Decentralised Governance: Hayek Amongst the Machines
Jason Potts Blockchain Innovation Hub, RMIT University, Melbourne, Australia
Bill Tulloh, Agoric, San Francisco, US
Chris Berg Blockchain Innovation Hub, RMIT University, Melbourne, Australia
Blockchain first emerged as the technology behind bitcoin, a cryptocurrency (Nakamoto 2008) or decentralised (peer-to-peer) private money (Hayek 1976). Yet while blockchain began as a financial technology, it has rapidly evolved into a much broader institutional technology (Davidson et al 2018) for decentralised economic governance, with adaptations including self-sovereign identity, smart contracts, oracles and wallets, decentralised autonomous organisations (DAOs), decentralised exchanges, and multichain interoperability. Blockchain is a new institutional technology that uses decentralised protocols to coordinate economic activity by lowering the cost of trust associated with shared data, exchange, and contracting (Berg et al 2017a, Arruñada and Garicano 2018, Catalini and Gans 2018). The study of blockchains as a governance technology to substitute and complement other coordinating economic institutions such as firms, markets and governments is called institutional cryptoeconomics (Berg et al 2017b, 2019).
However, as scholars have come to better understand distributed ledger technology  as an institutional technology, a surprising insight has emerged: DLT systems can coordinate and govern decentralised human economies (as governments, firms and markets also do), but blockchains and smart contracts can also coordinate and govern distributed machine economies (or human-and-machine economies). This extends the domain of catallaxy (i.e. the emergence of private orderings from distributed agents, Hayek 1978: 108-9) from market-coordination of human action to blockchain-coordination of human-to-machine and machine-machine economies.
The purpose of this special issue is to explore this new blockchain-enabled domain of decentralised governance that extends from market economies of people, organisations and knowledge through to machine economies of software agents and subroutines. Miller and Tulloh (2016) have proposed calling a unified science of the governance of the economic coordination of agents, whether humans or machines – ‘decision alignment’. Alternatively, if microeconomics studies market coordination of human economic agents, then nanoeconomics is the study of the market coordination of software agents. Nanoeconomics represents the next generation of secure computer architectures within a broader human-machine choice coordination context of ‘decision alignment’. Nanoeconomics is the study of an economy of software agents, using market institutions and property rights to order computation and bid for computational resources. It is the study of choices and market exchange that occur between computational objects in object-oriented software architectures, and which are economically coordinated through blockchain infrastructure.
Knowledge problems (Hayek 1945) affect both human and machine economies. However, they have only been widely diagnosed in human economies through microeconomic analysis of how market mechanisms process distributed knowledge and efficiently coordinate decentralised economic agents (Mises 1949). But the same problem exists in modern computer architectures based on stored-program architectures with computation scheduled through central processing units (Miller and Drexler 1988a, 1988b). These machines are fundamentally analogous to centrally-planned economies in how they hierarchically process information (Miller and Drexler 1988c). A key problem with ‘centrally-planned’ computation are the implications for computer security (Miller et al 2004). A decentralised software economy would instead seek to operationalise tradable property rights for access to subroutines through the principle of least authority (Miller et al 2013).
DLT provides economic infrastructure of property rights and peer-to-peer exchange that can facilitate decentralised interactions for both human and software agents. As more and more of the economy becomes machine-mediated, we need to worry about the security and efficiency implications of centrally-planned machine economies. But the underlying knowledge problems are general (Lachmann 1994, Lavoie 1995). Blockchains are constitutional protocols for catallactic ordering that can not only facilitate improved decentralised economic coordination for humans, but also for machines.
