687 research outputs found

    Beyond oracles – a critical look at real-world blockchains

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    This thesis intends to provide answers to the following questions: 1) What is the oracle problem, and how do the limitations of oracles affect different real-world applications? 2) What are the characteristics of the portion of the literature that leaves the oracle problem unaddressed? 3) Who are the main contributors to solving the oracle problem, and which issues are they focusing on? 4) How can the oracle problem be overcome in real-world applications? The first chapter aims to answer the first question through a literature review of the most current papers published in the field, bringing clarity to the blockchain oracle problem by discussing its effects in some of the most promising real-world blockchain applications. Thus, the chapter investigates the sectors of Intellectual Property Rights (IPRs), healthcare, supply chains, academic records, resource management, and law. By comparing the different applications, the review reveals that heterogeneous issues arise depending on the sector. The analysis supports the view that the more trusted a system is, the less the oracle problem has an impact. The second chapter presents the results of a systematic review intended to highlight the state-of-the-art of real-world blockchain applications using the oracle problem as a lens of analysis. Academic papers proposing real-world blockchain applications were reviewed to see if the authors considered the oracle’s role in the applications and related issues. The results found that almost 90% of the inspected literature neglected the role of oracles, thereby proposing incomplete or irreproducible projects. Through a bibliometric analysis, the third chapter sheds light on the institutions and authors that are actively contributing to the literature on oracles and promoting progress and cooperation. The study shows that, although there is still a lack of collaboration worldwide, there are dedicated authors and institutions working toward a similar and beneficial cause. The results also make it clear that most areas of oracle research are poorly addressed, with some remaining untouched. The fourth and last chapter focuses on a case study of a dairy company operating in the northeast region of Italy. The company applied blockchain technology to support the traceability of their products worldwide, and the study investigated the benefits of their innovation from the point of view of sustainability. The study also considers the role of oracle management, as it is a critical aspect of a blockchain-based project. Thus, the relationship between the company, the blockchain oracle, and the supervising authority is discussed, offering insight into how sustainable innovations can positively impact supply chain management. This work as a whole aims to shed light on blockchain oracles as an academic area of research, explaining why the study of oracles should be considered the backbone of blockchain literature development

    The Data Trust Solution to Data Sharing Problems

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    A small number of large companies hold most of the world’s data. Once in the hands of these companies, data subjects have little control over the use and sharing of their data. Additionally, this data is not generally available to small and medium enterprises or organizations who seek to use it for social good. A number of solutions have been proposed to limit Big Tech “power,” including antitrust actions and stricter privacy laws, but these measures are not likely to address both the oversharing and under-sharing of personal data. Although the data trust concept is being actively explored in the United Kingdom, European Union, and Canada, this is the first Article to take an in-depth look at the viability of data trusts from a US perspective. A data trust is a governance device that places an independent fiduciary intermediary between Big Tech and human data subjects. This Article explores how data trusts might be configured as bundles of contracts in the information supply chain. In addition to their benefits for the social good, data trusts might contribute to relieve some of the tension between EU and US privacy practices

    Owning the Sharing Economy - Comparing the business models of platform cooperatives and investor owned sharing economy platforms

