This paper draws on regulatory governance scholarship to argue that the analytic phenomenon currently known as ‘Big Data’ can be understood as a mode of ‘design-based’ regulation. Although Big Data decision-making technologies can take the form of automated decision-making systems, this paper focuses on algorithmic decision-guidance techniques. By highlighting correlations between data items that would not otherwise be observable, these techniques are being used to shape the informational choice context in which individual decision-making occurs, with the aim of channelling attention and decision-making in directions preferred by the ‘choice architect’. By relying upon the use of ‘nudge’ – a particular form of choice architecture that alters people’s behaviour in a predictable way without forbidding any options or significantly changing their economic incentives, these techniques constitute a ‘soft’ form of design-based control. But, unlike the static Nudges popularised by Thaler and Sunstein [(2008). Nudge. London: Penguin Books] such as placing the salad in front of the lasagne to encourage healthy eating, Big Data analytic nudges are extremely powerful and potent due to their networked, continuously updated, dynamic and pervasive nature (hence ‘hypernudge’). I adopt a liberal, rights-based critique of these techniques, contrasting liberal theoretical accounts with selective insights from science and technology studies (STS) and surveillance studies on the other. I argue that concerns about the legitimacy of these techniques are not satisfactorily resolved through reliance on individual notice and consent, touching upon the troubling implications for democracy and human flourishing if Big Data analytic techniques driven by commercial self-interest continue their onward march unchecked by effective and legitimate constraints.
Innovations in networked digital communications technologies, including the rise of “Big Data,” ubiquitous computing, and cloud storage systems, may be giving rise to a new system of social ordering known as algorithmic regulation. Algorithmic regulation refers to decisionmaking systems that regulate a domain of activity in order to manage risk or alter behavior through continual computational generation of knowledge by systematically collecting data (in real time on a continuous basis) emitted directly from numerous dynamic components pertaining to the regulated environment in order to identify and, if necessary, automatically refine (or prompt refinement of) the system’s operations to attain a pre-specified goal. This study provides a descriptive analysis of algorithmic regulation, classifying these decisionmaking systems as either reactive or pre-emptive, and offers a taxonomy that identifies eight different forms of algorithmic regulation based on their configuration at each of the three stages of the cybernetic process: notably, at the level of standard setting (adaptive vs. fixed behavioral standards), information-gathering and monitoring (historic data vs. predictions based on inferred data), and at the level of sanction and behavioral change (automatic execution vs. recommender systems). It maps the contours of several emerging debates surrounding algorithmic regulation, drawing upon insights from regulatory governance studies, legal critiques, surveillance studies, and critical data studies to highlight various concerns about the legitimacy of algorithmic regulation.
Professor Karen YeungProfessor of LawStart date at Kings: 1/09/2006Contact details:Telephone: +44 (0)20 7848 1550E-mail: email@example.comDepartmentLawsResearch interestsRegulation and governance; the regulatory state, regulatory institutions and instruments, regulating technology, design-based instrumentsLatest Research OutputsThe Forms and Limits of Choice Architecture as a Tool of GovernmentYeung, K. 15 Jul 2016 In : Law and Policy.ArticleHypernudge: Big Data as a mode of regulation by designYeung, K. 22 May 2016 In : Information Communication & Society. 20, 1, p. 118-136ArticlePublic Health Interventions as Regulatory GovernanceYeung, K. 3 May 2016 In : Public Health Ethics. p. 1-2Comment/debate‘Law, Regulation and Technology: the Field, Frame and Focal QuestionsScotford, E. A. K., Brownsword, R. & Yeung, K. 2016 Oxford Handbook of Law, Regulation and Technology. OUPChapter
A challenge held by the US Department of Health and Human Services (HHS) to encourage Blockchain use in the Health Information Technology field resulted in 15 winning whitepapers. The Department’s Office of the National Coordinator for Health Information Technology (ONC) first announced the “Use of Blockchain in Health IT and Health-Related Research” challenge in July.More than 70 submissions were received by ONC, “addressing ways that Blockchain technology might be used in health and health IT to protect, manage, and exchange electronic health information,” the Department revealed.
“Blockchain technology is going to revolutionize healthcare and the method in which every patient interacts.”That prediction, from technology consultant Peter Nichol in 2015, is far from being fully realized, but blockchain is gaining momentum among health IT thought leaders as a way to increase data security and interoperability while reducing costs.In finance, blockchain technology is best-known as the foundation for the digital currency, BitCoin. In healthcare, organizations like Deloitte, the Mayo Clinic and even Google have identified a growing number of use cases for blockchain as a means for more efficient and transparent data exchanges.
