Existing consensus systems are designed with implicit majoritarian assumptions. The commonly used term in consensus literature for a small group with dissenting opinions is adversary. This is particularly problematic when viewed through the lens of recent proposals to move governance structures to, for instance, blockchain-based systems which have majoritarian assumptions built into their design and operation.

There are some protections provided in social, political, and commercial governance structures for those with dissenting opinions via a system of minority rights, protected freedoms, and other checks and balances. If we are to design computational systems that meet the requirements of real-world institutions, we need to ensure that we preserve or improve upon the protections offered in existing systems. Majoritarian consensus gets in the way of achieving this goal: in their ideal instantiation, a set of nodes (the majority) have all the decision-making power while the remaining nodes have no ability to cause those decision to be renegotiated. This fundamental problem is further exacerbated in other computational systems (e.g. centralised systems), where the issue is often obfuscated by wrapping the computational system in layers of rough human consensus.

Existing institutional protections are far from perfect, highlighting the difficulty of the problem, but this reveals more acutely the current lack of research into this area on the computational side. This workshop aims to raise awareness of this issue and seeks answers to some fundamental questions about computational governance when viewed through this lens. What can technologists learn from other systems of governance? What advances in computer science would be required for computational systems to be useful in important affairs like human governance? Conversely, are there technologies that policy makers can use to improve existing systems? The answers to these questions lie at the intersection of fundamental computer science, policy making, jurisprudence and human rights. We invite submissions on the theme of Challenging Majoritarian Assumptions in Computational Governance from all these domains.

We expect to have 8-10 papers presented with each proposal going through single blind review. Position papers must be 5-10 pages in length and should be mailed to: mansoor AT openorigins.com . Alternatively, participants can also submit a single page extended abstract; however, please note that for inclusion into Data & Policy, extended abstracts would need to be converted into full papers and go through an additional round of peer review.

A special issue in Data & Policy - a peer-reviewed, open access journal published by Cambridge University Press - has been launched in tandem with this workshop. Selected authors will be invited to submit full papers to the journal.

Full CFP here: https://www.cambridge.org/core/journals/data-and-policy/information/call-for-papers-computational-governance-and-majoritarianism

Computational Governance & Majoritarianism (CoGMa) Workshop