This special issue will consider papers on broad themes of:
- New Institutional technologies of private orders, evolution of governance technologies, Decentralised governance
- Hayekian scholarship of blockchain
- Decentralised institutional and constitutional orders
- Decision alignment, Nanoeconomics, and software economies
- Institutional Cryptoeconomics
- Blockchain as a catallaxy, Operating systems as catallaxy, Constitutional catallaxy
- Bayesian decision-making (AI) combined with decentralised coordination (Blockchain)
- Blockchain for collective action, public choice, and crypto-democracy
 “A DLT system is a system of electronic records that enables a network of independent participants to establish a consensus around the authoritative ordering of cryptographically validated (“signed”) transactions. These records are made persistent by replicating the data across multiple nodes, and tamper-evident by linking them by cryptographic hashes. The shared result of the reconciliation/consensus process – the ‘ledger’ – serves as the authoritative version for these records.” (Rauch et al 2018: p. 24)
Key Dates and Paper Submission Procedure
Please submit papers to email@example.com or Christopher.firstname.lastname@example.org with subject header “C+T Hayek among the machines” by June 12, 2019.
Papers ideally should be less than 4,000 words, but consideration for longer papers also given. Papers selected will be peer-reviewed and published in Cosmos + Taxis in 2020.
Arruñada, B. Garicano, L. 2018. Blockchain: The birth of decentralised governance. Working Paper 1608, https://econ-papers.upf.edu/papers/1608.pdf
Berg, C., Davidson, S., Potts J., 2017a. Blockchains industrialise trust. SSRN https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3074070
Berg, C., Davidson, S., Potts, J. 2017b. How to understand the blockchain economy: Introducing institutional cryptoeconomics. https://medium.com/cryptoeconomics-australia/the-blockchain-economy-a-beginners-guide-to-institutional-cryptoeconomics-64bf2f2beec4
Berg, C., Davidson, S., Potts, J. 2019. Institutional Cryptoeconomics. Edward Elgar: Cheltenham.
Berg, C., Davidson, S., Potts, J. 2018. Ledgers. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3157421
Catalini, C., Gans, J. 2018. Some simple economics of the blockchain. NBER Working Paper Series No. 22952, National Bureau of Economic Research, Cambridge, MA.
Davidson, S., de Filippi, P., Potts, J. 2018. Blockchain and the institutions of capitalism. Journal of Institutional Economics.
Hayek, F. A. 1945. Use of knowledge in society. American Economic Review 36(4): 512-36.
___________. 1976. The Denationalisation of Money. Institute of Economic Affairs. London.
___________. 1978. Law, Legislation and Liberty, Vol. II.
Lachmann, L. 1994. Expectations and the Meaning of Institutions. Edited by Don Lavoie London: Routledge.
Lavoie, D. 1995. The market as a procedure for the discovery and conveyance of inarticulate knowledge. Advances in Austrian Economics 13: 115–137.
Miller, M., Drexler, K. E. 1988a. Markets and computation: agoric open systems. The Ecology of Computation, B. Huberman (ed.) Elsevier Science Publishers/North-Holland.
_____________.1988b. Incentive engineering for computational resource management. The Ecology of Computation, B. Huberman (ed.) Elsevier Science Publishers/North-Holland.
_____________. 1988c. Comparative ecology: A computational perspective. The Ecology of Computation, B. Huberman (ed.) Elsevier Science Publishers/North-Holland.
Miller, M., Tulloh, B., Shapiro, J. 2004. The structure of authority: Why security is not a separable concern. http://www.erights.org/talks/no-sep/secnotsep.pdf
Miller, M., Tulloh B. 2016. The Elements of Decision Alignment’ Proceedings of ECOOP 2016, The European Conference on Object-Oriented Programming.
Mises, L. 1949. Human Action. New Haven: Yale University Press.
Nakamoto, S. 2008. Bitcoin: a peer-to-peer electronic cash system. https://bitcoin.org/bitcoin.pdf
Rauch, M. et al 2018. Distributed Ledger Technology Systems: A conceptual framework. Cambridge Centre for Alternative Finance: Judge Business School. https://www.jbs.cam.ac.uk/fileadmin/user_upload/research/centres/alternative-finance/downloads/2018-10-26-conceptualising-dlt-systems.pdf