Recent work has proposed artificial intelligence (AI) models that can learn to decide whether make a prediction for an instance of task or delegate it human by considering both parties' capabilities. In simulations with synthetically generated context-independent predictions, delegation help improve the performance human-AI teams -- compared humans AI model completing alone. However, so far, remains unclear how perform and they perceive when are aware delegated instances them. experimental...

Abstract The fast aging of many western and eastern societies their increasing reliance on information technology create a compelling need to reconsider older users' interactions with computers. Changes in perceptual motor skill abilities that often accompany the process have important implications for design input devices. This paper summarises results two comparative studies 90 subjects aged between 20 75 years. In first study, three devices – mouse, touch screen eye-gaze control were...

On the basis of three empirical studies Fitts' Law was refined for bivariate pointing tasks on large touch screens. In first study different target width parameters were investigated. The second considered effect motion angle. Based results two a model movement time in human-computer interaction formulated. A third study, which is described here detail, concerns validation model. For 20 subjects had to execute task screen. experimental 250 rectangular objects displayed at randomly chosen...

Demographic changes have important implications for the quality of working life. Increasing age is often accompanied by in perceptual, cognitive and motor abilities. The scientifically proven decrease visual acuity with particular importance computer work. In this paper, vision was measured using a standardized eyesight test called Rodatest 302. To investigate age-induced change its impact on human performance, target detection experiment well-known Landolt rings conducted basis three...

Recent work has proposed artificial intelligence (AI) models that can learn to decide whether make a prediction for task instance or delegate it human by considering both parties’ capabilities. In simulations with synthetically generated context-independent predictions, delegation help improve the performance of human-AI teams—compared humans AI model completing alone. However, so far, remains unclear how perform and they perceive when individual instances are delegated them an model....

Leading teams effectively is an essential factor for team performance. Main events where leaders practice leadership are video-meetings which core elements of remote teamwork. However, leading challenging. In particular, in video-meetings, complex due to limitations such as aggravated understanding social signals and dynamics. Voice-based smart personal assistants (SPA) Amazon's Alexa can provide real-time support have the potential maintain effective video-meetings. Therefore, we developed...

Service design helps organisations focus on – and for their most important stakeholders. We argue that although the tools of service can highlight integrate multiple stakeholder perspectives, they cannot adequately address complexity inherent in organisations. This is limiting impact design. Indicators this taking place are a lack support or funding projects, as well resistance ‘cultural’ push back when it comes to implementation.

The fast aging of many western and eastern societies their increasing reliance on information technology create a compelling need to reconsider older users' interactions with computers. This paper summarizes the results 6 years research

The objective of this paper is to examine the impact motivational factors on perceived state quality management systems (QMS) within four small and medium sized companies from different industries in Germany. Although extensive research has been carried out last decade, none acknowledges interrelation between status a QMS existence inherent everyday work routine. Therefore, approach presented focuses emergence relevant investigate potential interdependencies. It was found that supervisor...

Generalized Learning Vector Quantization methods are a powerful and robust approach for classification tasks.They compare incoming samples with representative prototypes each target class.While physically interpretable, they do not account changes in the environment.We propose novel framework incorporation of context information into prototype generation.We can model dependencies modular way ranging from polynomials to neural networks.Evaluations on artificial real-world datasets show an...