# Submission to the Strategic Examination of R&D discussion paper

With Darcy W.E. Allen, Aaron M. Lane, and Jason Potts1

Dear expert panel,

We are a group of academic economists and legal scholars with a specialisation in innovation and the development and adoption of frontier technology. The Strategic Examination of Research and Development discussion paper underlines that Australia’s innovation system is one of underperformance and malinvestment.

This is not the first inquiry to investigate and underline Australia’s innovation system underperformance. Each has found the same deficiencies in the system that the Expert Panel seeks to understand:

  • In 1995 the Industry Commission found a need to “raise the social and economic payoff from public sector R\&D by achieving a wider external influence over what research gets done” and increase cost effectiveness (Industry Commission 1995)
  • In 2007 the Productivity Commission found that there were “major improvements” needed across the board and that research commercialisation was fraught with misaligned incentives and bureaucratic barriers (Productivity Commission 2007)
  • The Cutler Review found “shortcomings in the institutional framework that underpins the innovation system” (Cutler 2008).
  • In 2015 the Commonwealth Senate Economics References Committee inquiry into Australia’s Innovation System found that “Australia performs well in research”, but “such innovation is not developed into tangible wealth creation” (Senate Economics References Committee 2015).
  • In 2016 Joint Select Committee on Trade and Investment Growth Inquiry into Australia’s Future in Research and Innovation also underlined Australia’s underperformance in converting research into market ready innovation (Joint Select Committee on Trade and Investment Growth 2016)

It will be tempting for the expert panel to travel down the same paths as its predecessors. Australia’s innovation system consists of a large network of publicly funded organisations that rely on grants and subsidies as their base revenue model.

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Institutional acceleration

With Darcy W.E. Allen and Jason Potts. Forthcoming at Cambridge University Press.

This Element develops a theory of institutional acceleration to explain the transformation to a digital economy through a cluster of frontier technologies: artificial intelligence, blockchain, quantum computing, cryptography, and low-earth orbit infrastructure. Unlike previous technological revolutions, these technologies transform not how we organise things, but how we coordinate economic activity. The authors’ supertransition thesis explains why these digital technologies shouldn’t be understood in isolation, but rather should be understood in how they combine to create new institutional possibilities, leading to more open, complex, and global economic systems. Drawing on evolutionary economics and institutional theory, this Element shows how this evolutionary process is reshaping our institutional economic architecture. Ultimately, institutional acceleration drives greater computation and knowledge into our economic systems.

(Will be) available here

Dynamic Competition and Digital Platforms: Submission to the Australian Treasury Consultation on a New Digital Competition Regime

With Darcy W. E. Allen, Dirk Auer, Aaron M. Lane, Geoffrey A. Manne, Jason Potts, Lazar Radic

Executive Summary: The Australian Treasury’s proposed competition regime for digital platforms is flawed and should not proceed.

The policy rationale for an ex ante regime is unjustified. The Competition and Consumer Act 2010 (CCA) already provides a comprehensive framework to address concerns such as market power, unfair contract terms, and self-preferencing. The Australian Competition and Consumer Commission (ACCC) has not demonstrated any compelling reason existing competition laws are insufficient to regulate digital platforms and has not sought to enforce them against digital platforms.

The proposed regime is based on a misunderstanding of competition in the digital economy. Digital markets are characterised by dynamic competition, where innovation and technological change are the primary drivers of consumer welfare. The proposed ex ante regime, with its focus on static competition, may dampen innovation incentives and create barriers to technology diffusion, harming Australian consumers and businesses in the long run. Competition policy for digital platforms should be based on a dynamic competition approach that fosters innovation.

The proposed regulatory mechanisms are problematic. The reliance on subordinate legislation for crucial policy decisions is inappropriate, reducing parliamentary oversight. This approach lacks transparency and accountability, and may lead to unintended consequences for the digital economy.

We urge the Australian Treasury to reconsider its approach to regulating digital platforms. Instead of imposing an ex ante regime, the focus should be on enforcing existing competition laws and fostering a dynamic environment of innovation. This approach would better serve Australia’s long-term economic interests and the continued growth of the digital sector.

Available in PDF here.

DAOs are adaptive governance engines

With Darcy WE Allen, Aaron M Lane, and Jason Potts. Available at SSRN.

