14,955 research outputs found
Making a first impression as a start-up: Strategies to overcome low initial trust perceptions in digital innovation adoption
High failure rates of digital innovations by start-ups indicate that consumers' initial trust perceptions are make-or-break for their survival. Hence, start-ups have to design adequate business models to manage consumers' initial trust perceptions of digital innovations. Five experiments explore how start-ups can signal trustworthiness in order to overcome low initial trust perceptions and boost adoption. We find three specific design strategies of start-ups' digital business models – customer ratings, benefit communication, and revenue model – to be effective to overcome low initial trust perceptions and to increase adoption of digital innovations. The findings demonstrate that initial trust serves as a critical mediator in the relationship between these design strategies and consumers' adoption intentions. Additionally, the chosen revenue model has differential effects on privacy concerns, which mediate the relationship between revenue model and initial trust. The present empirical insights help start-ups to craft business model design strategies for successful digital innovation launch
Trustworthy IoT: An evidence collection approach based on smart contracts
Today, Internet of Things (IoT) implements an ecosystem where a panoply of interconnected devices collect data from physical environments and supply them to processing services, on top of which cloud-based applications are built and provided to mobile end users. The undebatable advantages of smart IoT systems clash with the need of a secure and trustworthy environment. In this paper, we propose a service-based methodology based on blockchain and smart contracts for trustworthy evidence collection at the basis of a trustworthy IoT assurance evaluation. The methodology balances the provided level of trustworthiness and its performance, and is experimentally evaluated using Hyperledger fabric blockchain
Dignitas: uso de reputação como moeda para avaliar a sensorização humana em cidades inteligentes
We live in an increasingly digital world, where Smart Cities have become a reality.
One of the characteristics that make these cities smart is their ability to gather
information and act upon it, improving their citizens lives. In this work, we present
our system, Dignitas. A blockchain-based reputation system that allows citizens
of a Smart City to assess the truthiness of information posted by other citizens.
This assessment is based on a bet that reporters make, and all of those who agreed
with him, that puts their gathered reputation at stake. This use of Reputation as
a currency is a novel idea that allowed us to build an anonymous system. Using
blockchain we were able to have multiple authorities, working with each other to
make the system secure and thus avoiding centralized schemes. Our work was
focused on developing our idea, a proof of concept, and testing the viability of our
new solution.Vivemos num mundo cada vez mais digital, onde as cidades inteligentes passaram
a ser uma realidade. Uma das características que permite a estas cidades serem inteligentes
é a capacidade de adquirir informação e agir sobre ela, melhorando a vida
de todos os cidadãos. Neste trabalho apresentamos o nosso sistema, Dignitas, um
sistema de reputação baseado numa blockchain que permite aos cidadãos de uma
cidade inteligente avaliar informação relatada por outras pessoas. Esta avaliação
é baseada numa aposta feita pelo relator, e por todos os que com ele concordam,
em que põe em risco parte da sua Reputação no sistema. Este uso da Reputação
como uma moeda é o que nos permite construir um sistema anónimo. O uso de
uma blockchain permite-nos ter múltiplas autoridades responsáveis, evitando por
isso o uso de esquemas centralizados. O nosso trabalho focou-se em desenvolver a
nossa ideia, uma prova de conceito, e testar a viabilidade desta nossa nova solução.Mestrado em Engenharia de Computadores e Telemátic
Building trust in AI Systems
Artificial Intelligence has integrated as a part of humans’ daily life while at the same time the AI-enabled services and applications are widely considered distrustful. Because the majority of the users are not expert in Machine Learning, not to mention Deep learning, it is important to create trustworthy AI services that understand humans but also explains themselves in an easily understandable way. This type of approach to Artificial Intelligence is called Explainable Hu- man-Centered thinking and it has been discovered as a solution for the distrust problem between human-AI interaction. This research is a qualitative study of User-Experience of different AI-based applications and services that are used in daily life activities such as navigation or checking grammar mistakes. The goal is to find UX elements that affect to user’s trust-perception of the service or application and create a united list of these elements based on previous literature. This list can be used for designing better, explainable, and human-centered AI, but it also fulfills its purpose by gathering together and validating research of the field. The results showed that even in the most strongly trusted services and applications, users can notice problems such as privacy issues or missing explainability. However, many of the commonly used services pro- vide added value for its user and they are relatively better than the other similar services. Based on the results, this study discusses also critically whether implementing HAI is only a UX-de- sign problem but rather a part of sharing knowledge of trustworthy AI and not accepting non- transparent functions and data usage.Tekoäly on integroitunut osaksi ihmisten jokapäiväistää elämää, mutta yleisesti tekoälyperustaisia palveluja ja sovelluksia ei pidetä luotettavina. T ämän lisäksi välillä palveluja tai sovelluksia käyttäessä on mahdotonta todentaa, onko käyttäjä kosketuksissa ihmisen vai koneen kanssa ja mihinkä käyttäjän saama informaatio, kuten ohjeet tai ehdotukset, perustuvat. Koska tämän tyyppinen käyttäjäkokemus lisää epäluottamusta ihmisen ja tietokoneen kanssakäymisessä ja koska suurin osa käyttäjistä ei ole koneoppimisen asiantuntijoita, on tärkeää luoda luotettavia tekoälypalveluja, jotka ymmärtävät ihmisiä ja selittävät omaa toimintaansa helposti ymmärrettävällä tavalla. Tämän tyyppistä lähestymistapaa tekoälyyn kutsutaan selittäväksi ihmiskeskiseksi (explainable human-centered) ajatteluksi ja sitä on pidetty ratkaisuna nimenomaiseen ihmisen ja tekoälyn välisen epäluottamuksen ongelmaan.
