3D-LIVE : live interactions through 3D visual environments

This paper explores Future Internet (FI) 3D-Media technologies and Internet of Things (IoT) in real and virtual environments in order to sense and experiment Real-Time interaction within live situations. The combination of FI testbeds and Living Labs (LL) would enable both researchers and users to explore capacities to enter the 3D Tele-Immersive (TI) application market and to establish new requirements for FI technology and infrastructure. It is expected that combining both FI technology pull and TI market pull would promote and accelerate the creation and adoption, by user communities such as sport practitioners, of innovative TI Services within sport events

Dynamic Estimation of Rater Reliability using Multi-Armed Bandits

One of the critical success factors for supervised machine learning is the quality of target values, or predictions, associated with training instances. Predictions can be discrete labels (such as a binary variable specifying whether a blog post is positive or negative) or continuous ratings (for instance, how boring a video is on a 10-point scale). In some areas, predictions are readily available, while in others, the eort of human workers has to be involved. For instance, in the task of emotion recognition from speech, a large corpus of speech recordings is usually available, and humans denote which emotions are present in which recordings

Living Innovation Laboratory Model Design and Implementation

Living Innovation Laboratory (LIL) is an open and recyclable way for multidisciplinary researchers to remote control resources and co-develop user centered projects. In the past few years, there were several papers about LIL published and trying to discuss and define the model and architecture of LIL. People all acknowledge about the three characteristics of LIL: user centered, co-creation, and context aware, which make it distinguished from test platform and other innovation approaches. Its existing model consists of five phases: initialization, preparation, formation, development, and evaluation. Goal Net is a goal-oriented methodology to formularize a progress. In this thesis, Goal Net is adopted to subtract a detailed and systemic methodology for LIL. LIL Goal Net Model breaks the five phases of LIL into more detailed steps. Big data, crowd sourcing, crowd funding and crowd testing take place in suitable steps to realize UUI, MCC and PCA throughout the innovation process in LIL 2.0. It would become a guideline for any company or organization to develop a project in the form of an LIL 2.0 project. To prove the feasibility of LIL Goal Net Model, it was applied to two real cases. One project is a Kinect game and the other one is an Internet product. They were both transformed to LIL 2.0 successfully, based on LIL goal net based methodology. The two projects were evaluated by phenomenography, which was a qualitative research method to study human experiences and their relations in hope of finding the better way to improve human experiences. Through phenomenographic study, the positive evaluation results showed that the new generation of LIL had more advantages in terms of effectiveness and efficiency.Comment: This is a book draf

Improving User Involvement Through Live Collaborative Creation

Creating an artifact - such as writing a book, developing software, or performing a piece of music - is often limited to those with domain-specific experience or training. As a consequence, effectively involving non-expert end users in such creative processes is challenging. This work explores how computational systems can facilitate collaboration, communication, and participation in the context of involving users in the process of creating artifacts while mitigating the challenges inherent to such processes. In particular, the interactive systems presented in this work support live collaborative creation, in which artifact users collaboratively participate in the artifact creation process with creators in real time. In the systems that I have created, I explored liveness, the extent to which the process of creating artifacts and the state of the artifacts are immediately and continuously perceptible, for applications such as programming, writing, music performance, and UI design. Liveness helps preserve natural expressivity, supports real-time communication, and facilitates participation in the creative process. Live collaboration is beneficial for users and creators alike: making the process of creation visible encourages users to engage in the process and better understand the final artifact. Additionally, creators can receive immediate feedback in a continuous, closed loop with users. Through these interactive systems, non-expert participants help create such artifacts as GUI prototypes, software, and musical performances. This dissertation explores three topics: (1) the challenges inherent to collaborative creation in live settings, and computational tools that address them; (2) methods for reducing the barriers of entry to live collaboration; and (3) approaches to preserving liveness in the creative process, affording creators more expressivity in making artifacts and affording users access to information traditionally only available in real-time processes. In this work, I showed that enabling collaborative, expressive, and live interactions in computational systems allow the broader population to take part in various creative practices.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145810/1/snaglee_1.pd

