@inbook{13786, abstract = {{Due to the superior job performing abilities and increasing computational capabilities, collaborating with artificial-intelligence-based services (AIBS or AI-based services) will be inevitable for employees in the service context. AI-based services in the form of virtual (e.g., chatbot) or physical (e.g., service robot) embodiments, which are characterized by a higher degree of autonomy and are intended to augment the tasks of human employees in a highly collaborative way, will increasingly become an integral part of employee’s work environment. Semi-structured interviews and a focus group discussion have been used to identify constructs driving employees’ perception of AI-based services and their impact on wellbeing. Combined with a thorough literature analysis, relations between the identified constructs have been derived from introducing a conceptual model of employees’ willingness to collaborate (WTC). This study identifies technology characteristics, job demands, resources, and control as constructs, directly influencing employees’ perceived risk of AI-based services.}}, author = {{Paluch, Stefanie and Wittkop, Thomas}}, booktitle = {{Artificial Intelligence in Customer Service : The Next Frontier for Personalized Engagement }}, editor = {{Sheth, Jagdish N. and Jain, Varsha and Mogaji, Emmanuel and Ambika, Anupama }}, isbn = {{978-3-031-33897-7}}, keywords = {{Artificial intelligence, AI-based services, Willingness to collaborate, Employees’ wellbeing}}, pages = {{281–302}}, publisher = {{Springer International Publishing AG}}, title = {{{Role of Risk on Employees’ Willingness to Collaborate with Artificial Intelligence and its Impact on Wellbeing}}}, doi = {{10.1007/978-3-031-33898-4_12}}, year = {{2023}}, } @misc{12994, abstract = {{HUMAN 2023 is the 6th workshop of a series for the ACM Hypertext conferences. The HUMAN workshop has a strong focus on the user and thus is complementary to the strong machine analytics research direction that could be experienced in previous conferences.The user-centric view on hypertext not only includes user interfaces and interaction, but also discussions about hypertext application domains as well as human-centered AI. Furthermore, the workshop raises the question of how original hypertext ideas (e. g., Doug Engelbart’s "augmenting human intellect" [7] or Jeff Conklin’s "hypertext as a computer-based medium for thinking and communication" [6]) can improve today’s hypertext systems.}}, author = {{Rubart, Jessica and Atzenbeck, Claus}}, booktitle = {{Proceedings of the 34th ACM Conference on Hypertext and Social Media}}, isbn = {{979-8-4007-0232-7}}, keywords = {{user interfaces, information structuring, decision making, human-centered AI, cognitive aspects, scientific community, digital humanities, user interaction, human factors, user-centric, annotation, adaptive hypertext, hypermedia, collaboration, information systems, augmentation, hypertext, communication, intercultural aspects}}, location = {{Rome, Italy}}, publisher = {{ACM}}, title = {{{HUMAN’23: 6th Workshop on Human Factors in Hypertext}}}, doi = {{10.1145/3603163.3610576}}, year = {{2023}}, } @misc{13020, abstract = {{Developing AI systems for automatic train operation (ATO) requires developers to have a deep understanding of the human tasks they are trying to replace. This paper fills this gap and translates the regulatory requirements from the context of German railways for the AI developer community. As a result, tasks such as train’s path monitoring for collision prediction, signal detection, door operation, etc. are identified. Based on this analysis, a functionally justified sensor setup with detailed configuration requirements is presented. This setup was also evaluated by a survey within the railway industry. The evaluated sensors include RGB/IR cameras, LIDARs, radars and ultrasonic sensors. Calculations and estimates for the evaluated sensors are presented graphically and included in this paper. However, the ultimate sensor setup is still a subject of research. The results of this paper also address the lack of training and test datasets for railway AI systems. It is proposed to acquire research datasets that will allow the training of domain adaptation algorithms to transform other datasets, thus increasing the number of available datasets. The sensor setup is also recommended for such research datasets.