Tämä kvalitatiivinen tutkimus tarkastelee käyttäjäkokemusta erilaisissa tekoälypohjaisista sovelluksista ja palveluista, joita käytetään jokapäiväisessä elämässä, kuten navigoinnissa tai esimerkiksi kieliasun tai kielioppivirheiden tarkastuksessa. Tavoitteena on löytää UX-elementit, jotka vaikuttavat käyttäjän kokemukseen luottamuksesta käyttäessään palvelua tai sovellusta, ja luoda yhtenäinen luettelo näistä elementeistä aiemman kirjallisuuden perusteella. Tätä luetteloa voidaan käyttää apuna ihmiskeskeisessä tekoälysuunnittelussa, mutta se täyttää tarkoituksensa myös kokoamalla yhteen ja validoimalla alan aiempaa tutkimusta nimenomaan tekoälyperusteisista sovelluksiin liittyen.
Kirjallisuuskatsaus esittelee tutkimuksen keskeiset käsitteet, kuten tekoälyn, luottamuksen ja käyttäjäkokemuksen. Lisäksi tässä osiossa kerätään yhteen tärkeimmät edellisissä tutkimuksissa jo identifioidut UX-elementit, jotka vaikuttavat käyttäjän kokemaan luottamukseen muun muassa web-suunnittelussa. Itse tutkimus jakaantuu kolmeen vaiheeseen, jossa ensimmäisenä tekoälyperustaiset sovellukset listataan perustuen alan kirjallisuuden tyyppimääritelmiin sekä käyttäjämäärä arvioiden mukaan. Toisessa vaiheessa, valitut sovellukset ja palvelut listattiin luotetuimmasta epäluotettavimpaan perustuen lyhyeen kyselytutkimukseen. Viimeiseksi syvähaastattelu, perustuen kriittisten tapahtumien tekniikkaan, suoritettiin kyselyyn vastanneille. Avoimilla kysymyksillä kartoitettiin tietoja tapahtumasta, jossa käyttäjä tunsi luottamusta tai epäluottamusta käyttäessään valittua tekoälyperusteistasovellusta tai palvelua.
Tulokset analysoitiin teemoittamalla havaitut UX elementit, jotka lisäävät luottamusta tai vähentävät epäluottamusta ja vertaamalla niitä listaan alan edellisistä havainnoista luottamukseen liittyen. Tuloksena saatiin tutkimuksen tavoitteen mukainen lista, jossa on validoitu kirjallisuuden havaintoja, että lisätty uusia havaintoja luottamukseen vaikuttavista UX- elementeistä perustuen tehtyihin käyttäjähaastatteluihin.
Kaiken kaikkiaan tämän tutkimuksen tärkeimmät havainnot vahvistivat luettelon tärkeistä UX- elementeistä, jotka on otettava huomioon luotaessa käyttäjien ja tekoälyjärjestelmien välistä luottamusta, mutta samalla vain luotettavien palvelujen suunnittelu ei riitä. Yksi tutkimuksen johtopäätös onkin, että kyselyn osallistujat käyttivät näitä palveluja, vaikka monet olivat huolissaan esimerkiksi omasta yksityisyydestään tai järjestelmän epämääräisestä datakäytöstä.
