Algorithmic regulation and rule of law | Mireille Hildebrandt

algorithms | law | papers | Research Notes

In this brief contribution, I distinguish between code-driven and data-driven regulation as novel instantiations of legal regulation. Before moving deeper into data-driven regulation, I explain the difference between law and regulation, and the relevance of such a difference for the rule of law. I discuss artificial legal intelligence (ALI) as a means to enable quantified legal prediction and argumentation mining which are both based on machine learning. This raises the question of whether the implementation of such technologies should count as law or as regulation, and what this means for their further development. Finally, I propose the concept of ‘agonistic machine learning’ as a means to bring data-driven regulation under the rule of law. This entails obligating developers, lawyers and those subject to the decisions of ALI to re-introduce adversarial interrogation at the level of its computational architecture.

Source: Algorithmic regulation and rule of law | Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences

The Crypto Governance Manifesto – Amentum – Medium

algorithms | applications | blockchain | governance | papers | Research Notes

If a miner controls an economy of scale (i.e. PoW hardware manufacturing), they ultimately control the liquidity/velocity flow of the State/Federal level cryptos that are derived from those root chains, given a lack of market competition. Therefore, direct influence over said monopolistic entities are then tightly-coupled to future tokenized cities/states, which means that entire political-monetary interfaces, globally, if adopted and built upon, could be centralizing governance in ways many might not immediately realize — until it’s too late.

Source: The Crypto Governance Manifesto – Amentum – Medium

Architecting the eSociety on Blockchain: A Provocation to Human Nature by Marcella Atzori, Mihaela Ulieru :: SSRN

blockchain | decentralization | governance | papers | Research Notes

The potential opened by distributed ledger technologies for peer-to-peer exchange enabling users and developers to co-own their platforms, organize their own communities and share the value generated according to their own rules has led many to believe in the ‘sharing economy’ as a way to foster cooperation between individuals on large scale, leading to a new, socially pacified post-capitalism era. In spite of any such utopian expectation, however, this paper argues that capitalism has simply strengthened, not only through the growing centralization of peer-to-peer digital services on proprietary platforms, but also through highly speculative practices embedded in decentralized architectural protocols. We tackle the new challenges raised by the engineering of human interactions through algorithmic governance, stressing the necessity to carefully evaluate sharing economy and platform cooperativism as complex phenomena with risks, benefits and unintended consequences inevitably intertwined in the fabric of human existence.

Source: Architecting the eSociety on Blockchain: A Provocation to Human Nature by Marcella Atzori, Mihaela Ulieru :: SSRN

On-Chain Vote Buying and the Rise of Dark DAOs

blockchain | cybercrime | hardware | identity | issues/conflicts | papers | Research Notes | trust

Dark DAO operators can further muddy the waters by launching attacks on choices the vote buyers actually oppose as potential false flag operations or smear campaigns; for example, Bob could run a Dark DAO working in Alice’s favor to delegitimize the outcome of an election Bob believes he is likely to lose.  The activation threshold, payout schedule, full attack strategy, number of users in the system, total amount of money pledged to the system, and more can be kept private or revealed either selectively or globally, making such DAOs ultimately tunable for structured incentive changes.Because the organization exists off-chain, no cartel of block producers or other system participants can detect, censor, or stop the attack.

Source: On-Chain Vote Buying and the Rise of Dark DAOs

Epistemic Harvest: The Electronic Database as Discourse and Means of Data Production | a peer-reviewed journal about_

decentralization | governance | papers | Research Notes

The following discussion of computational capital takes the electronic database, an infrastructure for storing in-formation, as vantage point. Following a brief look into how database systems serve in-formation desires, the notion of ‘database as discourse’ by Mark Poster is explored and further developed. Database as discourse establishes a machinic agency, directed towards the individual in a specific mode of hailing. This mode of hailing in turn leads to a scattered form of subjectivity, that is identified with Manuela Ott and Gerald Raunig as dividual. How does dividualization emerge from database infrastructure? What is the specific quality of data, that is produced by and being harvested from in/dividuals into databases, and what are the consequences of such a shifted view?

Source: Epistemic Harvest: The Electronic Database as Discourse and Means of Data Production | a peer-reviewed journal about_

The Truth About Blockchain

applications | blockchain | papers | Research Notes

The adoption of foundational technologies typically happens in four phases. Each phase is defined by the novelty of the applications and the complexity of the coordination efforts needed to make them workable. Applications low in novelty and complexity gain acceptance first. Applications high in novelty and complexity take decades to evolve but can transform the economy. TCP/IP technology, introduced on ARPAnet in 1972, has already reached the transformation phase, but blockchain applications (in red) are in their early days.

Source: The Truth About Blockchain

Blockchain Economics | Markus K. Brunnermeier

blockchain | economics | papers | people | Research Notes

When is record-keeping better arranged through distributed ledger technology (DLT) than through a traditional centralized intermediary? The ideal qualities of any record-keeping system are (i) correctness, (ii) decentralization, and (iii) cost efficiency. We point out a \textit{Blockchain Trilemma}: no ledger can satisfy all three properties simultaneously. A centralized ledger writer extracts rents due to its monopoly on the ledger. Its franchise value dynamically incentivizes honest reporting. Decentralized ledgers provide static incentives for honesty through computationally expensive Proof-of-Work algorithms but eliminate rents through “fork competition.” Portability of information between “forks” and competition among miners fosters competition among decentralized ledgers that is fiercer than traditional competition. However, fork competition can engender instability and miscoordination. While blockchains can keep track of ownership transfers, enforcement of possession rights is still needed in many blockchain applications.

Source: Blockchain Economics | Markus K. Brunnermeier

Law As Computation in the Era of Artificial Legal Intelligence. Speaking Law to the Power of Statistics by Mireille Hildebrandt :: SSRN

blockchain | justice | law | papers | people | Research Notes

Mireille Hildebrandt

Vrije Universiteit Brussel; Radboud University

Date Written: June 7, 2017


The idea of artificial legal intelligence stems from a previous wave of artificial intelligence, then called jurimetrics. It was based on an algorithmic understanding of law, celebrating logic as the sole ingredient for proper legal argumentation. However, as Holmes noted, the life of the law is experience rather than merely logic. Machine learning, which determines the current wave of artificial intelligence, is built on a data-driven machine experience. The resulting artificial legal intelligence may be far more successful in terms predicting the content of positive law. In this article, I discuss the assumptions of law and the rule of law and confront them with those of computational systems. As a twin paper to my Chorley lecture on Law as Information, this should inform the extent to which artificial legal intelligence provides for responsible innovation in legal decision making.