TOWARDS HUMAN-AI-COLLABORATION IN BRAINSTORMING: EMPIRICAL INSIGHTS INTO THE PERCEPTION OF WORKING WITH A GENERATIVE AI

Groups of humans or crowds can be remarkable when coming up with ideas. However, not everyone has a group of humans at their disposal to brainstorm. With recent advances in AI, however, generative large language models (LLM) might be capable of contributing ideas in a brainstorming session, turning individual work of a human into joint work of human and AI. It is, however, unclear, how group effects known from human brainstorming groups transfer to such a human-AI setting. In our mixed-method study (qualitative emphasis) with 24 participants, we investigate how a human brainstorms together with the generative LLM ‘GPT-3’, and how they perceived their experience. Our results highlight known effects like cognitive stimulation but also a risk of free riding. We thereby contribute to the understanding of how generative AI, which is becoming broadly available, can be used to address the challenge of human-AI collaboration for solving open-ended problems

Towards a Virtual Collaborator in Online Collaboration from an Organizations’ Perspective

In this empiric study, we present the specifications of virtual collaboration in times of the Covid-19 pandemic in an organization that worked mostly co-located beforehand, and requirements for a virtual collaborator (VC) resulting from those specifications. Related work shows that a VCs can support virtual teams in achieving their goals and promote creative work. We extend this with insights from practice by observing creative and collaborative workshops in the automotive industry and conducting interviews with facilitators and participants of these workshops. Subsequently, we identify the challenges that participants face in virtual collaboration, and derive design guidelines for a VC to address them. Main problems arise due to the virtual interaction lacking nonverbal communication and in the preparation phase that requires more planning and effort. A VC could help by influencing group cohesion and build networks between the participants, influencing the virtual working environment as well as contributing to the contents

Learning by Doing: Educators’ Perspective on an Illustrative Tool for AI-Generated Scaffolding for Students in Conceptualizing Design Science Research Studies

Design science research (DSR) is taught in university courses and used by students for their final theses. For successfully learning DSR, it is important to learn to apply it to real-world problems. However, students not only need to learn the new DSR paradigm (meta-level) but also need to develop an understanding of the problem domain (content-level). In this paper, we focus on content-level support (CLS), proposing an illustrative tool to aid students when learning to develop a conceptual design with DSR (e.g., for a prototype). Following the DSR paradigm, we deductively identify students’ issues and use the scaffolding approach to develop design requirements (DRs) and design principles (DPs). To offer AI-generated scaffolding, we use the generative language model (GLM) “GPT-3.” We evaluate our illustrative design through 13 expert interviews. Our results show that providing students with CLS is perceived to be helpful, but the interaction with the student needs to be designed carefully to circumvent unintended usage patterns. We contribute DPs and an illustrative instantiation thereof toward a DSR tool support ecosystem. More broadly, we contribute to the understanding of how humans can be supported by AI to solve problems, an important challenge in human-AI collaboration research

Designing and Evaluating a Collaborative Writing Process with Gamification Elements: Toward a Framework for Gamifying Collaboration Processes

In this study, we examine the influence that gamification elements have on collaboration processes in terms of whether they increase intention to continue to use the system based on meaningful engagement and hedonic motivation as well as outcome quality. Therefore, we review gamification models and principles for information systems and consolidate them in a preliminary framework. We then evaluate how one can supplement the collaboration process for collaborative story writing with gamification elements based on the framework. Additionally, we consider specific gamification elements to successfully accomplish the process. To do so, we conducted action design research in a common iterative structure. First, we observed and reflected on the analog collaborative writing process. Next, we derived design principles and remodeled and implemented the process via a Web application instantiation to evaluate them. In the evaluation, we identified the developed design principles’ ability to reach higher hedonic motivation and meaningful engagement, which led to an enhanced intention to continue to use the system. Additionally, we found the potential to manage the shift toward digital collaboration processes that motivate people to participate and produce promising outcomes that do not vary much from outcomes in an analog setting

Designing Mobile Applications for Citizen Participation in Urban Planning

As a result of the increasing requirements for urban planning, a paradigm shift towards citizen participation has evolved to collaboratively address enhancing urban challenges and social conflicts. Past projects have examined urban citizen participation processes and methods to support citizen participation. However, the challenges in the domain of informing, encouraging, and enabling participation at any time are not sufficiently examined and less attention was devoted to urban participation through mobile applications, even if required devices are widely used and can enable permanent communication channels between citizens and planning authorities. Therefore, a design science research project was initiated to examine how to design mobile applications to support citizen participation in urban planning projects. In this paper, the findings of the first cycle are presented including issues, meta-requirements, design principles, the development of a mock-up, and its evaluation to provide insight into the design of mobile applications for citizen participation