Abstract: We develop a new theory of Decentralised Autonomous Organisations (DAOs) that explains why they exist in terms of what they do. In New Institutional Economics, firms exist because they minimise the transaction costs of using a market. DAOs, which are a species of firm but made of smart contracts, would prima facie seem to extend this logic to further economise on lower transaction costs. Our argument here is that this is almost correct, but misses a critical factor that becomes readily apparent when you actually observe how DAOs behave in the wild, which we do by studying three DAOs-Shapeshift, Uniswap, and Optimism. Our theory is that the value of a DAO largely accrues to the dynamic adaptation in governance that the institutional form affords. DAOs enable low cost and fast change in governance structures in order to adapt to dynamic regulatory, competitive, and financial environments. A DAO is therefore not just a type of automation to distribute and minimise agency costs through token-governed smart contracts, as simple transaction cost theory explains. Rather, a DAO is a mechanism for cheap and fast variation in governance to enable an organisation to adapt to a complex dynamic economic environment. When the benefits of this mechanism exceed the costs we predict the existence of a DAO.

Common knowledge theory of stablecoins

With Chloe White and Jason Potts. Available at SSRN.

Abstract: We propose a new theory of stablecoins based on common knowledge. We contrast this with the ‘better money’ theory of stablecoins, which emphasises marginal improvements over the standard origin of money theory as: medium of exchange, unit of account, store of value.

Managing Generative AI in Firms: The Theory of Shadow User Innovation

With Julian Waters-Lynch, Darcy WE Allen, and Jason Potts. Available at SSRN.

Abstract: This paper explores the management challenge posed by pervasive and unsupervised use of generative AI (GenAI) applications in firms. Employees are covertly experimenting with these tools to discover and capture value from their use, without the express direction or visibility of organisational leaders or managers. We call this phenomenon shadow user innovation. Our analysis integrates literature on user innovation, general purpose technologies and the evolution of firm capabilities. We define shadow user innovation as employee-led user innovation inside firms that is opaque to management. We explain how this opacity obstructs a firm’s ability to translate the use of GenAI into visible improvements in productivity and profitability, because employees can currently privately capture these benefits. We discuss potential management responses to this challenge, outline a research program, and offer practical guidance for managers.

Institutions to constrain chaotic robots: why generative AI needs blockchain

With Sinclair Davidson and Jason Potts. Available at SSRN

Abstract: Generative AI is a very powerful new computing technology, but the problem of how to make it economically useful (Alice: “hello LLM, please send an email to Bob”) is limited by its inherent unpredictability. It might send the email, but it might do something else too. As a consequence, the large language models that underpin generative AI are not safe to use for most economically useful and valuable interactions with the world. This is the ‘economic alignment’ problem between the AI as an ‘agent’ and the human ‘principal’ who wants the LLM to interact in the world on their behalf. The answer we propose is smart contracts that can take LLM outputs and filter them as deterministic constraints. With smart contracts, LLMs can interact safely in the real world, and can unlock the vast economic opportunity of economically aligned and artificially intelligent agents.

The exchange theory of web3 governance

With Jason Potts, Darcy W E Allen, Aaron M. Lane and Trent MacDonald. Published in Kyklos,  June 2023. Working paper available on SSRN

Abstract: Blockchains have enabled innovation in distributed economic institutions, such as money (e.g., cryptocurrencies) and markets (e.g., decentralised exchanges), but also innovations in distributed governance, such as decentralised autonomous organisations. These innovations have generated academic interest in studying web3 governance, but as yet there is no general theory of web3 governance. In this paper, we draw on the contrast between a ‘romantic view’ of governance (characterised by consensus through community voting) and the ‘exchange view’ of governance from public choice theory (characterised by an entrepreneurial process of bargaining and exchange of voters under uncertainty). Our analysis is the first to argue that the latter ‘exchange view’ of governance is best to understand the dynamics of governance innovation in web3, providing the foundations for a new general theory of governance in this frontier field. We apply the ‘exchange view’ of governance to three case studies (Curve, Lido and Metagov), exploring how these projects enable pseudonymous, composable and permissionless governance processes to reveal value. Our approach helps illuminate how this emergent polycentric governance process can generate robustness in decentralised systems.

Large language models reduce agency costs


With Jason Potts, Darcy W E Allen, and Nataliya Ilyushina. Available on SSRN.

Large Language Models (LLMs) or generative AI have emerged as a new general-purpose technology in applied machine learning. These models are increasingly employed within firms to support a range of economic tasks. This paper investigates the economic value generated by the adoption and use of LLMs, which often occurs on an experimental basis, through two main channels. The first channel, already explored in the literature (e.g. Eloundou et al. 2023, Noy and Wang 2023), involves LLMs providing productive support akin to other capital investments or tools. The second, less examined channel concerns the reduction or elimination of agency costs in economic organisation due to the enhanced ability of economic actors to insource more tasks. This is particularly relevant for tasks that previously required contracting within or outside a firm. With LLMs enabling workers to perform tasks in which they had less specialisation, the costs associated with managing relationships and contracts decrease. This paper focuses on this second path of value creation through adoption of this innovative new general purpose technology. Furthermore, we examine the wider implications of the lower agency costs pathway on innovation, entrepreneurship and competition.