The effects of user assistance systems on user perception and behavior

The rapid development of information technology (IT) is changing how people approach and interact with IT systems (Maedche et al. 2016). IT systems can increasingly support people in performing ever more complex tasks (Vtyurina and Fourney 2018). However, people's cognitive abilities have not evolved as quickly as technology (Maedche et al. 2016). Thus, different external factors (e.g., complexity or uncertainty) and internal conditions (e.g., cognitive load or stress) reduce decision quality (Acciarini et al. 2021; Caputo 2013; Hilbert 2012). User-assistance systems (UASs) can help to compensate for human weaknesses and cope with new challenges. UASs aim to improve the user's cognition and capabilities, benefiting individuals, organizations, and society. To achieve this goal, UASs collect, prepare, aggregate, analyze information, and communicate results according to user preferences (Maedche et al. 2019). This support can relieve users and improve the quality of decision-making. Using UASs offers many benefits but requires successful interaction between the user and the UAS. However, this interaction introduces social and technical challenges, such as loss of control or reduced explainability, which can affect user trust and willingness to use the UAS (Maedche et al. 2019). To realize the benefits, UASs must be developed based on an understanding and incorporation of users' needs. Users and UASs are part of a socio-technical system to complete a specific task (Maedche et al. 2019). To create a benefit from the interaction, it is necessary to understand the interaction within the socio-technical system, i.e., the interaction between the user, UAS, and task, and to align the different components. For this reason, this dissertation aims to extend the existing knowledge on UAS design by better understanding the effects and mechanisms during the interaction between UASs and users in different application contexts. Therefore, theory and findings from different disciplines are combined and new theoretical knowledge is derived. In addition, data is collected and analyzed to validate the new theoretical knowledge empirically. The findings can be used to reduce adaptation barriers and realize a positive outcome. Overall this dissertation addresses the four classes of UASs presented by Maedche et al. (2016): basic UASs, interactive UASs, intelligent UASs, and anticipating UASs. First, this dissertation contributes to understanding how users interact with basic UASs. Basic UASs do not process contextual information and interact little with the user (Maedche et al. 2016). This behavior makes basic UASs suitable for application contexts, such as social media, where little interaction is desired. Social media is primarily used for entertainment and focuses on content consumption (Moravec et al. 2018). As a result, social media has become an essential source of news but also a target for fake news, with negative consequences for individuals and society (Clarke et al. 2021; Laato et al. 2020). Thus, this thesis presents two approaches to how basic UASs can be used to reduce the negative influence of fake news. Firstly, basic UASs can provide interventions by warning users of questionable content and providing verified information but the order in which the intervention elements are displayed influences the fake news perception. The intervention elements should be displayed after the fake news story to achieve an efficient intervention. Secondly, basic UASs can provide social norms to motivate users to report fake news and thereby stop the spread of fake news. However, social norms should be used carefully, as they can backfire and reduce the willingness to report fake news. Second, this dissertation contributes to understanding how users interact with interactive UASs. Interactive UASs incorporate limited information from the application context but focus on close interaction with the user to achieve a specific goal or behavior (Maedche et al. 2016). Typical goals include more physical activity, a healthier diet, and less tobacco and alcohol consumption to prevent disease and premature death (World Health Organization 2020). To increase goal achievement, previous researchers often utilize digital human representations (DHRs) such as avatars and embodied agents to form a socio-technical relationship between the user and the interactive UAS (Kim and Sundar 2012a; Pfeuffer et al. 2019). However, understanding how the design features of an interactive UAS affect the interaction with the user is crucial, as each design feature has a distinct impact on the user's perception. Based on existing knowledge, this thesis highlights the most widely used design features and analyzes their effects on behavior. The findings reveal important implications for future interactive UAS design. Third, this dissertation contributes to understanding how users interact with intelligent UASs. Intelligent UASs prioritize processing user and contextual information to adapt to the user's needs rather than focusing on an intensive interaction with the user (Maedche et al. 2016). Thus, intelligent UASs with emotional intelligence can provide people with task-oriented and emotional support, making them ideal for situations where interpersonal relationships are neglected, such as crowd working. Crowd workers frequently work independently without any significant interactions with other people (Jäger et al. 2019). In crowd work environments, traditional leader-employee relationships are usually not established, which can have a negative impact on employee motivation and performance (Cavazotte et al. 2012). Thus, this thesis examines the impact of an intelligent UAS with leadership and emotional capabilities on employee performance and enjoyment. The leadership capabilities of the intelligent UAS lead to an increase in enjoyment but a decrease in performance. The emotional capabilities of the intelligent UAS reduce the stimulating effect of leadership characteristics. Fourth, this dissertation contributes to understanding how users interact with anticipating UASs. Anticipating UASs are intelligent and interactive, providing users with task-related and emotional stimuli (Maedche et al. 2016). They also have advanced communication interfaces and can adapt to current situations and predict future events (Knote et al. 2018). Because of these advanced capabilities anticipating UASs enable collaborative work settings and often use anthropomorphic design cues to make the interaction more intuitive and comfortable (André et al. 2019). However, these anthropomorphic design cues can also raise expectations too high, leading to disappointment and rejection if they are not met (Bartneck et al. 2009; Mori 1970). To create a successful collaborative relationship between anticipating UASs and users, it is important to understand the impact of anthropomorphic design cues on the interaction and decision-making processes. This dissertation presents a theoretical model that explains the interaction between anthropomorphic anticipating UASs and users and an experimental procedure for empirical evaluation. The experiment design lays the groundwork for empirically testing the theoretical model in future research. To sum up, this dissertation contributes to information systems knowledge by improving understanding of the interaction between UASs and users in different application contexts. It develops new theoretical knowledge based on previous research and empirically evaluates user behavior to explain and predict it. In addition, this dissertation generates new knowledge by prototypically developing UASs and provides new insights for different classes of UASs. These insights can be used by researchers and practitioners to design more user-centric UASs and realize their potential benefits