}}, author = {{Tagiew, Rustam and Leinhos, Dirk and von der Haar, Henrik and Klotz, Christian and Sprute, Dennis and Ziehn, Jens and Schmelter, Andreas and Witte, Stefan and Klasek, Pavel}}, booktitle = {{Discover Artificial Intelligence}}, issn = {{2731-0809}}, keywords = {{Automatic train operation, ATO, GoA3, GoA4, Perception, AI}}, number = {{1}}, publisher = {{Springer International Publishing }}, title = {{{Sensor system for development of perception systems for ATO}}}, doi = {{10.1007/s44163-023-00066-4}}, volume = {{3}}, year = {{2023}}, } @article{10645, abstract = {{Artificial Intelligence (AI)-based applications promise great potential benefits for companies. However, an isolated consideration of the technical system is not sufficient for the design. Rather, it is necessary to design the entire work system taking into account the socio-technical system approach. This enables the combination of the strengths of people and intelligent systems. This paper presents an approach for a socio-technical requirements elicitation in the design of AI-based systems by adapting the HTO-analysis. First, a mission statement is developed. Based on a detailed process modelling, existing data and systems are recorded. In addition, all relevant stakeholder groups are included by conducting interviews and surveys. Thus, the procedure enables the derivation of a comprehensive catalogue of requirements. The application of the approach is illustrated by using an example from industrial practice, the design of an intelligent workforce planning system.}}, author = {{Gabriel, Stefan and Bentler, Dominik and Grote, Eva-Maria and Junker, Caroline and Wendischhoff, David Meyer zu and Bansmann, Michael and Latos, Benedikt and Hobscheidt, Daniela and Kühn, Arno and Dumitrescu, Roman}}, issn = {{2212-8271}}, journal = {{Procedia CIRP}}, keywords = {{socio-technial design socio-technial design, requirements elicitation, AI-human-collaboration, work design : workforce planning requirements elicitation AI-human-collaboration work design workforce planning}}, pages = {{431--436}}, publisher = {{Elsevier BV}}, title = {{{Requirements analysis for an intelligent workforce planning system: a socio-technical approach to design AI-based systems}}}, doi = {{10.1016/j.procir.2022.05.274}}, volume = {{109}}, year = {{2022}}, } @inbook{6910, abstract = {{AI is on the rise. Powerful cloud platforms and networked software components can perform increasingly complex data evaluations and simulations. Recent research and development projects1 show how great the potential of artificial intelligence is for urban planning. However, despite the impressive, technical possibilities, it currently remains unclear how planning stakeholders and the affected population can be meaningfully involved in the intelligent processes of the "black box". The authors are of the opinion that sustainable urban development planning not only requires acceptance of the spatial planning result, as has been the case up to now, but also requires acceptance of the increasingly digitally supported planning process. For this reason, it must also be possible for laypersons to understand the digital analysis and evaluation processes and to comprehend their relevance and spatial interactions. Consequently, simulations must not only run in the computers of the respective planning or engineering offices, but require a simple, haptic analog translation that can also be used in participation processes as already shown in the CityScope projects2. For this project, the big revitalization project of Deutzer Hafen in Cologne to a future district with more than 9.500 daily users is used as a case study in building a decision support system for urban planning. It is composed of three parts: an agent-based model, a tangible user interface and a synthetic population. The project enables users to get in touch with an agent-based model (ABM) without any knowledge in coding or even interacting with computers. It connects physical objects to digital information. Based on the theories of Castiglione et.al.3 , Gehl4 , Shannon5 and Jacobs6 this project shows how to use an artificial and analog simulation model to measure the urban vitality of the public spaces in the district, based on the activity and travelling patterns of the population. This is done by testing different scenarios in which we change interactive parameters of the model: the use of the buildings and the demographics of the population. We can then determine which scenarios benefit the most life in the public spaces of the district, by finding areas of interest or problematic ones. }}, author = {{Barbosa Jardim, Amanda and Müh, Maximilian and Häusler, Axel and Kondziela, Andrea}}, booktitle = {{ REAL CORP 2021: Cities 20.50, creating habitats for the 3rd millennium, smart - sustainable - climate neutral : proceedings of 26th International Conference on Urban Planning, Regional Development and Information Society}}, editor = {{Schrenk, Manfred and Popovich, Vasily V. and Zeile, Peter and Elisei, Pietro and Beyer, Clemens and Ryser, Judith and Stöglehner, Gernot}}, isbn = {{978-3-9504945-0-1}}, keywords = {{mart Cities, Agent-based modelling, KI/AI, Participation, Tangible Data}}, location = {{Wien}}, publisher = {{CORP - Competence Center of Urban and Regional Planning}}, title = {{{Synthetic and Tangible Agents for an Activity-based Urban Planning Tool}}}, doi = {{10.48494/REALCORP2021.1049}}, year = {{2021}}, }