Policy Brief
The authors highlight why we believe the problem of “plural publics” to be a core challenge of data governance, discuss existing tools that can help achieve it and a research agenda to further develop and integrate these tools.
By:
Divya Siddarth
Glen Weyl
Shrey Jain
Data governance is usually conceptualized in terms of “privacy” v. “publicity”. Yet a core feature of pluralistic societies is association, groups that share with each other, privately. These are a diversity of “publics”, each externally private but with the ability to coordinate and share internally. Empowering them requires tools that allow the establishment of shared communicative contexts and their defense against external sharing outside of context. The ease of spreading information online has challenged such “contextual integrity” and the rise of generative foundation models like GPT-4 may radically exacerbate this challenge. In the face of this challenge, we highlight why we believe the problem of “plural publics” to be a core challenge of data governance, discuss existing tools that can help achieve it and a research agenda to further develop and integrate these tools.
Occasional Paper
In a new working paper, Crocodile Tears: Can the Ethical-Moral Intelligence of AI Models Be Trusted?, Allen Lab authors Sarah Hubbard, David Kidd, and Andrei Stupu introduce an ethical-moral intelligence framework for evaluating AI models across dimensions of moral expertise, sensitivity, coherence, and transparency.
Open Access Resource
Allen Lab for Democracy Renovation Senior Fellow Allison Stanger, in collaboration with Jaron Lanier and Audrey Tang, envision a post-Section 230 landscape that fosters innovation in digital public spaces using models optimized for public interest rather than attention metrics.
Feature
The Allen Lab for Democracy Renovation and Bloomberg Center for Cities brought together civic technologists, researchers, as well as municipal and state leaders across Massachusetts for a workshop on digital civic infrastructure.
Occasional Paper
In a new working paper, Crocodile Tears: Can the Ethical-Moral Intelligence of AI Models Be Trusted?, Allen Lab authors Sarah Hubbard, David Kidd, and Andrei Stupu introduce an ethical-moral intelligence framework for evaluating AI models across dimensions of moral expertise, sensitivity, coherence, and transparency.
Open Access Resource
Allen Lab for Democracy Renovation Senior Fellow Allison Stanger, in collaboration with Jaron Lanier and Audrey Tang, envision a post-Section 230 landscape that fosters innovation in digital public spaces using models optimized for public interest rather than attention metrics.
Feature
The Allen Lab for Democracy Renovation and Bloomberg Center for Cities brought together civic technologists, researchers, as well as municipal and state leaders across Massachusetts for a workshop on digital civic infrastructure.