A Multi-Dimensional Approach for Framing Crowdsourcing Archetypes

All different kinds of organizations – business, public, and non-governmental alike – are becoming aware of a soaring complexity in problem solving, decision making and idea development. In a multitude of circumstances, multidisciplinary teams, high-caliber skilled resources and world-class computer suites do not suffice to cope with such a complexity: in fact, a further need concerns the sharing and ‘externalization’ of tacit knowledge already existing in the society. In this direction, participatory tendencies flourishing in the interconnected society in which we live today lead ‘collective intelligence’ to emerge as key ingredient of distributed problem solving systems going well beyond the traditional boundaries of organizations. Resulting outputs can remarkably enrich decision processes and creative processes carried out by indoor experts, allowing organizations to reap benefits in terms of opportunity, time and cost. Taking stock of the mare magnum of promising opportunities to be tapped, of the inherent diversity lying among them, and of the enormous success of some initiative launched hitherto, the thesis aspires to provide a sound basis for the clear comprehension and systematic exploitation of crowdsourcing. After a thorough literature review, the thesis explores new ways for formalizing crowdsourcing models with the aim of distilling a brand-new multi-dimensional framework to categorize various crowdsourcing archetypes. To say it in a nutshell, the proposed framework combines two dimensions (i.e., motivations to participate and organization of external solvers) in order to portray six archetypes. Among the numerous significant elements of novelty brought by this framework, the prominent one is the ‘holistic’ approach that combines both profit and non-profit, trying to put private and public sectors under a common roof in order to examine in a whole corpus the multi-faceted mechanisms for mobilizing and harnessing competence and expertise which are distributed among the crowd. Looking at how the crowd may be turned into value to be internalized by organizations, the thesis examines crowdsourcing practices in the public as well in the private sector. Regarding the former, the investigation leverages the experience into the PADGETS project through action research – drawing on theoretical studies as well as on intensive fieldwork activities – to systematize how crowdsourcing can be fruitfully incorporated into the policy lifecycle. Concerning the private realm, a cohort of real cases in the limelight is examined – having recourse to case study methodology – to formalize different ways through which crowdsourcing becomes a business model game-changer. Finally, the two perspectives (i.e., public and private) are coalesced into an integrated view acting as a backdrop for proposing next-generation governance model massively hinged on crowdsourcing. In fact, drawing on archetypes schematized, the thesis depicts a potential paradigm that government may embrace in the coming future to tap the potential of collective intelligence, thus maximizing the utilization of a resource that today seems certainly underexploited

