Jan Marco Leimeister

The pervasiveness and increasing sophistication of artificial intelligence (AI)-based artifacts within private, organizational, and social realms change how humans interact with machines. Theorizing about the way humans perceive AI-based artifacts is crucial to understanding why and to what extent humans deem these as competent for, i.e., decision-making, yet has traditionally taken a modality-agnostic view. In this paper, we theorize about a particular case of interaction, namely that of voice-based interaction with AI-based artifacts. The capabilities and perceived naturalness of such artifacts, fueled by continuous advances in natural language processing, induce users to deem an artifact as able to act autonomously in a goal-oriented manner. We argue that there is a positive direct relationship between the voice capabilities of an artifact and users’ agency attribution, ultimately obscuring the artifact’s true nature and competencies. This relationship is further moderated by an artifact’s actual agency, uncertainty, and user characteristics.

Traditionally, the metaverse has been defined as a virtual reality space in which users can interact with a computer-generated environment and other users. Nowadays, it is much more than that—the metaverse can be described as a variety of digital platforms and ecosystems, with each ecosystem as an independent universe with its own material, complementors, and functionalities. Creating metaverse ecosystems and integrated platforms results in different roles and responsibilities for complementors, consumers, platform owners, and orchestrators. The term metaverse platforms is further structured and clarified by four perspectives: innovation, production, transaction, and social interaction. Consequently, this fundamental paper defines it as: “A Metaverse is a massively scaled and interoperable meta-ecosystem of other digital ecosystems of real-time rendered 3D virtual worlds which can be experienced synchronously and persistently by an unlimited number of complementors and consumers with an increased user experience caused by a creativity-guided co-creation of goods managed by orchestrators and supported by platform owners.” Consequently, the metaverse offers vast opportunities for digital innovations beyond traditional social media or computer games and creates new infrastructures for add-on innovations in all areas of the digital economy.

Conversational agents (CAs) have come a long way from their first appearance in the 1960s to today's generative models. Continuous technological advancements such as statistical computing and large language models allow for an increasingly natural and effortless interaction, as well as domain-agnostic deployment opportunities. Ultimately, this evolution begs multiple questions: How have technical capabilities developed? How is the nature of work changed through humans' interaction with conversational agents? How has research framed dominant perceptions and depictions of such agents? And what is the path forward? To address these questions, we conducted a bibliometric study including over 5000 research articles on CAs. Based on a systematic analysis of keywords, topics, and author networks, we derive "five waves of CA research" that describe the past, present, and potential future of research on CAs. Our results highlight fundamental technical evolutions and theoretical paradigms in CA research. Therefore, we discuss the moderating role of big technologies, and novel technological advancements like OpenAI GPT or BLOOM NLU that mark the next frontier of CA research. We contribute to theory by laying out central research streams in CA research, and offer practical implications by highlighting the design and deployment opportunities of CAs.

Persuasive system design (PSD) is an umbrella term for designs in information systems (IS) that can influence people’s attitude, behavior, or decision making for better or for worse. On the one hand, PSD can improve users’ engagement and motivation to change their attitude, behavior, or decision making in a favorable way, which can help them achieve a desired outcome and, thus, improve their wellbeing. On the other hand, PSD misuse can lead to unethical and undesirable outcomes, such as disclosing unnecessary information or agreeing to terms that do not favor users, which, in turn, can negatively impact their wellbeing. These powerful persuasive designs can involve concepts such as gamification, gamblification, and digital nudging, which all have become prominent in recent years and have been implemented successfully across different sectors, such as education, e-health, e-governance, e-finance, and digital privacy contexts. However, such persuasive influence on individuals raises ethical questions as PSD can impair users’ autonomy or persuade them towards a third party’s goals and, hence, lead to unethical decision-making processes and outcomes. In human-computer interaction, recent advances in artificial intelligence have made this topic particularly significant. These novel technologies allow one to influence the decisions that users make, to gather data, and to profile and persuade users into unethical outcomes. These unethical outcomes can lead to psychological and emotional damage to users. To understand the role that ethics play in persuasive system design, we conducted an exhaustive systematic literature analysis and 20 interviews to overview ethical considerations for persuasive system design. Furthermore, we derive potential propositions for more ethical PSD and shed light on potential research gaps.

