Johannes Schneider

Johannes Schneider
University of Liechtenstein · Institute of Information Systems

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110
Publications
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1,689
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Publications

Publications (110)
Article
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Digital agents with human-like characteristics have become ubiquitous in our society and are increasingly relevant in commercial applications. While some of them closely resemble humans in appearance (e.g., digital humans), they still lack many subtle social cues that are important for interacting with humans. Among them are the so-called microexpr...
Article
Full-text available
While artificial intelligence (AI) governance is thoroughly discussed on a philosophical, societal, and regulatory level, few works target companies. We address this gap by deriving a conceptual framework from literature. We decompose AI governance into governance of data, machine learning models, and AI systems along the dimensions of who, what, a...
Article
Full-text available
Spatial data exhibits the property that nearby points are correlated. This also holds for learnt representations across layers, but not for commonly used weight initialization methods. Our theoretical analysis quantifies the learning behavior of weights of a single spatial filter. It is thus in contrast to a large body of work that discusses statis...
Conference Paper
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While AI provides many business opportunities across industries, the organizational implications of AI are still largely unclear. We investigate governance roles related to AI use in practice, and undertake first steps to define the role profiles of a Chief AI Officer (CAIO) and an AI Risk Officer (AIRO). We base our inquiry on two sources: a liter...
Article
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Humans interact more and more with systems containing AI components. In this work, we focus on hand gestures such as handwriting and sketches serving as inputs to such systems. They are represented as a trajectory, i.e. sequence of points, that is altered to improve interaction with an AI model while keeping the model fixed. Optimized inputs are ac...
Article
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Interpreting a large number of neurons in deep learning is difficult. Our proposed ‘CLAssifier-DECoder’ architecture (ClaDec) facilitates the understanding of the output of an arbitrary layer of neurons or subsets thereof. It uses a decoder that transforms the incomprehensible representation of the given neurons to a representation that is more sim...
Preprint
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We propose to generate adversarial samples by modifying activations of upper layers encoding semantically meaningful concepts. The original sample is shifted towards a target sample, yielding an adversarial sample, by using the modified activations to reconstruct the original sample. A human might (and possibly should) notice differences between th...
Preprint
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The learning dynamics of deep neural networks are subject to controversy. Using the information bottleneck (IB) theory separate fitting and compression phases have been put forward but have since been heavily debated. We approach learning dynamics by analyzing a layer's reconstruction ability of the input and prediction performance based on the evo...
Article
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Autograding short textual answers has become much more feasible due to the rise of NLP and the increased availability of question-answer pairs brought about by a shift to online education. Autograding performance is still inferior to human grading. The statistical and black-box nature of state-of-the-art machine learning models makes them untrustwo...
Preprint
Full-text available
Autograding short textual answers has become much more feasible due to the rise of NLP and the increased availability of question-answer pairs brought about by a shift to online education. Autograding performance is still inferior to human grading. The statistical and black-box nature of state-of-the-art machine learning models makes them untrustwo...
Chapter
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Operators of complex, networked systems are constantly confronted with a large number of error events that are time-consuming to address. Events in one network component can trigger a cascade of events in other components leading to many intertwined sequences of a large number of error messages. Operators often only seek to identify and unders...
Conference Paper
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Artificial intelligence (AI) comes with great opportunities but can also pose significant risks. Automatically generated explanations for decisions can increase transparency and foster trust, especially for systems based on automated predictions by AI models. However, given, e.g., economic incentives to create dishonest AI, to what extent can we tr...
Article
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Keywords: artificial intelligence, deep learning, computational creativity. Abstract: While the potential of deep learning(DL) for automating simple tasks is already well explored, recent research has started investigating the use of deep learning for creative design, both for complete artifact creation and supporting humans in the creation process...
Article
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Inferring users’ perceptions of Virtual Environments (VEs) is essential for Virtual Reality (VR) research. Traditionally, this is achieved through assessing users’ affective states before and after being exposed to a VE, based on standardized, self-assessment questionnaires. The main disadvantage of questionnaires is their sequential administration...