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    In the past decade, the collaborative economy has received a lot of attention in media and research. Originally the collaborative economy was expected to change the ways we consume and bring significant social and environmental benefits. In recent years the collaborative economy has, however, also received a lot of criticism especially in terms of worker rights and the ways in which value is distributed within the sector. One possible solution to this could be platform cooperatives, that is, sharing economy platforms that are owned by its customers, workers or other stakeholders. The premise of platform cooperatives is that if workers or customers are the owners of the platform, their rights are better protected and that the profits would be distributed straight to those that are in a key role in creating value. There is very little research done on platform cooperatives, and this thesis aims to contribute to that research gap. The main focus of this thesis is to look at the differences and similarities in business models between platform cooperatives and investor owned sharing economy platforms. Another objective of this thesis is also to look at how the business model canvas as a tool should take into account the alternative starting point and way of organizing economic activity of platform cooperatives. The framework of this research is the business model canvas by Osterwalder and Pigneur (2010). The business model canvas is a widely used tool in mapping out what value the company is generating and for who as well as what kind of resources, activities and partners it is using to deliver that value. The method used for this study is multiple case study. Four platform cooperatives were selected from the most common types of platform cooperatives along with four investor owned counterparts that had a similar offering. The main differences emerged in the value proposition, customer relationships and key partners while the companies resembled each other in terms of channels, key activities and key resources. In addition, an adapted business model canvas is derived that takes better into account the different starting point of doing business of platform cooperatives. Viimeisen vuosikymmenen aikana jakamistalous on saanut paljon mediahuomiota ja sitä on tutkittu paljon. Jakamistalouden ensimmäisten vuosien aikana odotettiin, että jakamistalouden rakenteet muuttaisivat taloutta merkittävästi ja toisivat mukanaan huomattavia sosiaalisia ja ympäristöhyötyjä. Viime vuosien aikana jakamistalous on kuitenkin saanut paljon kritiikkiä osakseen, erityisesti liittyen työntekijöiden oikeuksiin ja siihen, kuinka voitot jakautuvat sektorin osallistujien kesken. Yksi ehdotetuista ratkaisuista jakamistalouden haasteisiin ovat alustaosuuskunnat, jotka ovat jakamistalouden alla toimivia alustoja, joiden omistajia ovat työntekijät, asiakkaat tai muut sidosryhmät. Alustaosuuskuntien toimivuuden idea perustuu oletukseen, että jos työntekijät tai asiakkaat omistavat alustan, heidän oikeutensa ovat paremmin suojeltuja ja voitot jakaantuisivat suoraan heille, jotka ovat keskeisessä roolissa arvonluonnissa. Alustaosuuskuntia on tutkittu todella vähän, ja tämän pro gradu tutkielman tarkoitus on kuroa tätä kuilua umpeen. Tämän tutkielman päätarkoitus on selvittää, mitkä ovat keskeiset erot ja samankaltaisuudet liikentoimintamalleissa alustaosuuskuntien ja osakeyhtiöpohjaisten jakamistalouden alustojen välillä. Toinen tavoite on tutkia, kuinka liiketoimintallien konseptualisointityökalun kannattaisi ottaa osuuskuntien lähtökohdat ja tavoitteet paremmin huomioon. Tässä tutkimuksessa käytetty viitekehys on Osterwalderin ja Pigneur’in (2010) liiketoimintamallikangas. Tämä työkalu on laajasti käytetty tunnistamaan minkälaista arvoa yritys luo, kenelle sekä mitä resursseja, aktiviteetteja ja partnereita on käytetty arvontuottamisesssa. Pro gradu-tutkielman metodi on monitapaustutkimus. Neljä alustaosuuskuntaa valittiin niiltä sektoreilta, joilla alustaosuuskuntia on eniten. Näitä vertaillaan neljään osakeyhtiöpohjaiseen jakamistalouden alustoihin, joilla on samankaltainen tarjoama valittuihin alustaosuuskuntiin verrattuna. Suurimmat erot ilmenivät arvopropositiossa, asiakassuhteissa ja partnereissa, kun taas samankaltaisuuksia löytyi käytettyjen kanavien, aktiviteettien ja resurssien osalta. Lisäksi tuloksissa määritellään sovellettu liiketoimintamallikangas, joka ottaa paremmin huomioon alustaosuuskuntien eri lähtökohdat liiketoiminnalle

    The Digitalisation of African Agriculture Report 2018-2019

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    An inclusive, digitally-enabled agricultural transformation could help achieve meaningful livelihood improvements for Africa’s smallholder farmers and pastoralists. It could drive greater engagement in agriculture from women and youth and create employment opportunities along the value chain. At CTA we staked a claim on this power of digitalisation to more systematically transform agriculture early on. Digitalisation, focusing on not individual ICTs but the application of these technologies to entire value chains, is a theme that cuts across all of our work. In youth entrepreneurship, we are fostering a new breed of young ICT ‘agripreneurs’. In climate-smart agriculture multiple projects provide information that can help towards building resilience for smallholder farmers. And in women empowerment we are supporting digital platforms to drive greater inclusion for women entrepreneurs in agricultural value chains

