereignty and human rights in the suppoly chain both suffer from siloed thinking between business and academic research. How might we close the gap?

How might we provide a data sovereignty definition, framework, and... validated tech stack, quickly?

Electronic Markets provided this thoroughly lit review by Franziska von Scherenberg , Malte Hellmeier and, Boris Otto . As is becoming more apparent daily, a lack of solid theoretical taxonomy and framework for data as currency in this global economy threatens to bring the nations of the world into increasingly fragile states. Their excellent review shows an equal fragility in the research exposing that data sovereignty is not consistently defined and even contradicts itself. This team of German researchers promote a agency model and validate it with real-world examples and demonstrate what the constitutive elements of such a framework implemented would require, but it appears to us here that we need a tech stack to enable it. While these data sharing frameworks are crucial, what about a thorough vetting of existing blockchain and other cross-functional data management tools to provide a stack to enable it. In other words, I am asking: could the tools that have most threatened data sovereignty and digital identity and citizenship actually be what provides the tools that enable the remedy?

Why is there "economic complicity" between state actors and corporate actors in human rights abuses in the global supply chain when we know it is bad for the bottom line?

Despite the fact that Harvard Business Review, Economist Intelligence Unit, University of California Berkely, and the International Labor Organization have all published highly publicized research on the prevalence of human rights abuses that hurt the bottom line, troublingly what Tricia Olsen and Laura Bernal-Bermudez have called "economic complicity" between state and corporate actors persists. Bernal-Bermudez and Olsen contend that corporations can actually both clean up their own performance and actually intervene on behalf of humans when the state is engaging in abuse, and as the studies mention above achieve competitive and profit-based gains at the same time. Meanwhile, while most mainstream research improperly focuses on the global threat of job replacement "AI" represents through automation, more activist groups are exposing that data mining is creating a new form of digital enslavement as Sorab Ghaswalla writes in this Linked In article. As with the above article on data framworking there appears to be a large gap between socially-conscious business understandings and academic ones, impoverishing both cultures and blocking effective action. How might we close this gap?