Conference Paper
Full-text available
COVID-19 vaccination has led to unrest within societies, and intense public debates are often carried out on social media platforms like Twitter. A better understanding of concerns, issues, and communication on COVID-19 vaccines is a first step to reduce tension within society and improve the negative effects of the pandemic. It can also contribute...
Conference Paper
Full-text available
An essential aspect in the evaluation of Virtual Training Environments (VTEs) is the assessment of users' training success, preferably in real-time, e.g. to continuously adapt the training or to provide feedback. To achieve this, leveraging users' behavioral data has been shown to be a valid option. Behavioral data include sensor data from eye trac...
Preprint
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The data distribution commonly evolves over time leading to problems such as concept drift that often decrease classifier performance. We seek to predict unseen data (and their labels) allowing us to tackle challenges due to a non-constant data distribution in a \emph{proactive} manner rather than detecting and reacting to already existing changes...
Chapter
We present a ‘CLAssifier-DECoder’ architecture (ClaDec) which facilitates the comprehension of the output of an arbitrary layer in a neural network (NN). It uses a decoder to transform the non-interpretable representation of the given layer to a representation that is more similar to the domain a human is familiar with. In an image recognition prob...
Preprint
Full-text available
Interpreting a large number of neurons in deep learning is difficult. Our proposed `CLAssifier-DECoder' architecture (ClaDec) facilitates the understanding of the output of an arbitrary layer of neurons or subsets thereof. It uses a decoder that transforms the incomprehensible representation of the given neurons to a representation that is more sim...
Conference Paper
Full-text available
We present a 'CLAssifier-DECoder' architecture (ClaDec) which facilitates the comprehension of the output of an arbitrary layer in a neural network (NN). It uses a decoder to transform the non-interpretable representation of the given layer to a representation that is more similar to the domain a human is familiar with. In an image recognition prob...
Preprint
Full-text available
We present a `CLAssifier-DECoder' architecture (\emph{ClaDec}) which facilitates the comprehension of the output of an arbitrary layer in a neural network (NN). It uses a decoder to transform the non-interpretable representation of the given layer to a representation that is more similar to the domain a human is familiar with. In an image recogniti...
Article
Full-text available
For e-commerce retailers, even small increases in waiting times have been found to lead to user dissatisfaction and losses in sales. This paper investigates how contextual and behavioral factors influence the impact of latency on the website performance of a real e-commerce platform. The results show an increased impact of latency for users with fa...
Chapter
Full-text available
We discuss training techniques, objectives and metrics toward personalization of deep learning models. In machine learning, personalization addresses the goal of a trained model to target a particular individual by optimizing one or more performance metrics, while conforming to certain constraints. To personalize, we investigate three methods of “c...
Chapter
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This paper reports on a case study in collaborationwith an industry partner to explore the value creation potentials of Mixed Reality (MR) in construction. MR is a technology that allows for intuitive interaction with digital data through overlays on the real world, giving immediate access to the data of a construction site to quickly track or reso...
Conference Paper
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The COVID-19 pandemic accelerated the implementation and adoption of new features in web-conferencing systems (WCSs), such as custom backgrounds (CBs) that mask the real physical background with a custom, i.e., user chosen, background. In this work, we explore what types of backgrounds are selected and why they are used by analyzing text and images...
Article
While the analysis and usage of data are increasing in importance, the application of sophisticated BI solutions in small stores is limited by available technical capabilities and financial resources. This study investigates how brick-and-mortar stores can benefit from an expansion of service functionalities of a cross-industry loyalty card provide...
Conference Paper
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Understanding students’ sentiment is valuable to understanding the changes that could or should be made in curriculum design at third level. Learning analytics has shown potential for improving student learning experiences and supporting teacher inquiry. Yet, there is limited research that reports on the adoption and actual use of learning analytic...
Article
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Artificial Intelligence (AI) has diffused into many areas of our private and professional life. In this research note, we describe exemplary risks of black-box AI, the consequent need for explainability, and previous research on Explainable AI (XAI) in information systems research. Moreover, we discuss the origin of the term XAI, generalized XAI ob...