This short essay reflects on some of the potential implications of automated enforcement via distributed ledger systems (including blockchain) to ensure the security of transactions for ‘freedom under law’ and the social foundations upon which the rule of law in modern legal orders is grounded.Keywords: blockchain, distributed ledgers, rule of law, individual liberty, automation, law enforcement, governanceJEL Classification: K20, K40, K42Suggested Citation:Yeung, Karen, Block
People keep repeating the phrase “Code is Law” without clear understanding of what it’s supposed to mean. Some deliberately misinterpret it to mean that “ETC supports thieves and crooks” and similar nonsense. Let’s get some things straight. Code is law on the blockchain. In the sense, all executions and transactions are final and immutable. So, from our (Ethereum Classic supporters) standpoint by pushing the DAO hard fork EF broke the “law” in the sense that they imposed an invalid transaction state on the blockchain.This has nothing to do with contractual or criminal law, or other legal considerations. Stating that “code is law” is similar to acknowledging the laws of physics. The law of gravity says that when I push a piano out of a window, the piano will fall downwards. It does not mean that it’s necessarily “legal” for me to push that piano out of that window. And if I do so and the falling piano kills some passer-by, it would be insane for me to argue before the judge that I shouldn’t go to jail because I broke no laws of physics.On Ethereum blockchain, a Turing complete code operates with a very real and tangible value. Because of this, there is always a potential for mistakes and unintended outcomes. There will always be transactions and code execution results that someone is not happy about. There will be conflicts and disagreements, there will be code vulnerabilities and exploits, there will be scams and thefts, there will be all kinds of ugly things.Who should deal with all these conflicts? Let’s imagine for a moment that we decided ‘the blockchain community’ will take it upon itself to deal with it all.Who is going to make a call which on-chain code execution is “theft,” and which is not? Is this ponzi contract scammy enough to shut it down? Do we tolerate this dark market while it sells fake ids and marijuana, but draw the line once it starts to dabble in child porn and cocaine?Should there be a democratic voting system (moot court) to decide on these cases, changing the blockchain state based on such decisions? Should there be a committee that decides what smart contract behavior is ‘unacceptable’ and what transactions are ‘illegal’ enough to justify a hard fork?What may serve as a basis for such decisions? Where is the applicable body of law? Who is going to be the police, the judge and the jury? What is a due process? What is the appeal procedure? A lot of questions, and no good answers to these questions, when it comes to “blockchain justice”.But it’s even worse if there is no system at all. If ‘the blockchain community’ just makes a special exception in regards to a ‘special case’, choosing to administer justice ‘just this one time’. What is so special about this case, one may ask? Why does this theft get a special treatment, and the other thefts don’t? Who do you need to know, whose buddy do you need to be to get such exceptional treatment? How are you going to defend such preferential treatment against legal cases citing a precedent and subpoenas demanding reversal of specific transactions?It’s this whole snake’s nest that could be avoided by refusing to be dragged into conflict resolution and quest for justice as related to smart contract execution. And it only requires sticking to principles of blockchain neutrality and immutability.So, code is law on the blockchain. All executions are final, all transactions are immutable. For everything else, there is a time-tested way to adjudicate legal disputes and carry out the administration of justice. It’s called legal system.
UCL Roberts Building, Malet Place, London WC1Organised by the UCL Centre for Law, Economics and Society with the support of the Modern Law Review and UCL Public EngagementThe workshop deals with emergent economic, political and legal phenomena in the field of FinTech. It pursues two distinct goals. First, it intends to generate awareness and facilitate a better understanding of the actors, phenomena and dynamics of the new financial order. Second, it explores the political and legal implications of financial and technological innovation based on blockchain technology. These debates will constitute the basis of an edited volume that introduces practitioners and researchers to the regulatory and political challenges of blockchain technologies and its diverse uses.The Speakers include:Tomaso Aste (UCL)Iris Chiu (UCL)Georgios Dimitropoulos (Hamad Bin Khalifa University Law School)Stefan Eich (Princeton Society of Fellows)Hermann Elendner (Humboldt University of Berlin)Jonathan Greenacre (Oxford University)Rohan Grey (Modern Money Network)Philipp Hacker (EUI)Michael Jacobides (London Business School and NY Fed)Rosa María Lastra (Queen Mary University of London)Ioannis Lianos (UCL)Pietro Ortolani (Max Planck Institute Luxembourg)Giovanni Sartor (European University Institute)Alexandros Seretakis (University of Luxembourg)Paolo Tasca (UCL)Angela Walch (St. Mary’s University School of Law)Aaron J. Wright (Cardozo School of Law)Karen Yeung (King’s College London)Claus D. Zimmermann (Sidley Austin LLP)
Bitcoin ObituariesBitcoin has died 166 timesObituary Stats | Submit Obituary | Obituary Generator
Cryptocurrencies are portrayed as a more anonymous and less traceable method of payment than credit cards. So if you shop online and pay with Bitcoin or another cryptocurrency, how much privacy do you have? In a new paper, we show just how little.Websites including shopping sites typically have dozens of third-party trackers per site. These third parties track sensitive details of payment flows, such as the items you add to your shopping cart, and their prices, regardless of how you choose to pay. Crucially, we find that many shopping sites leak enough information about your purchase to trackers that they can link it uniquely to the payment transaction on the blockchain. From there, there are well-known ways to further link that transaction to the rest of your Bitcoin wallet addresses. You can protect yourself by using browser extensions such as Adblock Plus and uBlock Origin, and by using Bitcoin anonymity techniques like CoinJoin. These measures help, but we find that linkages are still possible.