Evaluating Human-Language Model Interaction

Many real-world applications of language models (LMs), such as writing assistance and code autocomplete, involve human-LM interaction. However, most benchmarks are non-interactive in that a model produces output without human involvement. To evaluate human-LM interaction, we develop a new framework, Human-AI Language-based Interaction Evaluation (HALIE), that defines the components of interactive systems and dimensions to consider when designing evaluation metrics. Compared to standard, non-interactive evaluation, HALIE captures (i) the interactive process, not only the final output; (ii) the first-person subjective experience, not just a third-party assessment; and (iii) notions of preference beyond quality (e.g., enjoyment and ownership). We then design five tasks to cover different forms of interaction: social dialogue, question answering, crossword puzzles, summarization, and metaphor generation. With four state-of-the-art LMs (three variants of OpenAI's GPT-3 and AI21 Labs' Jurassic-1), we find that better non-interactive performance does not always translate to better human-LM interaction. In particular, we highlight three cases where the results from non-interactive and interactive metrics diverge and underscore the importance of human-LM interaction for LM evaluation.Comment: Authored by the Center for Research on Foundation Models (CRFM) at the Stanford Institute for Human-Centered Artificial Intelligence (HAI

Distributed Data Management in Vehicular Networks Using Mobile Agents

En los últimos años, las tecnologías de la información y las comunicaciones se han incorporado al mundo de la automoción gracias a sus avances, y han permitido la creación de dispositivos cada vez más pequeños y potentes. De esta forma, los vehículos pueden ahora incorporar por un precio asequible equipos informáticos y de comunicaciones.En este escenario, los vehículos que circulan por una determinada zona (como una ciudad o una autopista) pueden comunicarse entre ellos usando dispositivos inalámbricos que les permiten intercambiar información con otros vehículos cercanos, formando así una red vehicular ad hoc, o VANET (Vehicular Ad hoc Network). En este tipo de redes, las comunicaciones se establecen con conexiones punto a punto por medio de dispositivos tipo Wi-Fi, que permiten la comunicación con otros del mismo tipo dentro de su alcance, sin que sea necesaria la existencia previa de una infraestructura de comunicaciones como ocurre con las tecnologías de telefonía móvil (como 3G/4G), que además requieren de una suscripción y el pago de una tarifa para poder usarlas.Cada vehículo puede enviar información y recibirla de diversos orígenes, como el propio vehículo (por medio de los sensores que lleva incorporados), otros vehículos que se encuentran cerca, así como de la infraestructura de tráfico presente en las carreteras (como semáforos, señales, paneles electrónicos de información, cámaras de vigilancia, etc.). Todos estas fuentes pueden transmitir datos de diversa índole, como información de interés para los conductores (por ejemplo, atascos de tráfico o accidentes en la vía), o de cualquier otro tipo, mientras sea posible digitalizarla y enviarla a través de una red.Todos esos datos pueden ser almacenados localmente en los ordenadores que llevan los vehículos a medida que son recibidos, y sería muy interesante poder sacarles partido por medio de alguna aplicación que los explotara. Por ejemplo, podrían utilizarse los vehículos como plataformas móviles de sensores que obtengan datos de los lugares por los que viajan. Otro ejemplo de aplicación sería la de ayudar a encontrar plazas de aparcamiento libres en una zona de una ciudad, usando la información que suministrarían los vehículos que dejan una plaza libre.Con este fin, en esta tesis se ha desarrollado una propuesta de la gestión de datos basada en el uso de agentes móviles para poder hacer uso de la información presente en una VANET de forma eficiente y flexible. Esta no es una tarea trivial, ya que los datos se encuentran dispersos entre los vehículos que forman la red, y dichos vehículos están constantemente moviéndose y cambiando de posición. Esto hace que las conexiones de red establecidas entre ellos sean inestables y de corta duración, ya que están constantemente creándose y destruyéndose a medida que los vehículos entran y salen del alcance de sus comunicaciones debido a sus movimientos.En un escenario tan complicado, la aproximación que proponemos permite que los datos sean localizados, y que se puedan hacer consultas sobre ellos y transmitirlos de un sitio cualquiera de la VANET a otro, usando estrategias multi-salto que se adaptan a las siempre cambiantes posiciones de los vehículos. Esto es posible gracias a la utilización de agentes móviles para el procesamiento de datos, ya que cuentan con una serie de propiedades (como su movilidad, autonomía, adaptabilidad, o inteligencia), que hace que sean una elección muy apropiada para este tipo de entorno móvil y con un elevado grado de incertidumbre.La solución propuesta ha sido extensamente evaluada y probada por medio de simulaciones, que demuestran su buen rendimiento y fiabilidad en redes vehiculares con diferentes condiciones y en diversos escenarios.<br /