Näin ollen nämä tulokset osoittavat, että käyttäjät hyväksyivät nämä käytännöt, koska sovelluksen tai palvelun käyttäminen toi suhteellista etua muihin palveluihin verrattuna tai merkittävää lisäarvoa käyttäjän jokapäiväiseen elämään. Näiden tulosten perusteella, tässä tutkimuksessa keskustellaan myös kriittisesti siitä, onko HAI:n (Human Centered Artificial intelligence) eli ihmiskeskeisen tekoälyn käyttöönotto vain UX-suunnittelun ongelma, vaan pikemminkin osa koulutusta ja tiedon jakamista luotettavasta tekoälystä jolloin käyttäjät eivät hyväksy läpinäkymättömiä toimintoja tai tietojen väärinkäyttöä, vaan vaativat luotettavia ja avoimia käytäntöjä, jotka selitetään heille erilaisten käyttöliittymäelementtien kautta
Overcoming the Blockchain Oracle Problem in the Traceability of Non-Fungible Products
Blockchain implications within the sustainability domain are rapidly arousing the interest of researchers and institutions. However, despite the avalanche of articles, papers, and recently published books, innovation in the blockchain domain is still heavily influenced by light literature, such as news, articles, opinion posts, and white papers. Lacking a homogeneous literature background, case studies often fall into storytelling, providing mere descriptions of the facts according to the writers\u2019 impressions and opinions. We therefore investigate blockchain adoption for sustainable purposes through a case study while remaining firmly grounded in three main theoretical literature streams: knowledge management, knowledge infrastructure, and trust. Since blockchain interaction with the real world is managed by oracles, addressing the oracle problem is essential in order to evaluate the effectiveness of blockchain for sustainability issues. However, to the best of the authors\u2019 knowledge, no other paper has effciently addressed this subject or even mentioned it. Recognizing its scarce consideration in the literature, the oracle problem will be analyzed in both theoretical and practical terms, thereby providing a way to solve the issues related to non-fungible products in the supply chain. Choice over the selected case study was made in light of the divergence in motives for the adoption of blockchain (economic over social), which makes the results more inferable at a broader scale and offers an insight into how sustainable innovations can also be economically viabl
Digitising the Industry Internet of Things Connecting the Physical, Digital and VirtualWorlds
This book provides an overview of the current Internet of Things (IoT) landscape, ranging from the research, innovation and development priorities to enabling technologies in a global context. A successful deployment of IoT technologies requires integration on all layers, be it cognitive and semantic aspects, middleware components, services, edge devices/machines and infrastructures. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC - Internet of Things European Research Cluster from research to technological innovation, validation and deployment. The book builds on the ideas put forward by the European Research Cluster and the IoT European Platform Initiative (IoT-EPI) and presents global views and state of the art results on the challenges facing the research, innovation, development and deployment of IoT in the next years. The IoT is bridging the physical world with virtual world and requires sound information processing capabilities for the "digital shadows" of these real things. The research and innovation in nanoelectronics, semiconductor, sensors/actuators, communication, analytics technologies, cyber-physical systems, software, swarm intelligent and deep learning systems are essential for the successful deployment of IoT applications. The emergence of IoT platforms with multiple functionalities enables rapid development and lower costs by offering standardised components that can be shared across multiple solutions in many industry verticals. The IoT applications will gradually move from vertical, single purpose solutions to multi-purpose and collaborative applications interacting across industry verticals, organisations and people, being one of the essential paradigms of the digital economy. Many of those applications still have to be identified and involvement of end-users including the creative sector in this innovation is crucial. The IoT applications and deployments as integrated building blocks of the new digital economy are part of the accompanying IoT policy framework to address issues of horizontal nature and common interest (i.e. privacy, end-to-end security, user acceptance, societal, ethical aspects and legal issues) for providing trusted IoT solutions in a coordinated and consolidated manner across the IoT activities and pilots. In this, context IoT ecosystems offer solutions beyond a platform and solve important technical challenges in the different verticals and across verticals. These IoT technology ecosystems are instrumental for the deployment of large pilots and can easily be connected to or build upon the core IoT solutions for different applications in order to expand the system of use and allow new and even unanticipated IoT end uses. Technical topics discussed in the book include: • Introduction• Digitising industry and IoT as key enabler in the new era of Digital Economy• IoT Strategic Research and Innovation Agenda• IoT in the digital industrial context: Digital Single Market• Integration of heterogeneous systems and bridging the virtual, digital and physical worlds• Federated IoT platforms and interoperability• Evolution from intelligent devices to connected systems of systems by adding new layers of cognitive behaviour, artificial intelligence and user interfaces.• Innovation through IoT ecosystems• Trust-based IoT end-to-end security, privacy framework• User acceptance, societal, ethical aspects and legal issues• Internet of Things Application
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