Collaboration among Crowdsourcees: Towards a Design Theory for Collaboration Process Design

Crowdsourcing is used for collaborative problem solving in different domains. The key to optimal solutions is mostly found by collaboration among the crowdsourcees. The current state of research on this field addresses this topic mainly with an explorative focus on a specific domain, such as idea contests. We gather and analyze the contributions from the different domains on collaboration in crowdsourcing. We present a framework for a general collaboration process model for crowdsourcing. To derive this framework, we conducted a literature review and set up a database, which assigns the literature to the process steps that we identified from interaction patterns in the literature. The framework considers phases before and after the collaboration among crowdsourcees and includes relevant activities that can influence the collaboration process. This paper contributes to a deeper understanding of the interaction among crowdsourcees and provides crowdsourcers with grounding for the informed design of effective collaborative crowdsourcing processes.

Implementing an Intelligent Collaborative Agent as Teammate in Collaborative Writing: toward a Synergy of Humans and AI

This paper aims at implementing a hybrid form of group work through the incorporation of an intelligent collaborative agent into a Collaborative Writing process. With that it contributes to the overall research gap establishing acceptance of AI towards complementary hybrid work. To approach this aim, we follow a Design Science Research process. We identify requirements for the agent to be considered a teammate based on expert interviews in the light of Social Response Theory and the concept of the Uncanny Valley. Next, we derive design principles for the implementation of an agent as teammate from the collected requirements. For the evaluation of the design principles and the human teammates’ perception of the agent, we instantiate a Collaborative Writing process via a web-application incorporating the agent. The evaluation reveals the partly successful implementation of the developed design principles. Additionally, the results show the potential of hybrid collaboration teams accepting non-human teammates

Exploring AI supported Citizen Argumentation on Urban Participation Platforms

The paradigm shift in urban planning toward citizen participation originates from the Smart City concept, as politicians and scientists argue that citizens should be included in the design of their environment. This led to the development of urban participation platforms and was enhanced by the COVID-19 pandemic as on-site participation was unavailable. Past projects showed that urban participation platforms can reach thousands of citizens, but it became apparent that citizens' contributions vary widely and are sometimes not understandable and comprehensible which limits their value for urban projects. Therefore, we examined how an AI-based feedback system can increase citizens’ argumentation on urban platforms. For this, an explorative comparison of two prototypes was conducted by applying Argumentation Theory and Mayring's qualitative content analysis to empirically analyze collected data. The findings highlight that the developed AI-based feedback system supports citizens and leads to more argumentative and comprehensible argumentations on urban participation platforms

Prototyping a Conversational Agent for AI-Supported Ideation in Organizational Creativity Processes

In this study, we present design guidelines (DGs) for the development and improvement of a virtual collaborator (VC) for Design Thinking (DT). Based on interviews in an ex ante study, we designed a first prototype of a VC. From an ex post evaluation using focus group discussions, we derive strengths, weaknesses, opportunities and threats of the VC. Strengths of the VC are good structure, giving inspiration as well as pace and accuracy. Opportunities are to set level of detail, give a more humane representation, and linking search with other DT phases. Weaknesses are not always suitable content and the VC being rather suitable for research phases as well as one-sided communication and no empathy. Threats are questionable search parameters and too narrow focus of search. We then derived DGs for further improvement of the VC, addressing the weaknesses, threats and ideas from participants

Augmented Facilitation: Designing a multi-modal Conversational Agent for Group Ideation

Human facilitators face the challenge to structure and collect relevant insights from collaborative creative work sessions, which can suffer if they face a high workload. Hence, for effective value co-creation in organizational ideation we suggest an facilitation augmentation with a conversational agent (CA). CAs have the ability to support respective collaborative work by documenting and analyzing unstructured data. Following the design science research paradigm, and based on the literature about facilitation and human-AI collaboration, we derive design principles to develop a CA prototype that collects ideas from a group ideation session and displays them back in a structured (multi-modal) manner. We evaluate the CA by conducting four focus groups. Key findings show that the CA successfully distills and enriches information. Our study contributes to understanding the role of CA in augmenting facilitation and it provides guidance for practice on how to integrate these technologies in group meetings