Preprint
Full-text available
While the potential of deep learning(DL) for automating simple tasks is already well explored, recent research started investigating the use of deep learning for creative design, both for complete artifact creation and supporting humans in the creation process. In this paper, we use insights from computational creativity to conceptualize and assess...
Preprint
Full-text available
Humans possess a remarkable capability to make fast, intuitive decisions, but also to self-reflect, i.e., to explain to oneself, and to efficiently learn from explanations by others. This work provides the first steps toward mimicking this process by capitalizing on the explanations generated based on existing explanation methods, i.e. Grad-CAM. Le...
Preprint
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Paper is finally published!!!! Cite as: Johannes Schneider, Rene Abraham, Christian Meske & Jan Vom Brocke (2022). Artificial Intelligence Governance For Businesses, Information Systems Management, DOI: 10.1080/10580530.2022.2085825 ------------------------------------------------------------------------------------------------------------------...
Preprint
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Humans rely more and more on systems with AI components. The AI community typically treats human inputs as a given and optimizes AI models only. This thinking is one-sided and it neglects the fact that humans can learn, too. In this work, human inputs are optimized for better interaction with an AI model while keeping the model fixed. The optimized...
Article
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Regulations to contain the spread of COVID-19 have affected corporations, institutions, and individuals to a degree that most people have never seen before. Information systems researchers have initiated a discourse on information technology's role in helping people manage this situation. This study informs and substantiates this discourse based on...
Conference Paper
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Data analytics has become an important part of companies in industry, leading to an increase in the demand for analytics experts. Data analytics is also a central aspect of trends such as “Big Data”, “Data Science”, “Artificial Intelligence”. As such, for potential analytics professionals to have relevant job skills, educational institutions need t...
Article
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This study investigates the potential influence of blockchain technology adoption on a company's competitive performance from an interorganizational systems perspective. A research framework is derived based on expert interviews and tested with a quantitative survey. The results show, that by offering traceability and immutability of transactions,...
Chapter
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Humans increasingly interact with Artificial intelligence (AI) systems. AI systems are optimized for objectives such as minimum computation or minimum error rate in recognizing and interpreting inputs from humans. In contrast, inputs created by humans are often treated as a given. We investigate how inputs of humans can be altered to reduce misinte...
Preprint
Full-text available
In an increasingly autonomous manner AI systems make decisions impacting our daily life. Their actions might cause accidents, harm or, more generally, violate regulations-either intentionally or not. Thus, AI systems might be considered suspects for various events. Therefore, it is essential to relate particular events to an AI, its owner and its c...
Preprint
Full-text available
Spatial data exhibits the property that nearby points are correlated. This holds also for learnt representations across layers, but not for commonly used weight initialization methods. Our theoretical analysis reveals for uncorrelated initial-ization that (i) flow through layers suffers from much more rapid decrease and (ii) training of individual...
Preprint
Full-text available
Artificial intelligence(AI) systems and humans communicate more and more with each other. AI systems are optimized for objectives such as error rate in communication or effort, eg. computation. In contrast, inputs created by humans are often treated as a given. We investigate how humans providing information to an AI can adjust to reduce miscommuni...
Conference Paper
Full-text available
Social networks are omnipresent in both our private and professional lives. As social beings, we thrive on the ability provided to us by the technology to be social. But what does it really mean to be social within social networks? To better capture and measure socialness in that context, we look beyond measures of being active and having many conn...
Article
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Interest in the field of data analytics among researchers and practitioners has been rising over the last few years. The digitalization of the built environment leads to increased availability of data, enabling the introduction of data analytics. In this paper we propose a novel framework for data driven value creation in architecture, engineering...
Conference Paper
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Interest in the field of data analytics among researchers and practitioners has been rising over the last few years. The ongoing process of digital transformation in architecture, engineering and construction (AEC) leads to increased availability of data along an asset's lifecycle, enabling the introduction of data analytics. Applications of data a...