In-company training is facing new challenges in preparing employees for the demands of digitalized and automated manufacturing. New training concepts like microlearning are necessary to support work-process-related learning. To handle the limitations of microlearning, we develop a 360-degree learning system to demonstrate a realistic work environment. Nonetheless, there is a lack of design knowledge supporting the motivation and performance of employees using the system. Based on a systematic literature review and semi-structured interviews, we have developed design requirements for interactive 360-degree learning environments. We used a workshop-based mixed-method approach with interviews, concept maps, and video analysis to evaluate the motivation and performance of precision mechanics within a prototypical work-process-oriented learning environment in an inter-company vocational training center. The results show a positive effect on learning outcomes and motivation. In addition, the ease of use and sense of presence while using the learning environment are rated as high. We contribute to theory by shedding new light on learners' motivation and performance within work-process-oriented interactive 360-degree learning environments. Furthermore, we offer guidelines for developing such interactive 360-degree learning environments.

Novel technologies such as smart personal assistants integrate digital services into everyday life. These services use personal data to offer personalized services. While they are subject to special data protection regulations at the time of development, there are few guidelines describing the transition from legal requirements to implementation. To reduce risks, services depend on external legal assessments. With developers and legal experts often missing either legal or technical knowledge, the challenge lies in bridging this gap. We observe that design patterns support both developers and legal experts, and we present an approach in which design patterns are leveraged to provide twofold value for both developers and legal experts when dealing with novel technologies. We conducted a revelatory case study for smart personal assistants and scaffolded the case interpretation through cognitive fit theory. On the basis of the findings, we develop a theoretical model to explain and predict the twofold value of design patterns to develop and assess lawful technologies.

Volatility, uncertainty, complexity, and ambiguity (VUCA) are drivers in today's business world. To perform amid this accelerated change and the digitalization progress, organizations are implementing agility. However, such an implementation does not happen without stumbling blocks and some fail. One reason for this is actors’ agile mindset (AM), which is necessary to deal succefully within a VUCA environment. Knowledge of the AM is in its infancy and conceptualization and measuring tools for it are lacking. Furthermore, the relation of the AM in terms of strategic agility and performance is still unclear. Our study aims to close these gaps. We examine AM through 15 interviews and a survey (N = 449) to predict strategic agility and performance. As a result, we conceptualize AM as an attitude that comprises four dimensions: attitude towards 1) learning spirit, 2) collaborative exchange, 3) empowered self-guidance, and 4) customer co-creation. Furthermore, we describe how actors with an AM deal with new technologies. We found that AM affects organizational performance mediated by strategic agility. These findings contribute to the agility and management research by providing a conceptualization and measuring instrument for AM. Furthermore, its relevance for strategic agility is explained and its relationship with organizational performance outlined

Intelligent agents (IAs) are permeating both business and society. However, interacting with IAs poses challenges moving beyond technological limitations towards the human-computer interface. Thus, the knowledgebase related to interaction with IAs has grown exponentially but remains segregated and impedes the advancement of the field. Therefore, we conduct a systematic literature review to integrate empirical knowledge on user interaction with IAs. This is the first paper to examine 107 Information Systems and Human-Computer Interaction papers and identified 389 relationships between design elements and user acceptance of IAs. Along the independent and dependent variables of these relationships, we span a research space model encompassing empirical research on designing for IA user acceptance. Further we contribute to theory, by presenting a research agenda along the dimensions of the research space, which shall be useful to both researchers and practitioners. This complements the past and present knowledge on designing for IA user acceptance with potential pathways into the future of IAs.

Facilitated by AI technology, the phenomenon of cognitive automation extends the scope of deterministic business process automation (BPA) through the probabilistic automation of knowledge and service work. By transforming work systems through cognitive automation, organizations are provided with vast strategic opportunities to gain business value. However, research lacks a unified conceptual lens on cognitive automation, which hinders scientific progress. Thus, based on a Systematic Literature Review, we describe the fundamentals of cognitive automation and provide an integrated conceptualization. We provide an overview of the major BPA approaches such as workflow management, robotic process automation, and Machine Learning-facilitated BPA while emphasizing their complementary relationships. Furthermore, we show how the phenomenon of cognitive automation can be instantiated by Machine Learning-facilitated BPA systems that operate along the spectrum of lightweight and heavyweight IT implementations in larger IS ecosystems. Based on this, we describe the relevance and opportunities of cognitive automation in Information Systems research.