This report zooms in on the potential of blockchain to transform scholarly communication and research in general.By describing important initiatives in this field, it highlights how blockchain can touch many critical aspects of scholarly communication, including transparency, trust, reproducibility and credit. Moreover, blockchain could change the role of publishers in the future, and it could have an important role in research beyond scholarly communication.The report shows that blockchain technology has the potential to solve some of the most prominent issues currently facing scholarly communication, such as those around costs, openness, and universal accessibility to scientific information.
Source: Blockchain for Research
A new study of the global open-source platform, GitHub, offers key lessons on blockchain development—how projects have grown, what’s likely to come next, and the implications for financial services firms.
Source: The evolution of blockchain technology | Deloitte Insights
While much has already been written about blockchain applications and prospects in the FinTech industry, little research has been done to explore blockchain technology’s user-centric paradigm in enabling various applications beyond banking. This article is an effort to contribute to that body of scholarship by exploring blockchain technology’s potential applications, and their limits, in areas that intersect with social impact, including human rights. This article explores whether blockchain technology and its core operational principles – such as decentralisation, transparency, equality and accountability – could play a role in limiting undue online surveillance, censorship and human rights abuses that are facilitated by the increasing reliance on a few entities that control access to information online. By doing so, this article aims at initiating a scholarly curiosity to understand what is possible and what is to be concerned about when it comes to the potential impact of blockchain technology on society.
Source: Blockchain technology for social impact: opportunities and challenges ahead: Journal of Cyber Policy: Vol 0, No 0
The meteoric rise of Bitcoin has led to heightened investment, academic, commercial, numismatic, transactional, and practitioner interest in that cryptocurrency, as well as in the growing array of such instruments worldwide. This leads to an accentuated need for an examination of the historical evolution of Bitcoin as the seminal instrument in the development of cryptocurrencies, and this discussion paper seeks to address that gap.
Source: A History of Bitcoin by Usman W. Chohan :: SSRN
Experiments in Algorithmic GovernanceThe following is an excerpt of an academic article [PDF] I wrote detailing why The DAO failed, and why other DAOs and blockchain technologies might also fail. In a nutshell, lack of an appropriate governance structure and plan, and insufficient recognition of the challenges of building new social models doomed The DAO. When building new blockchain platforms, one ought to plan for these eventualities.
Source: Why The DAO failed (and others might too) — Steemit
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.
Source: ‘Hypernudge’: Big Data as a mode of regulation by design: Information, Communication & Society: Vol 20, No 1
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.
Source: Algorithmic regulation: A critical interrogation – Yeung – 2017 – Regulation & Governance – Wiley Online Library
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.
Source: 15 blockchain whitepapers awarded winners of US Department of Health and Human Services Challenge » Brave New Coin
“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.
Source: Blockchain for Healthcare: A Recommended Reading List