    FinBook: literary content as digital commodity

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    This short essay explains the significance of the FinBook intervention, and invites the reader to participate. We have associated each chapter within this book with a financial robot (FinBot), and created a market whereby book content will be traded with financial securities. As human labour increasingly consists of unstable and uncertain work practices and as algorithms replace people on the virtual trading floors of the worlds markets, we see members of society taking advantage of FinBots to invest and make extra funds. Bots of all kinds are making financial decisions for us, searching online on our behalf to help us invest, to consume products and services. Our contribution to this compilation is to turn the collection of chapters in this book into a dynamic investment portfolio, and thereby play out what might happen to the process of buying and consuming literature in the not-so-distant future. By attaching identities (through QR codes) to each chapter, we create a market in which the chapter can ‘perform’. Our FinBots will trade based on features extracted from the authors’ words in this book: the political, ethical and cultural values embedded in the work, and the extent to which the FinBots share authors’ concerns; and the performance of chapters amongst those human and non-human actors that make up the market, and readership. In short, the FinBook model turns our work and the work of our co-authors into an investment portfolio, mediated by the market and the attention of readers. By creating a digital economy specifically around the content of online texts, our chapter and the FinBook platform aims to challenge the reader to consider how their personal values align them with individual articles, and how these become contested as they perform different value judgements about the financial performance of each chapter and the book as a whole. At the same time, by introducing ‘autonomous’ trading bots, we also explore the different ‘network’ affordances that differ between paper based books that’s scarcity is developed through analogue form, and digital forms of books whose uniqueness is reached through encryption. We thereby speak to wider questions about the conditions of an aggressive market in which algorithms subject cultural and intellectual items – books – to economic parameters, and the increasing ubiquity of data bots as actors in our social, political, economic and cultural lives. We understand that our marketization of literature may be an uncomfortable juxtaposition against the conventionally-imagined way a book is created, enjoyed and shared: it is intended to be

    Big Data and Artificial Intelligence in Digital Finance

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    This open access book presents how cutting-edge digital technologies like Big Data, Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector. The book illustrates how recent advances in these technologies facilitate banks, FinTech, and financial institutions to collect, process, analyze, and fully leverage the very large amounts of data that are nowadays produced and exchanged in the sector. To this end, the book also describes some more the most popular Big Data, AI and Blockchain applications in the sector, including novel applications in the areas of Know Your Customer (KYC), Personalized Wealth Management and Asset Management, Portfolio Risk Assessment, as well as variety of novel Usage-based Insurance applications based on Internet-of-Things data. Most of the presented applications have been developed, deployed and validated in real-life digital finance settings in the context of the European Commission funded INFINITECH project, which is a flagship innovation initiative for Big Data and AI in digital finance. This book is ideal for researchers and practitioners in Big Data, AI, banking and digital finance

    A Survey on ChatGPT: AI-Generated Contents, Challenges, and Solutions

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    With the widespread use of large artificial intelligence (AI) models such as ChatGPT, AI-generated content (AIGC) has garnered increasing attention and is leading a paradigm shift in content creation and knowledge representation. AIGC uses generative large AI algorithms to assist or replace humans in creating massive, high-quality, and human-like content at a faster pace and lower cost, based on user-provided prompts. Despite the recent significant progress in AIGC, security, privacy, ethical, and legal challenges still need to be addressed. This paper presents an in-depth survey of working principles, security and privacy threats, state-of-the-art solutions, and future challenges of the AIGC paradigm. Specifically, we first explore the enabling technologies, general architecture of AIGC, and discuss its working modes and key characteristics. Then, we investigate the taxonomy of security and privacy threats to AIGC and highlight the ethical and societal implications of GPT and AIGC technologies. Furthermore, we review the state-of-the-art AIGC watermarking approaches for regulatable AIGC paradigms regarding the AIGC model and its produced content. Finally, we identify future challenges and open research directions related to AIGC.Comment: 20 pages, 6 figures, 4 table

    Big Data and Artificial Intelligence in Digital Finance

    Get PDF
    This open access book presents how cutting-edge digital technologies like Big Data, Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector. The book illustrates how recent advances in these technologies facilitate banks, FinTech, and financial institutions to collect, process, analyze, and fully leverage the very large amounts of data that are nowadays produced and exchanged in the sector. To this end, the book also describes some more the most popular Big Data, AI and Blockchain applications in the sector, including novel applications in the areas of Know Your Customer (KYC), Personalized Wealth Management and Asset Management, Portfolio Risk Assessment, as well as variety of novel Usage-based Insurance applications based on Internet-of-Things data. Most of the presented applications have been developed, deployed and validated in real-life digital finance settings in the context of the European Commission funded INFINITECH project, which is a flagship innovation initiative for Big Data and AI in digital finance. This book is ideal for researchers and practitioners in Big Data, AI, banking and digital finance
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