Conference Paper
Full-text available
In this paper, we present a virtual learning environment for an industrial assembly task, which combines an easy-to-use interaction with an intuitive user experience. It is shown that such a virtual environment can be used for initial training to introduce tasks to new employees, but also experts may benefit from advanced training in case of new pr...
Preprint
Full-text available
We discuss training techniques, objectives and metrics toward mass personalization of deep learning models. In machine learning, personalization refers to the fact that every trained model should be targeted towards an individual by optimizing one or several performance metrics and often obeying additional constraints. We investigate three methods...
Conference Paper
Full-text available
Neural systems offer high predictive accuracy but are plagued by long training times and low interpretability. We present a simple neural architecture for recommender systems that lifts several of these shortcomings. Firstly, the approach has a high predictive power that is comparable to state-of-the-art recommender approaches. Secondly, owing to i...
Article
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Data governance refers to the exercise of authority and control over the management of data. The purpose of data governance is to increase the value of data and minimize data-related cost and risk. Despite data governance gaining in importance in recent years, a holistic view on data governance, which could guide both practitioners and researchers,...
Preprint
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This work investigates questions related to learning features in convolutional neural networks (CNN). Empirical findings across multiple architectures such as VGG, ResNet, Inception and MobileNet indicate that weights near the center of a filter are larger than weights on the outside. Current regularization schemes violate this principle. Thus, we...
Conference Paper
Full-text available
Explanation in machine learning and related fields such as artificial intelligence aims at making machine learning models and their decisions understandable to humans. Existing work suggests that personalizing explanations might help to improve understandability. In this work, we derive a conceptualization of personalized explanation by defining an...
Conference Paper
Full-text available
This paper develops a set of principles for green data mining, related to the key stages of business understanding, data understanding, data preparation, modeling, evaluation, and deployment. The principles are grounded in a review of the Cross Industry Standard Process for Data mining (CRISP-DM) model and relevant literature on data mining methods...
Conference Paper
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Due to the rapid shift of companies towardssuperb customer experience and satisfaction, ticketing systemshave come into a prominence and represent a strategic elementin business competitiveness. Different software companies havedeveloped very effective software tools for issue tracking, nev-ertheless, some sub-processes and tasks within the ticketi...
Chapter
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Trust is a key concern in big data analytics (BDA). Explaining “black-box” models, demonstrating transferability of models and robustness to data changes with respect to quality or content can help in improving confidence in BDA. To this end, we propose metrics for measuring robustness with respect to input noise. We also provide empirical evidence...
Conference Paper
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Emotions spread through online and offline social networks and subsequently influence individuals' decisions and behaviours. Empirical studies on emotional contagion are almost non-existent in information systems research, leaving a gap in understanding how individuals are affected by emotions expressed in online sources. Online newspaper articles...
Article
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We give a new randomized distributed algorithm for (Δ +1)-coloring in the LOCAL model, running in O(&sqrt; log Δ)+ 2O(&sqrt;log log n) rounds in a graph of maximum degree Δ. This implies that the (Δ +1)-coloring problem is easier than the maximal independent set problem and the maximal matching problem, due to their lower bounds of Ω(min(&sqrt;&fra...
Article
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Blockchain technology has the ability to disrupt most of today’s markets.We describe the business case of the fintech startup Own that aims to use blockchain technology to disrupt the equity market.We use this case to provide a specific example of how blockchain-based business models work and how they can disrupt markets by cutting out intermediari...
Article
This study examines how dimensions of culture influence variations in views about the link between corporate tax payments and corporate social responsibility (CSR). Using textual analysis and a newly-developed set of keywords unique to a tax setting, we analyze 4,438 CSR reports from 24 countries, which is the largest sample that has been analyzed...
Conference Paper
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Digital social networks play an increasingly important role in organizations. Such enterprise social networks (ESN) allow users to form and join groups and the exchange of messages within or across such groups. ESN are said to improve communication and collaboration across boundaries, therefore increasing the flow of information, exchange of knowle...